Maintworld Magazine 4/2021

4/2021 www.maintworld.com

maintenance & asset management

What led to

this condition? p 22

CAN WE BUILD SANDCASTLES WITH LOOSE SAND? PG 20 AI FACTORY FOR RAILWAY OPERATION & MAINTENANCE PG 32 MAINTENANCE PEOPLE, GET CERTIFIED! PG 44

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EDITORIAL

To Repair or

not to Repair...

WITHOUT any doubt you have already tried to

repair a household appliance and/or an electronic

device. And let me guess, it proved not

to be an easy task. Sometimes spare parts and

technical information are not available. Or you

simply do not succeed to open up the appliance

without causing damage. Throwing it away and

replacing it is then the only solution.

UNACCEPTABLE

In current times of climate change and environmental awareness, people no

longer accept that things cannot be repaired. Many voices call for a shift from a

throw-away society to a more sustainable model. The possibility to repair things

that break plays a major role in this shift. Legislators around the world seem to

have understood the importance of repair.

THE RIGHT TO REPAIR

In July 2021 new legislation has come into force in the UK requiring manufacturers

of white goods and TVs to make repair information and spare parts available

for ten years. In the US, Congressman Joe Morelle introduced a bill in June that

goes even further. In the ‘Fair Repair Act’, both consumers and businesses are given

the fundamental right to carry out repairs on their own equipment. Equipment

manufacturers will be obliged to make available all diagnostic and repair information,

parts, and tools in a timely manner, and on fair and reasonable terms.

In Europe, manufacturers already have to comply with ecodesign directives,

and are obliged to provide spare parts for 10 years. The European Parliament is

also currently considering the introduction of a mandatory repair score. Italy and

France will soon be introducing legislation banning the artificial ageing of consumer

products to extend product lifetime.

REPAIRABILITY BECOMES VISIBLE

France was already pioneering by introducing the ‘repairability index’ for consumer

electronics at the beginning of this year. The easier products are to disassemble,

and the more readily available spare parts and technical information are,

the higher the repair score. Also, the price of the spare parts is considered, next

to some other product-specific criteria, for instance, the number of disassembly

steps. Researchers are currently investigating the impact of the repairability index

both on consumer behaviour, and on product design allowing better repairability.

GAME CHANGER

One thing is clear, the maintenance and asset management community should

embrace the current uprise in awareness of the importance of repair. We will not

only benefit from legislation that is also applicable on industrial assets, but having

consumers thinking about repair might inspire young people to also take up a job

in maintenance in repair. Let’s surf the waves of the right to repair movement!

Wim Vancauwenberghe

Maintenance Evangelist

Member of EFNMS ESHEC (European Health Safety and Environment Committee)

4 maintworld 4/2021

6

The

SPS trade show aims

at “bringing automation to

life” and “covers the entire

spectrum of smart and digital

automation” technology topics.

IN THIS ISSUE 4/2021

36

Corporate

leadership should

support building the Process

Guide by including plant

leadership experts.

=

38

Maintenance

cost is an

important indicator for

a plant’s performance.

6

10

14

16

ICONICS, World Leading Automation

Software Provider & Trusted Partner

in Digital Transformation, to Exhibit

and Present at SPS

Digitalisation of production systems:

The right interfaces for late adopters

What is the big deal about accredited

certification?

Avoiding Unplanned Downtime:

Online Monitor of Critical Bearings

20

22

24

26

32

Can we build sandcastles

with loose sand?

What led to this condition?

OPC UA, MQTT, and Information

Interoperability

Risk Based Inspection

AI Factory for Operation

& Maintenance

36

38

Strategic Success for Shutdowns –

The Importance of C-Suite Support

Benchmarking maintenance cost

in a vacuum

42

3 Ways in Which Manufacturers Can

Manage Their MRO Inventory

44

48

Maintenance people, get certified!

Integrating information for

evidence-based decision making

Issued by Promaint (Finnish Maintenance Society), Messuaukio 1, 00520 Helsinki, Finland tel. +358 29 007 4570 Publisher Omnipress Oy,

Väritehtaankatu 8, 4. kerros, 01300 Vantaa, tel. +358 20 6100, www.omnipress.fi Editor-in-chief Nina Garlo-Melkas tel. +358 50 36 46 491,

nina.garlo@media.fi, Advertisements Kai Portman, Sales Director, tel. +358 358 44 763 2573, ads@maintworld.com Layout Menu Meedia,

www.menuk.ee Subscriptions and Change of Address members toimisto@kunnossapito.fi, non-members tilaajapalvelu@media.fi

Printed by Reusner, www.reusner.ee Frequency 4 issues per year, ISSN L 1798-7024, ISSN 1798-7024 (print), ISSN 1799-8670 (online).

4/2021 maintworld 5

PARTNER ARTICLE

Text and images: ICONICS, SHUTTERSTOCK

ICONICS, World Leading Automation

Software Provider & Trusted Partner in Digital

Transformation, to Exhibit and Present at SPS

The Smart Production Solutions (SPS) Trade Show will happen in Nuremberg, Germany

on November 23 – 25. And as a world leading automation software provider

and trusted partner in digital transformation, ICONICS will exhibit and present at SPS.

This will be our first major international in-person trade show since COVID, and we

are thrilled at the opportunity to see our customers face-to-face again and to help

them solve their operational challenges and meet their corporate sustainability goals.

THE SPS trade show aims at “bringing automation to life” and

“covers the entire spectrum of smart and digital automation”

technology topics. It is also an excellent chance to exchange and

discuss ideas on how to address operational and energy challenges

your company may be facing and spark the imagination for

connected factories, connected infrastructures, and a connected

front on sustainability initiatives.

ICONICS develops software to automate the monitoring and

management of manufacturing and industrial processes. We do

this to help companies reduce their operating costs, be more

efficient, detect faults, improve overall equipment effectiveness,

reduce response times, and so on. The common thread across all

these applications is to focus on specific, measurable factors, and

then connect to the devices, equipment, and environments to

collect the telemetry data. Once all of the data sources are connected,

the trick is to display it in ways that are meaningful to

operators, managers, engineers, and executives. It doesn’t matter

what industry you are in or what type of community you belong to;

we have the tools to display the data to give you real-time information

and real-time wisdom. With this information, you can then

diagnose what’s wrong, what’s happened, what’s inefficient, and

then what corrective measures to take.

The software at work in each of those cases is known

as the ICONICS Suite, and it is a combination of four

elements: GENESIS64, Hyper Historian, AnalytiX®, and

IoTWorX. There is a unique and singular platform service

connecting all of those elements together; not just for the

industry today in its current applications, but also for the

industry as it looks forward to future-proofing the elements

of its systems. And ICONICS Suite is a unified platform

that is competitive, flexible, scalable, and modular, as well

as customizable and extensible. In essence, ICONICS is the

“Switzerland of Automation” with the ability to connect to

virtually any equipment or device.

A key to realizing success in these automation projects

is to start with one specific challenge and then scale up and

out. Start economically and then use that as a baseline to

solve whatever problem you encounter next. And as you

probably know, there is always something else to uncover

once you get started.

Fortunately for the attendees, besides exhibiting at SPS,

ICONICS will also present. Business Development Manager

Sebastian Hohenhoff from our German team will talk on

Tuesday, 23 November from 14:40 to 15:00 about “How


PARTNER ARTICLE

Shopfloor Self-Service Dashboards Improve the Overall

Visibility of Your Production Lines”. Here is a brief glimpse

into what Sebastian will cover in his presentation.

Many manufacturers face the challenge of gathering all relevant

information from different data sources from the shopfloor.

Different vendors provide different systems; some include local

analytics functions while others provide just raw data, if even.

This scattering of information often makes it difficult to provide a

cohesive view of a system and, even in cases where all the data can

be visualized together, it might not be shaped logically for the end

user. Correlating these different datasets with each other is tricky,

and trying to query them using a common set of filters or parameters

can be quite difficult.

To get an overall visibility into the manufacturing process,

it is essential to have a solution which combines all relevant data

from all the various sources into one visualization and analytics

system, no matter who the machine vendor is or what PLC is used.

With ICONICS, the real-time data from the production floor can

be collected via open protocols like OPC UA, Modbus, CC-Link,

and more. Even the use of native and proprietary protocols to

connect to nearly all PLC vendors is possible by utilizing the

Takebishi DeviceXPlorer, which integrates perfectly with

ICONICS’ GENESIS64.

Sebastian will also explain how in order to make visualization

meaningful, just showing real-time data is not enough.

It’s important to have a business intelligence (BI) data model

and information flow engine like ICONICS AnalytiX-BI in the

background. This engine can do calculations with real-time

values, contextualize, and augment these with a variety of meta

data. That meta data can come from nearly any IT source like

relational databases, Kafka, MQTT, web services and more, or

directly from ERP, MES, CRM, or other relevant 3rd party

systems already in place. ICONICS bridges the existing data

silos, gathers and normalizes all that data with user-defined

data models, represents collections of datasets that are logically

related to each other, irrespective of their physical origin,

and allows multi-step transformations of the ingested data for

better shaping and filtering. Striking the right balance between

all of those requirements may seem daunting at first, but by

working with the right solution provider, it is readily achievable

and worthwhile, as it makes the end result even more

powerful.

The outcome of the AnalytiX-BI data model can be visualized

on any smart device, depending on customer preference.

A thick-client installation on a desktop computer can be used or

the flexibility of the HTML5-compatible dashboards can be leveraged

with every current web browser. The dashboards can show up

on large TV screens, tiny smartwatch displays, mobile phones, tablets,

or wearables, responsively adjusting in size to provide the best

possible user experience. The latest ICONICS’ release 10.97.1 even

supports advanced 3D graphics on any modern web browser without

requiring any add-ons, extensions, or plug-ins to be installed.

These more advanced dashboards and visualization features

can be created with ICONICS’ very own GraphWorX64 tool.

But what about the plant manager who is interested in a KPI dashboard

with a focus on Overall Equipment Effectiveness (OEE)

for their entire plant? To address this need, ICONICS has made

self-service dashboards available with KPIWorX. Self-service


PARTNER ARTICLE

means that anyone with access to the visualization system can

easily create dashboards directly from within the browser via

a drag-and-drop feature; no additional software is required. By

using standardized symbol libraries and preconfigured components

(gauges, process points, trends, alarms, grids and more),

a fully functioning dashboard can be created within a matter of

minutes to show the latest real-time and plant-related KPIs.

Additionally, in today’s environment, security of IT and OT

systems is essential. No unauthorized party should be able to read

production data or, even worse, write back malicious or false

data into the system. To prevent cybersecurity related breaches,

GENESIS64 utilizes multiple layers of security. First, to set up,

every installation requires a user with a password to avoid the

danger of completely open systems. To make user administration

easier, the system fully integrates with Microsoft’s Active Directory

for on-premises installations and Azure Active Directory

for cloud deployments. We also strongly encourage the use of

multi-factor authentication, which is supported within ICONICS

applications via OIDC / OAuth2. To secure the domains, SAML 2.0

is supported. To protect the system itself, ICONICS uses binary

signing along with a strong integrity check. VeriSign has signed the

binaries to ensure these have not been tampered with or changed

without authentication. Furthermore, the binaries are obfuscated,

preventing reverse engineering.

Finally, Sebastian will provide a demonstration of our

ICONICS software, so attendees can see firsthand how their

organizations can benefit from our system automation platform.

If you can’t make the presentation, come by our booth

to talk to our team. You can find the ICONICS booth in Hall

5-159, in close proximity to our technology partners like

Microsoft, the OPC Foundation, and Takebishi.

Providing Industry Solutions for Today

and for the Future

Advances in technology, no matter the application, occur

at an incredibly fast pace. To stay competitive, it’s imperative

to stay up to date. But there is an upside to this – it’s

fun! And going to trade shows like SPS is not only an amazing

experience, it is educational at the same time. If you

are planning on attending, stop by for a chat. We’ll get you

up to speed on our latest automation software and digital

transformation technology and get you and your company

on the road to operational efficiency and sustainability.

ICONICS provides industry solutions for today and for the

future. It’s what we do.

Want to know more about how the ICONICS Suite can

help your company with its system automation, digital

technology transformation, and sustainability initiatives?

Watch at your convenience an array of informative, interesting,

and relevant sessions from our ICONICS Connect 2021

event at iconics.com/Connect2021


PARTNER ARTICLE

Digitalisation of production systems:

The right interfaces for late adopters

The fact that digitalisation of production systems is progressing has become an

established consensus among manufacturers, operators, and service providers

in the mechanical engineering sector. At the same time however, statements

such as the following from T-Systems often cause uncertainty among OEMs in

the mechanical engineering sector: “Digitization is disrupting existing”.

Dipl.-Ing. JAKOB DÜCK, Global Industry Segment Manager

THE CORRELATION, as well as the resulting

transformations of business models and

the associated risks, must be viewed in a

highly differentiated manner. The mechanical

engineering sector in particular,

featuring its typical structure of SMEs and

"hidden champions", is in a very good position

worldwide to perceive digitalisation

not as a threat but as an opportunity to

expand existing business models and, over

the long term, to open up new markets by

leveraging new technologies. In the final

instance, it is clear to all business players

that digitalisation will secure the longterm

competitiveness of OEMs in the mechanical

and plant engineering sector.

Which arguments support such a view?

1. Digitalisation can only be

successfully mastered in many

individual steps. For those involved,

this cannot be about all-encompassing

umbrella functionalities, as described

under the terms "IIoT", "Industry

4.0", "Digital Engineering" and the

like. Far more, it is about concrete

approaches that can be used to advance

the efficiency and cost-effectiveness

of machines along the entire "life

cycle" with as little input and effort

as possible. And because automation

in mechanical engineering has been

driven principally by digitalisation for

decades, it is primarily those OEMs

that can successfully implement

these approaches based on their core

competencies. Only OEMs are able

to implement specific measures that

combine existing functionalities and

systems with the most promising


PARTNER ARTICLE

new control and data transmission

technologies! [2]

2. Digitalisation in industry is often

mentioned along with the keyword

"Industry 4.0", a term which stands

for the 4th industrial revolution:

consequently, the disruptive potential

of current technical developments

is equated with the effects of the

industrial use of steam engines,

electricity and computers. Successful

players such as Amazon, Microsoft and

Google are often cited as prominent

examples of the forces of change. In the

case of the medium-sized mechanical

and plant engineering industry, on

the other hand, these developments

appear at least partly as a threat. The

protagonists of digitalisation are

endeavouring to take the edge off

this. Hans Beckhoff, the founder and

CEO of Beckhoff Automation, very

aptly explained during an IHK event

in 2017 that these changes and shifts

represent opportunities for industrial

manufacturing and that the speed of

the upheaval is slower than initially

assumed: "From today's perspective,

the introduction of the steam engine

seems like a revolution. However,

at the time it took more than half

a century for its use in industry to

result in substantial changes." In a

similar manner, he stated, one should

regard the impact of digitalisation for

industrial production today, which is

triggering an evolutionary development

at all levels and in all processes. At the

same time, Beckhoff also emphasises

that this realisation by no means

guarantees that one should sit back and

do nothing! According to Beckhoff, it is

precisely the courageous protagonists

who will be rewarded if they creatively

develop new business models for

production systems.

HARTING has analysed the

implementation strategies of its

customers and can decidedly confirm

Beckhoff's theses. Accordingly, in

order to achieve sustainable success

with digitalisation projects, it is above

all advisable not to want to achieve

everything immediately [3].

Whether the development is revolutionary

or evolutionary: All parties

involved agree that data forms the basis of

more rational processes - and indeed all

types of data. The catch phrase "Data is the

new oil!" originally referred to "Big Data"

or the storage and availability of consumer

data. But this characterisation can certainly

also be applied to data in the industrial

arena. However, to stay with the metaphor,

this "new oil" still requires functioning

"pipelines" and other structural elements.

Consequently, "Data is the new oil" not

least describes the current situation of

many machine and plant manufacturers

who are in the process of revising the generation,

processing and transmission of

data for their products.

The OEM's "data view" of production

systems today can be summarised as follows:

- OEMs are experts for many existing

technological, machine-related data, as

well as for the use of this data in intrinsic

machine functions, and for advanced automation

functions

- The increased use of the "internal

intelligence" of automation components

such as drives, smart sensors, actuators or

HMI systems with all the associated data

transitions is also part of an OEM's standard

toolkit today

- In addition, this comprises all possible

data transfer layers on the level of interlinked

machine or production lines that

use known data origin, machine, user and

process models, which are also considered

proprietary know-how

- However: In terms of digitalisation,

not all the aforementioned data structures

and transmission layers that are part of the

control and automation systems should

simply be "discarded" and replaced by new

ones. This is due to the fact that almost the

entire functionality of modern production

systems is based on software and suitable

specific interfaces - these functionalities

have been developed with an enormous

amount of material and engineering effort.

Consequently, an initial conclusion is

as follows: In order to drive digitalisation

forward with as little effort and input as possible

and to cope with the associated rising

data volumes, machine and plant manufacturers

must be able to continue to use existing

data structures and interfaces!

In the sense of ‘the data is the new oil’

analogy, proven and sufficiently functional

"pipeline structures" must continue to be

used and extended to include new "pipelines".

In this way, companies will succeed

in enhancing their competitiveness and

gaining new market shares in their own

business segment or in other fields of production

technology. To put it in terms of

control technology for industrial systems:

An OEM active in mechanical engineering

needs its proven fieldbuses and interfaces


PARTNER ARTICLE

for evolutionary digitalisation. At the

same time, suitable physical interfaces are

advantageous for the expansion of new

systems and services in the edge areas, as

well as for the most seamless connection

possible to the world of "Big Data". Players

mastering both disciplines will be best

equipped to meet the growing and, in some

cases, still unknown future requirements

of machine users.

The trend-setting requirements for

developments related to digitalisation

outlined in the following section are based

on the experience of the HARTING Technology

Group. The company provides

solutions for all types of data interfaces

of modern drive, control, HMI and communication

technology in mechanical engineering

production systems. HARTING

is also a pioneer in many ground-breaking

developments for power and signal transmission

in the industrial arena. In the

field of Industrial Ethernet, HARTING is

playing a key role in shaping and designing

various standards on the physical layer: for

example, the company is actively involved

in solutions for the so-called SPE (Single

Pair Ethernet) technology.

Decades of experience in the field of interfaces

for factory automation, combined

with the expertise of a trendsetter in the

latest data transmission technologies (including

the "Big Data" world), make it possible

from HARTING's viewpoint to always

find optimal solutions on the physical layer

for each and every specific interface design.

With the help of the right interfaces, OEMs

can decisively drive the migration to digitalisation

forward that is so vital for them.

In each solution here, the respective application

with its mechanical, environmental

and EMC conditions and other requirements

must remain leading.

"What is the simplest and most effective

way to design data transmission interfaces

in production systems - at all conceivable

levels of the factory and all the way into

the 'cloud'? " This question often causes

headaches in the R&D and engineering departments

of machine building companies

that want to gradually shape and design

individual actual digitalisation aspects in

their projects. The requirements that need

to be met are as follows:

- All types of data interfaces should be

implementable, both well-proven but also

current innovations

DIGITALISATION WILL SECURE THE LONG-TERM COMPETITIVENESS

OF OEMS IN THE MECHANICAL AND PLANT ENGINEERING SECTOR.

- The range of interfaces must be scalable,

i.e., the same interface type can be designed

in the required normative version,

IP protection class or for the required environmental

conditions (EMC, resistance

to dirt, UV radiation, mechanical stresses

such as shock & vibration or the hygiene

requirements)

- With regard to the transitions between

sites or sections, it must be possible to use

interfaces that function reliably and conform

to standards

- Product variants must be available

that are designed for different manufacturing

and assembly processes at the OEM,

e.g., for tool-free assembly if flexibility is

required, or for automatic assembly in the

case that higher quantities are to be manufactured

in connection with a high level of

process reliability

- Data interfaces must be combinable

with each other and must be placeable with

other signal and power interfaces in one

enclosure or even together in one insulator

in order to save space and costs and to simplify

processes.

The approach outlined above allows developers

and project managers to concentrate

on the central tasks for their respective

application during the design phase

- without having to spend time on the "less

important criteria" of interfaces. At the

same time, they can be certain that there

is a suitable interface available for every

expansion stage of a machine module or a

data transmission link. The corresponding

solutions are both cost- and functionoptimised

and scalable. The cost-efficient,

technically straight forward expansion of

services and system extensions at all levels

of factory automation and beyond can be

implemented at any time, even retroactively,

at the respective machine user.

Figure 1 presents the approach in an

exemplary way: It provides an overview

of the best-known network systems for

industrial data transmission and describes

selected actual HARTING solutions, which

are shown as product families. It is apparent

exactly how great the freedom in the

design of the data interfaces actually is:

for practically every type of field bus or

Industrial Ethernet there are several options

available for designing the physical

layer. This means that it is (almost) always

possible to find a solution that is optimally

suited to the application - even for requirements

that are still unknown today and/

or for digitalisation requirements that are

growing along with the application.

SOURCES:

[1] T-Systems: Accelerate Digitalisation (t-systems.com)

[2] HMS: "The goal is to generate value from data."(industry-of-things.com)

[3] HARTING: http://www.us- tech.com/RelId/2651702/ISvars/default/Weighing_the_Cost_and_Benefits_of_Digitalization_in_Manufacturing.htm


YOUR PARTNER IN

ULTRASOUND

INSTRUMENTS

Leak Detection

Bearing Condition Monitoring

Bearing Lubrication

Steam Traps & Valves

Electrical Inspection

TRAINING

CAT & CAT II Ultrasound Training

Onsite Implementation Training

Application Specific Training

CONTINUOUS SUPPORT

Free support & license-free software

Online Courses

Free access to our Learning Center

(webinars, articles, tutorials)

UE SYSTEMS

www.uesystems.com

info@uesystems.com

CONTACT US FOR AN

ONSITE DEMONSTRATION

CERTIFICATION

What is the big deal about

accredited certification?

Being certified is just

about passing a test,

right? If you can pass the

test, surely that is proof

that you are worthy of

being certified, right?

And as long as there are

no obvious and easy

ways to cheat, surely the

examination process is

adequate, right?


JASON TRANTER,

ARP

Mobius Institute

AS THE OWNER of two organizations that

provide training and accredited certification,

I have a different opinion that I

would like to share. So yes, I am biased,

but we have done things the hard way

for very good reasons (and the ISO is on

my side – or should I say, I am on their

side).

To train or not to train, that is

the first question

Not that it is specifically related to the

accreditation process, but people often

ask why training is required to be

certified by Mobius Institute.

First, the condition monitoring

standards (ISO 18436) defined by the

International Standards Organization

(ISO) require that training is completed.

They define the topics that must be

covered and the duration of the train-

CERTIFICATION

ing. But even the Asset Reliability Practitioner

(ARP) certification requires

training, and it is not part of the condition

monitoring standards.

The reason the ISO choose to require

training, and why the author agrees with

that decision, is because an exam can

only cover a limited set of questions - it

is hoped that a person who is certified

would have much broader and deeper

knowledge. Although there are typically

100 questions on an exam, it is impossible

to test on every single subject. And

on most exams, you only have to get 70%

of the questions correct.

Therefore, we believe that a person

who is certified should have been

educated in a structured manner to a

healthy level of depth on all of the relevant

topics – not just know enough to

get by. The exam "simply" ensures that

they understand certain facts, concepts,

and principles and can apply their

knowledge.

Should you need experience

to be certified?

Again, the ISO condition monitoring

standards require that candidates meet

certain experience requirements which

must be independently verified. For

example, an ISO 18436-2 Category II

vibration analyst must have 18 months of

experience before they can be certified.

But again, if you can pass the exam

why do you need to prove that you have

experience? In the author’s opinion,

the requirement to have experience not

only ensures that certified personnel

can deliver greater value, but it also adds

weight to the meaning of being certified.

If a person is smart enough, they can

learn just enough to get through the

exam potentially without ever having

tested a machine or visited an industrial

site. An employer or consulting client

should have some confidence that a

certified person has at least a minimum

level of competence. Verified experience

provides that confidence.

Can’t the exam be written so

that only competent people

can pass?

There are certainly those who believe that

is true, but the author is not one of them.

First, when most exams have a

70% pass grade, any questions that do

require experience do not even need

to be answered correctly. But you may

like to try to think of an exam question,

that has four multiple choice options,

that only a person with experience can

answer correctly, without there being

any requirement to work in any specific

industry (i.e., you can’t ask a question

about paper mill reliability, or a question

specific to mining). And if you can come

up with such a question, well done, now

you only have to write 99 more before

the exam is ready to go.

So no, even though we ensure that

our exams are as practical as possible

(i.e., not just calculations, recognition of

acronyms and definitions, etc.) I do not

believe that only a person with genuine

experience can pass.

WHEN A NEW CERTIFICATION

PROGRAM IS DEFINED IT

MUST BE APPROVED BY

THE ACCREDITATION BODY.

What is the difference

between accredited and

non-accredited certification?

In short, accredited certification has

been audited by an independent,

Government approved entity that

ensures that what the certification

body does is fair, independent, and

that it meets all of the requirements.

While there are standards like

ISO 18436 that define how condition

monitoring certification works, there

are many certification programs

that are not specifically

defined by the ISO. ARP,

CMRP, CRL, and CRE

are all such programs.

Rather than defining

every last detail of how

every single certification

program should operate,

a standard has been

developed, ISO/IEC 17024, that defines

the core elements that every personnel

certification program must meet.

Accreditation bodies such as ANSI,

JAS-ANZ, and UKAS can then audit

certification bodies such as the

Mobius Institute Board of Certification

(MIBoC) and SMRP to ensure that

everything is clean and aboveboard.

When a new certification program

is defined it must be approved by the

accreditation organization. It will then

be audited every six months for the first

two years minimum and then every

12 months thereafter.

They check everything.

They randomly select a large number

of certified candidates and ensure

they were trained correctly, examine

correctly, they meet the experience

requirements, and much more. They

also ensure that our personnel follow

all procedures, that we have an effective

quality control process in place, and

that everything we do in relation to the

examination process meets the highest

standards. That is why we video record

people taking exams, there must be

invigilator’s, we have exam databases,

and much more.

I could easily make this an extremely

long, detailed, (and boring) article by

explaining all of the details behind our

committees, examination development

and statistical analysis, and much more -

but I will save you from the detail. Let us

just say that no stone is left unturned to

ensure that everything is done correctly.

As a business owner, there are

numerous situations where decisions

must be made in line with the certification

and accreditation requirements

versus decisions that would lead to

greater revenue and profit. But that is

the way it needs to be if certification

is to be respected by those who are

certified and those who wish to employ

certified personnel. So yes, accreditation

matters.


CASE STUDY

Avoiding Unplanned Downtime:

Online Monitor of Critical Bearings

ADRIAN MESSER,

CMRP, UE Systems

adrianm@uesystems.com

Keeping a close eye on the condition of critical equipment

is fundamental in any industrial facility. When

critical bearings fail, it almost always leads to unplanned

downtime and interrupted production process,

costing companies thousands in production loses.

IN THIS CASE STUDY we will look at how an online monitoring

solution using ultrasonic sensors was able to detect an issue on

a critical bearing before it turned into a big problem.

Critical equipment: bleach decker in a pulp and

paper plant

Usually, in pulp and paper plants we will find a wash floor or

wash area, where the paper comes through to be thoroughly

cleaned / bleached. That job is done by a machine called a

bleach decker, which is considered a critical and fundamental

piece of equipment for production operations.

In this particular plant, which has a predictive maintenance

program in place, it was decided to invest in online monitoring

for these machines. The maintenance team wants to be alerted

as soon as anything unusual is happening with the equipment

in order to prevent any failures that would lead to a stop in

production. This machine has 4 bearings, of about 48 inch /

120 cm diameter, rotating at 3 RPM.

To enable online monitoring and early failure detection,

ultrasonic sensors are being used on the machines’ bearings.

These are UE Systems Remote Access Sensors, which are permanently

installed on the bearings and constantly collect decibel

readings and sound recordings. All this data is then sent to

a central processing unit called the 4Cast. This unit is connected

to the Internet and will alert the maintenance team (e-mail

and SMS alerts) when certain decibel levels are reached.


CASE STUDY

Bleach decker with the ultrasonic sensor mounted on the bearing

The sensors are connected to the 4Cast, a central processing unit

with internet connection

Why ultrasound?

The preference for ultrasound technology to monitor these

bearings has to do with its obvious advantages: since the

ultrasonic sensors monitor the bearings’ friction levels, any

increase in friction will be noticed. This allows for a very early

warning of failure. Also, because the data from the sensors

comes in the form of decibel readings, it is easy to interpret:

the higher the friction, the higher the dB value. When this value

reaches a certain limit above the baseline, an alarm is sent.

And, even more relevant to these bearings, ultrasound is the

most efficient technology to inspect slow speed bearings. The

bearings on this machine are rotating at 3RPM. At such slow

speeds, it is generally extremely challenging to notice any issues

using technologies such as vibration analysis or thermography.

But ultrasound shines when the subject is slow speed bearing

monitoring, especially when you can record the sound from the

bearing, analyse it in a sound spectrum software and check if

the amplitude shows any peaks, which normally indicate a fault.

Thus, ultrasound is the perfect technology when we want to

online monitor slow speed critical bearings.

Failure detection with online monitoring using

ultrasonic sensors

Everything seemed to be fine with the bleach decker at this

pulp and paper facility, as the machine was working as expected.

However, the 4Cast, an ultrasonic online monitoring

system, received an unusual decibel reading from one of the

ultrasonic sensors. The NDE (non-drive-end) bearing of this

bleach decker was registering 17dB when, normally, a bearing

rotating at such slow speeds like 3RPM should simply show a

0dB reading.

This, of course, triggered the system to immediately alert

the maintenance team. The 4Cast was setup to consider any

reading above 8dB on this bearing to be a high alarm, and

therefore, the following alert was sent from DMS, the UE Systems

software where all the data from the 4Cast is stored:

We can clearly see why the alert was triggered: the 4Cast

received a 17dB reading from a bearing where the threshold for

a high alarm was setup at 8dB. The alert message also contains

useful information regarding the machine (operating floor

slow moving bearing; bleach decker) and, naturally, a time

stamp of when the reading was taken.

When an alarm level is reached, the 4Cast will also take a

sound recording from the bearing for further analysis. This

is especially useful in slow speed bearings, where the sound

spectrum can tell us a lot about what’s going on with the asset.

In this case, and even though the machine was apparently

working as expected, the sound file spectrum showed a very

different story.


CASE STUDY

The peaks shown in this sound sample clearly indicate a

problem with the bearing. Also, when reproducing the sound

file, we could very clearly hear the impact noises. The failure

was even more obvious when the sound file was compared to

a sound recording from one of the other bearings.

We can clearly see the differences. In this case, the recording

sounds smooth and looks uniform, and we don’t see

amplitude peaks at all. So, this would be an example of how

the sound spectrum of a good bearing should look like.

The next step for the maintenance team was scheduling

the replacement of this bearing, without disrupting production.

When the bearing was dismantled, the damage was

clearly visible.

The signs of impact are obvious. Also, metal fragments

were found in the shaft, plus spalling, with some pitting, and

slight abrasion were present in the outer race.

Conclusion

By detecting the issue at an early stage, the maintenance team

was able to replace the bearing during scheduled downtime

and without disrupting the production process. We can imagine

the consequences if the issue was not detected at this stage

and the bearing was allowed to continue operating: the metal

fragments would certainly affect the motor shaft, which would

then also need to be replaced; and the facility would have to

face unplanned downtime. In such a situation we could be

looking at a loss of around 250K GBP.

By using the proper technology, with the proper maintenance

procedures in place, the team was able to identify and

solve the issue before it became a major problem. This case

study shows how powerful ultrasound technology can be,

especially when used in sensors connected to the network to

provide truly online and permanent monitoring solutions.


PARTNER ARTICLE

Can we build sandcastles

with loose sand?

How apparently worthless data, can still be useful

The Internet of things, big data and prescriptive

maintenance are supposed to be the big promises

from the 21st century. No more unplanned downtime

because we can predict all failures. Many companies,

however, struggle with these developments. They

say there is hardly any data available and question

the usability. It appears to be “loose sand” … until you

start working with it.

PETER DECAIGNY

MAINNOVATION,

Peter.Decaigny@

mainnovation.com

THE FIELD of maintenance is developing.

More and more, maintenance and

asset management are mentioned

in the same breath. Where maintenance

focuses mainly on the present

and nearby future – the assets need

to function to be able to deliver the

required production or service – asset

management is more about long-term

planning, life-cycle issues, and modernization.

The goal is to monitor the

lifespan of the assets and start investment

projects at the right time to guarantee

safety and reliability.


PARTNER ARTICLE

Poor data quality?

Executing asset management requires

knowledge about the expected lifespan,

use, degradation and, eventually,

failure of assets.

– Our experience is that companies that

think they only have low-quality data, at

least have these figures at their disposal,

says Peter Decaigny of Mainnovation.

– And they are more useful than

you think.

Companies that are ruled by the illusion

of the day – they are operating like a fire

brigade with a focus on corrective maintenance

– struggle to see the big picture.

– Everyone is busy, malfunctions

regularly occur and most attention is

paid to solving them as quickly as possible.

The misconception is that registration of

this downtime is just 'loose sand'. However,

if you compare the downtime (in hours)

with the frequency of failure - the number

of failures - you gain insight into which assets

often cause downtime for a long time.

These are the assets you need to pay attention

to, Decaigny says.

– By looking for the cause or reason

for the downtime, perhaps they can be resolved

or removed.

– We gain insight into the 'Mean Time

Between Failure' and also the 'Mean Time

to Repair' and this helps to draw the right

conclusions.

Incoherent?

In another case there is a fair amount of

data available, but there seems to be no

connection. It seems like an incoherent

story from which no conclusions can be

drawn. But here too the message is 'just

start with what you do know'.

The first step is collecting and analysing

data. If the analysis only raises questions

and does not provide any insight, it is advisable

to take a critical look at the representation

of those figures.

– We can, for example, plot the Time to

Failure in chronological order. So how many

weeks did it take for an asset to fail. This

could just result in an arbitrary number of

figures. From 120 weeks, to 40 weeks, to 16

weeks and then suddenly 118 weeks again.

It is difficult to draw conclusions from this.

We see companies making the mistake of

taking an average. In this example, one

would replace an asset before the 74th week,

but is that 'just in time' or is this capital

destruction? Data can often initially lead to

confusion instead of insight.

– But don't give up, Decaigny says.

– Start to combine data. Use other

models that compare different values to

the Time to Failure. Or focus on the peaks.

What causes the outliers?

Big data

Mainnovation has clients within plants,

fleet and infra. This means great versatility

in assets. From power stations,

tank storage companies and industrial

installations, to transport and various

infrastructure companies.

– Every asset is unique. Even comparable

assets have unique factors such

as the method of use, the level of maintenance

and the skills and tools of the

operators and the technical service are

of influence, explains Decaigny.

THE INTERNET OF

THINGS, BIG DATA AND

PRESCRIPTIVEMAINTENANCE

ARE SUPPOSED TO BE THE BIG

PROMISES FROM THE 21ST

CENTURY.

– Furthermore, there are, for example,

weather influences or the pressure

or humidity that can have negative

effects on the materials. We know the

term 'a Monday morning product', but

that should be adapted to ‘a Tuesday

afternoon product’, because statistically

that turns out to be a bad production

moment. How come? Nobody knows.

With this Decaigny wants to emphasize

that we cannot just blindly rely on

numbers.

– It starts with data. And by working

with it you can improve the data. Then

it will become clear that the factor 'temperature'

– as an example – must also

be taken into account. And who knows,

you might discover that the Thursday

afternoon operator prefers to work with

an open window.

Value drivers

A correct analysis of the available data is

therefore of great importance. Not only

when minimal data is available, but also

when we use big data and take various

external factors into account. Moreover, it

becomes increasingly difficult to compare

apples to apples and to draw conclusions.

Another approach to get started with data

is to first determine what the most important

value driver is. In other words: what should

we aim for in order to create value with maintenance

and make a positive contribution to

the operating result.

– That can differ per company, even per

factory, explains Decaigny.

– While one wants to aim for maximum

uptime, because the demand for the product

is very high, the other may have to focus on

cost reduction. There is also value in reducing

(security) risks or perhaps it is better to invest

in modernization now because this has economic

added value in the long term.

These are the four value drivers from

Mainnovation's VDM XL methodology.

– And whoever wants to steer in four directions,

will eventually come to a standstill, so

that's never a good idea.

Compare

In the first example we mentioned in this

article – where it was all about minimizing

downtime – the focus was on asset utilization

and improving uptime. In this case we

opt for the value driver cost control. If this is

the mission, we should collect data to help

make decisions about operational expenditure

(OPEX). But how do you know whether

these costs are too high and can possibly be

reduced?

Decaigny has a simple answer to this

question:

– Compare, for instance by benchmarking.

Mainnovation has a benchmark database

of more than 1.000 companies. Comparing

data with companies in the same industry,

provides a realistic picture of the improvement

potential. By dividing the investment

amount by the replacement value, large

companies and small companies can still be

compared.

– For this big data is not a must. But it is

important to choose the right data. By comparing

apples to apples, you know where you

stand and what the possibilities are to take

steps forward to bring you closer to your

business goal, states Decaigny.

So, we have seen that it is good to take the

plunge and just get started. Even if it seems

like loose sand, it is possible to build sandcastles.

A final tip that Decaigny also likes to

give is:

– Make it visible. Let the shopfloor participate.

Show the data, show the improvements

so that people also understand which

buttons they have to turn – literally or figuratively

– to get even more positive figures.


PARTNER ARTICLE

What led to

this condition?

Everything is fine? That shouldn't make us invisible

18 pumps under the responsibility of a Condition Monitoring team,

demonstrating an almost identical behavior, with identical symptoms… and

surely calling for full attention. A user (meaning a friend, a member of the SDT

family) asked me to assist. I was happy to join the party.

TEXT: HARIS TROBRADOVIC I IMAGES: SDT, SHUTTERSTOCK


PARTNER ARTICLE

We are so dedicated to look for a root cause of each failure,

to prevent it from re-occurring. Well, let’s look for a root

cause of success with the same dedication and invested effort,

to make sure it does re-occur.

FIRSTLY, I looked at all the Ultrasound data one by one, and all

of them looked quite similar to the one shown above.

After detailed examination of the entire data set, I found

ABSOLUTELY NOTHING WRONG. With no hesitation, I

called some people much cleverer than myself, to review all

the vibration data and they came back with the absolute same

conclusion about the condition – they found ABSOLUTELY

NOTHING WRONG.

Although it seemed that the party was over, the best part

was yet to come: some Root Cause Analysis (RCA), root causes

of that condition and maybe some recommendations. “If it

wasn’t in a newspaper, it never happened”.

One might think that there was no reason to do an RCA, and

that there was nothing to report, because everything was fine.

Well, we thought that we had a perfectly good reason for RCA

and a proper report.

Because everything is fine

Just a summary of the issued report:

As you can see, there is a lot to report. That excellent

condition did not happen all by itself. There were decisions,

investments, training, people … and lots of knowledge and care

involved to come to the point where we found no issues in the

collected data.

Let’s look at ALL heroes,

not just some of them

Usually, I read about finding a defect, a potential failure. That

is, of course, good. It justifies the use of technology, it proves

the competence of the expert using it and it proves that Condition

Monitoring is a lifesaving approach, so to speak.

But, finding a defect, even in the earliest stages, is never

good news.

It is surely better than waiting for an asset to start sending

smoke signals and fail, but in its essence; it is not good news.

Nobody celebrates when a medical diagnostician finds a

problem, even in the early stages. It proves that he uses proper

technology in a proper way, it proves that he is a good expert.

But that is not good news.

Look at how it developed over the years, moving from full

reactive behavior to predictive. Years ago, companies were

celebrating people coming in at 3 am to repair failed assets,

purely reactive. Those people had a complete exclusivity on

heroism. That was wrong, of course.

Then, we learned a lesson, and started celebrating those

who detect problems much earlier, Condition Monitoring. It

didn’t go smoothly, there was a lot of effort invested in writing

a report about success, because it is not an easy task writing

about something that would cost X $ if not addressed in time.

Practically, reporting an absence of a huge problem by showing

a presence of small one. Showing an egg that would become a

dragon.

People easily notice the presence of a bad

event, but fail to notice the absence of one

Moving to a proactive mindset makes recognizing heroes even

more tricky. How do you convince management about the danger

coming from a dragon, when you don’t even have an egg to

show? How do you report the absence of a big problem without

having a small problem to show? How do you report the complete

absence of problems? How do you connect that absence

with your work? And, on top of that, how do you translate it to

a language that fits the business targets?

Tricky, isn’t it?

Condition Monitoring is much more than just detecting

anomalies. We should not forget that an important (and surely

desirable) part of the job is to confirm good condition. And

that should be the most satisfying part of the job; issuing a report

saying that you can confirm all the assets are working fine.

That doesn’t mean that your technology doesn’t work well.

That doesn’t mean that you are not good at it. It just means

that your work improved the Reliability to the level where

you do not have so much detected problems to show. But you

should show the absence of them.

Make a success root cause analysis and report it.

Then … share the glory with those who made it possible.

Those whose job is to make sure you have nothing to detect.

The lubrication community is one of them.

Let’s start bragging with perfect signals coming from perfectly

operating assets

… and explaining why that is so.


PARTNER ARTICLE

OPC UA, MQTT, and

Information Interoperability

In earlier times, OPC learned a hard lesson that tying a specification to a specific wire

protocol leads to obsolescence as technology evolves. This is why OPC UA has layered

architecture, which makes it possible to create mappings for any number of transports

like JSON HTTP or UA TCP for Client/Server and MQTT or UA UDP for Pub/Sub.

By STEFAN HOPPE, President OPC Foundation

WHEN OPC releases a specification,

they try to provide mappings for what

the market has initially indicated they

want, only to find that sometimes the

uptake may be diminished (e.g., AMQP).

The power of OPC UA is that these mappings

can be quickly modified to implement

new mappings that better match

market needs (e.g., MQTT). When a

future technology emerges, a such as

QUIC/HTTP3, OPC UA is ready.

The reason protocols can be added as

needed is because the value of OPC UA

comes from information interoperability,

which exists no matter what protocol

is used to communicate. OPC UA provides

a standard framework for describing

information that can be accessed by

Client/Server or Pub/Sub. This enables

a level of plug-and-play between applications

from different vendors that

cannot be achieved by simply standardizing

the message format and topic tree.

This is particularly true for cloud-based

applications that need to integrate data

from many sources.

This is why Erich Barnstedt, Chief

Architect, Standards & Consortia, Azure

IoT at Microsoft, shared that, “One of


the questions I get quite a lot is “should I

use OPC UA or MQTT to send industrial

data to the cloud?” My answer is always

the same: Use both! OPC UA for the

payload and MQTT for the transport.

Let me explain:” “First of all, comparing

the two technologies is an apples-to

oranges comparison, as OPC UA is an

application while MQTT is a protocol. It

is like asking: “Should I use web pages or

the Internet Protocol for my website?” I

think you get my point...” The emphasis

on the need for information interoperability

was also why the OPC Foundation

and CESMII joined forces to create the

OPC UA Cloud Library, which enables

the publishing and discovery of standardized

OPC UA Information Models as

a component of the Smart Manufacturing

Innovation Platform and Profiles. In

their July 2021 press release, CESMII

stated, “The key to new levels of innovation

and performance will only be

achieved when information, and associated

context, can flow freely in the enterprise,

to users and applications that

need that information.” Delivering reusable

Information Models is a strategic

component of the Cloud Library.

The protocol independent architecture

of OPC UA also allows for synergies between

applications that would not necessarily have

anything in common. For example, all of

the major automation vendors are investing

heavily in OPC Foundation’s Field Level

Communication (FLC) initiative, which is

based entirely on UA Pub/Sub using UDP.

For these applications, MQTT simply cannot

provide the capabilities that the controller-to-controller

FLC applications require.

On the other hand, the UA Pub/Sub infrastructure

developed for FLC will enable

connectivity to the cloud via UA Pub/Sub

over MQTT because the overall architecture

and configuration model is the same. This,

in turn, will mean a lot of OPC UA commercial

off-the-shelf (COTS) products will be

available that can push data to the cloud via

UA Pub/Sub over MQTT. In the long term

this means a much greater selection of products

will be available to factory owners that

need to connect their factories to the cloud.

This emphasis on information interoperability

and protocol adaptability makes

OPC UA the best long-term solution for any

factory owner looking to leverage MQTT

and a means to connect their factories to the

cloud.

Online Condition

Monitoring

Be Vigilant over your critical assets

• Ultrasound

• Vibration

• Temperature

• Tachometer

• Process

A turn-key

condition monitoring

solution combining the versatility

of ultrasound, the analytics of vibration,

standard communication protocols and an

embedded trending and analysis software.

RISK MANAGEMENT

Risk Based Inspection

TEXT: PDM

Every now and then, the world is shocked by incidents, such as explosions,

emissions of toxic gases, or large fires. For instance, you will recall the giant

explosion of 2,750 tons of ammonium nitrate in the Beirut harbor on August 4,

2020. Such incidents are nightmares that must be prevented at all times.

THIS ARTICLE focuses on one aspect of risk

reduction in the process industry, namely

the risks of static asset failure. It presents

a methodology that helps companies to

focus on the most critical static assets. That

focus is necessary because in an average

plant there simply are too many static assets

to always keep an eye on.

Risk Based Inspection is an effective

and efficient method because it contributes

to the integrity and reliability of static assets

in industrial facilities. It helps to properly

allocate the inspection resources to the

static assets with the highest risk profiles

that need the most attention.

Risk Based Inspection (RBI) is an

effective and efficient inspection management

& planning methodology. RBI contributes

to the integrity and reliability of

static assets in industrial facilities. It helps

to properly allocate the inspection resources

to the static assets with the highest risk

profiles that need the most attention.

Therefore, it is recommended to use RBI

as a default method, especially during large

maintenance projects, rather than waiting

for static asset failures, with related unsafe

situations and consequential damage.

RBI is considered as part of the Risk

Based Maintenance (RBM) approach and is

also seen as a way of working towards Condition

Based Maintenance (CBM).

Static assets and risks

STATIC AND MECHANICAL ASSETS

There is distinction between static and

mechanical assets. The simple fact that

mechanical parts contain rotating or moving

parts usually leads maintenance departments

to pay more attention to these.

Generally speaking, mechanically energized

rotating or moving parts often break down

relatively fast during operation. The movement

of parts tends to create friction, heat

and vibrations that cause wear.

However, these are not a valid reason to

neglect the static parts in industrial facili-

RBI BEST PRACTICES – API 580 / 581

This white paper is based on the API 580 “Risk Based Inspection” standard, which was

issued by the American Petroleum Institute for application to static assets in refining,

petrochemical, and chemical plants. This standard describes the minimum requirements

by providing essential guidelines for the implementation of an effective and

usable RBI program.

The API 581 “Risk Based Inspection Technology” standard compliments these guidelines

by detailing the appropriate methodologies and procedures to be followed. For

example, it provides quantitative calculation methods to determine an inspection plan.

The standards provide the basic RBI system design and is a great starting point for

those wishing to begin with RBI initiation.

There are other international standards that can be used in addition to or instead

of API 580/581, for instance, the European standard EN 16991 “Risk-based inspection

framework” and PCC-3 “Inspection Planning Using Risk-Based Inspection”, issued by

ASME (American Society of Mechanical Engineers).


RISK MANAGEMENT

ties, because these are subject to different

deterioration mechanisms, for example

corrosion under insulation (see textbox).

Static assets are typically used for the

construction of plants or for storage and

transportation of fluids. These fluids are

often dangerous, especially in chemical

installations.

The integrity and reliability of mechanical

assets is the domain of Reliability Centered

Maintenance (RCM), while static assets

are the subject of Risk Based Inspection.

Despite the similarities in approach

of RCM compared to RBI, for example with

regard to the risk matrix, RCM is beyond

the scope of this document.

Static assets

Static assets are parts of industrial facilities

that do not contain rotating or moving

parts. An average plant can easily number

more than a hundred such static assets, for

example:

• piping systems

• storage tanks

• (pressure) vessels

• heat exchangers

• asset housing or casing

• load-bearing structures.

Examples of mechanical assets are pumps,

rotating shafts, conveyor belts, turbines,

engines, and robot arms.

FAILURES OF STATIC ASSETS

The process industry faces some major issues

that imply that Risk Based Inspection

is part of the solution to a broader problem

than the failure of static assets:

• Corrective maintenance is often carried

out too late (after the outage),

preventive maintenance often too early

(better safe than sorry)

• Cost-inefficiencies and low uptime /

availability levels due to unplanned stops

• Inadequate degradation models, limited

standardized guidelines, lack of specialized

(technical) tools.

Corrosion under insulation (CUI)

Corrosion under insulation (CUI) is a degradation

mechanism that occurs in insulated

pipes and appliances and it is one of the major

threats to the aging assets of our contemporary

industry. It is a difficult phenomenon to

control because the locations where it occurs

are difficult to detect. The rate of degradation

depends on many factors and is difficult to

predict. Corrective action is on average necessary

after 20-30 years of operation. Potentially,

the degradation of steel pipes and other

equipment by CUI can lead to major incidents

due to loss of integrity. To prevent this, corrective

measures worth billions of euros are

being taken.

In order to reduce the risks associated with

failure mechanisms, these mechanisms must

be well understood, while control measures

must be defined to ensure the integrity and

reliability of the installation. The control

measures consist of inspections, monitoring,

adjustments & repairs.

Improved system integrity, fewer unplanned

stops, lower maintenance costs,

and higher production are examples of the

benefits and positive results of Risk Based

Inspection.

DELIVERABLES OF RISK BASED

INSPECTION

RBI results in five related deliverables (see

Figure 1):

1. Prioritization of high-risk components:

WHAT to inspect

2. Determination of inspection intervals:

WHEN to inspect

3. Expected damage mechanisms: WHERE

to inspect

4. Selection of best inspection method:

HOW to inspect

5. Data requirements for continuous improvement:

WHAT to report.

To obtain these deliverables efficiently, RBI

follows a structured process.

THE RBI PROCESS

The RBI process as shown in Figure 2 consists

of a loop with six steps:

1. Data and information collection

2. Risk assessment

3. Risk ranking

4. Inspection plan

5. Mitigation

6. Reassessment.


RISK MANAGEMENT

Step 1: Data and information collection

The RBI process is initiated with a data and

information collection phase. This is needed

to understand the characteristics of the

primary processes, especially the damaging

effect of the process mediums (chemicals)

in the static equipment. This step provides

accurate and up-to-date information for the

next steps in the RBI process. The primary

goal is to convert all that data into a suitable

risk-based inspection plan for continuous

condition monitoring, periodic inspections,

and larger turnarounds.

To enhance the failure-forecasting capability,

the RBI database must include the

following up-to-date information:

• Description of failure mechanisms

• Corrosion studies, especially of corrosion

under insulation (CUI), a notorious

equipment killer

• Degradation models per process.

Data is typically collected through detailed

process analysis in conjunction with longterm

corrosion and degradation studies for

each part of the static equipment involved.

Collecting and processing this data can

take a lot of effort, requiring a long-term

perspective, especially when different information

systems are involved. Many large

companies have already built a library of

degradation models.

Data for RBI analysis

Data normally required for an RBI analysis

may include, but is not limited to:

• Type of equipment (original parts, replacements,

or modifications; remaining

lifetime)

• Materials of construction

• Inspection, repair, and replacement

records

• Process fluid compositions

• Inventory of fluids

• Operating conditions

• Safety & detection systems

• Deterioration mechanisms, rates, and

severity (e.g., corrosion, corrosion under

insulation, metal fatigue, stress, or

chemical attack)

• Personnel densities

• Coating, cladding, and insulation data

• Business interruption costs

• Equipment replacement costs

• Environmental remediation costs.

A library of degradation models is the cornerstone

of all maintenance strategies. Such

a library is a prerequisite to switch from

rule-based or time-based inspection to riskbased

inspection.

Step 2: Risk assessment

For each part of the static equipment

the probability of failure and the

consequences of failure are assessed,

based on data from the RBI database.

The probability of failure analysis

should address all deterioration mechanisms

to which the equipment being

studied is susceptible.

The following consequences of failure

must be considered:

• Financial aspects

• Health aspects

• Environmental aspects

• Regulatory consequences.

RBI addresses the concerns of many

plant managers:

• Declining integrity of installations

• Failure of static assets and its

consequences (massive repairs,

unplanned stops)

• Insufficient availability and reliability

of installations

• Consequences of failure for business

(costs, HSE, etc.)

• Safety of employees and local residents

(getting injured, burned, or

poisoned)

• Clean environment (hazardous


leaks, powerful explosions, emissions of toxic gases)

• Requirements imposed by the authorities (high fines,

plant closure).

The probability is typically expressed in terms of frequency

(categories ranging from 1-5), while the consequences

are ranging from “A” (minor) to “E” (severe).

Next, the risk of failure is calculated, which results in risk

categories, “high”, “medium”, “low”.

Risk of failure

=

probability of failure x

consequences of failure

RoF = PoF x CoF

The assessment of overall plant risk is highly complex.

That's why a multidisciplinary team with a broad expertise

is needed. The RBI process involves multiple stakeholders

and various engineering backgrounds. The judgment

of old hands in the profession is to be considered

particularly valuable, but even for them it remains quite

difficult to estimate the risks in the first place.

Step 3: Risk ranking

To prioritize the risks and to communicate the results of

the analysis a risk matrix can be used, like the example

shown in Figure 3 (a 7x7 matrix is also common). The risk

categories (RoF) are plotted in the matrix of probability

categories (PoF) by consequence categories (CoF).

The analysis, as depicted in the risk matrix and substantiated

by quantitative data, is used to optimize priorities

and intervals for the inspection planning. Equipment

items residing towards the right upper corner of the matrix

should take priority, because these items have the

highest risk. These are the most probable failures with

the most severe consequences. In contrast, items residing

towards the left bottom corner of the matrix will tend to

take lower priority, because these items have the lowest

risk.

Like for many other phenomena, the Pareto principle

is applicable for RBI, as it turns out that a large percentage

of the total unit risk will be concentrated in a relatively

small percentage of the equipment items. So, from

all equipment items that are competing for attention, the

idea is to review the inspection plan focusing on those

components with the highest risk.

Step 4: Inspection plan

After the risk ranking, engineers try in collaboration with

corrosion engineers to design an inspection plan that gives

priority to components with the highest total risk. Material

degradation and failure mechanisms will continue to

develop, no matter if the act of inspecting is carried out or

not. Inspection serves to identify, monitor, and measure

these mechanisms before becoming critical. The inspection

serves as a continual risk-updating and reduction effort,

merely in terms of knowing what is currently going on

with the static assets that are being utilized.

RISK MANAGEMENT

Limited resources and manpower

prevent thorough inspections of all

static assets, especially when costly

inspection methods must be used in a

relatively short period of time. Because

the inspection plan allocates the inspection

resources to the static assets with

the highest risk profiles, while avoiding

unnecessary regular inspections

on non-critical items, RBI is actually a

cost-cutting maintenance strategy. The

potential savings on inspection cost are

20-40 percent by implementing RBI.

Categories of inspection

To identify, classify, analyse, and evaluate

failure mechanisms, RBI uses three

categories of inspection:

1. Visual inspection: external inspection.

2. Invasive inspection: opening-up assets

to take samples and examining

CUI.

3. Non-destructive inspection: endoscope,

Eddy-current, acoustic emission

and vibration analysis.

The risk ranking will not provide a

straightforward indication of the type of

inspection; this needs to be determined

per item by choosing the inspection method

that is sufficient for detecting the deterioration

mechanisms and its severity.

Typical situations where risk management

through inspection may have

little or no effect are:

• Corrosion rates well established,

and equipment is nearing end of life

• Instantaneous failures related to

operating conditions such as brittle

fracture

• Inspection technology that is not

sufficient to detect or quantify deterioration

adequately

• Too short a time frame from the

onset of the deterioration to final

failure for periodic inspections to

be effective (e.g., high-cycle fatigue

cracking)

• Event-driven failures (circumstances

that cannot be predicted).

Step 5: Mitigation

If completed inspections have shown

that the inherent overall risk of a static

item is acceptable or relatively low

when compared to other evaluated

static items, no further mitigation

measures may be necessary. However,

since the whole idea revolves around

tackling static items with the highest

risk, more often than not some form

of mitigation has to be considered. For

effective risk reduction you can devise

measures that limit the consequences

and probability. To prevent future

failures, it may be necessary to repair,

modify, or renew parts of the installation,

or to shorten the time interval

between turnarounds or regular inspections.

RBI can potentially be used as a steppingstone

to condition-based monitoring

as it provides an organization with

the ability to gain valuable insight into

their highest risk items of static equipment,

which is routinely inspected. The

initial investments in condition-based

monitoring, including complex sensors

and software packages, can be quite

high, but can also be seen as a form of

mitigation.

Step 6: Reassessment

The previous steps are all based on

particular moments. As time goes by,

changes that could affect the probability

or consequences of failure are inevitable.

Therefore, it’s important that the

facility has an effective Management of

Change process that identifies when a

reassessment is necessary. The RBI reassessment

concerns:

• Inspections

• Process and hardware characteristics

• Maintenance (strategies / approaches).

Many deterioration mechanisms are

time dependent. Typically, the RBI

assessment will project deterioration

at a continuous rate. These rates

may vary over time. Through inspection

activities, the average rates of

deterioration may be better defined.

Some deterioration mechanisms

are independent of time, e.g., they

occur only when there are specific

conditions present. These conditions

may not have been predicted in the

original assessment but may have

subsequently occurred. Inspection

activities will increase information

on the condition of the equipment

and the results should be reviewed to

determine if a RBI reassessment is

necessary.

By creating and using predictive

degradation models, combined with

routine inspections and testing as efficiently

and effectively as possible,

RBI allows for long-term monitoring

of static assets. In the context of

continuous improvement being

embedded in the RBI approach, the

RBI process should be repeated after

the cycle has taken place and the necessary

investments in risk reduction

have been made. Keep in mind that

there will always be some degree of

residual risk as all risks can never be

completely eliminated. The aim of

RBI is to reduce this residual risk to

an acceptable level.


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DIGITALISATION

Industrial AI

Part III: AI Factory for

Operation & Maintenance

RAMIN KARIM, DIEGO GALAR

AND UDAY KUMAR,

Division of Operation and

Maintenance Engineering Luleå

University of Technology

All over the world, industries are boarding the

digital train and exploiting the power of new

and emerging technologies, such as Artificial

Intelligence (AI), Deep Learning (DL), Machine

Learning (ML), Big Data analytics, and Digital

Twins, to enhance competitiveness and make

operations competitive and economically viable.

HOWEVER, transitioning to digitalisation

to manage the complex engineering assets

effectively and efficiently is a challenging

task, as it requires the use and

integration of various tools, technologies

and models.

The move to implementation of

new and emerging technologies requires

availability and accessibility to

data and information, as well as domain-specific

physics-based models

to gain deeper insight into industrial

processes, thus facilitating correct de-


DIGITALISATION

Figure 1. Generic concept of 'AI Factory'

Figure 2. AI Factory defined Analytics Autonomy Level (AAL), (Karim et al, 2021)

cision-making by considering all relevant

and contextual information. In

this transformation journey, data and

models are considered digital assets

(ISO55000) that reflect the current

health of an asset; and processing such

data permits a glimpse into the future

trends of an asset’s health and its performance

from a life cycle perspective.

However, to establish effective and

efficient asset management using a

life cycle perspective and to exploit

the power of new technologies, we

need appropriate concepts, methodologies,

tools, and technologies,

especially given the requirements

of different types of assets and the

associated domain-specific challenges.

More specifically, industries

are facing challenges developing and

implementing AI to increase the level

of autonomy in maintenance, especially

in the contexts of maintenance

and repair needs assessment, task

planning, resource allocation, task

execution, performance assessment,

and continuous improvements, whilst

considering the relevant contextual

information.

The digital transformation of industry

requires deeper insights into the

operational domain of assets, prevalent

business and governance models,

and regulatory regimes to adequately

address the challenges. From a digital

asset management perspective, the

main challenges are related to source

integration, distributed computing,

content processing, and cybersecurity.

A technology platform could bridge

research findings with innovative solutions

that are scalable for the transformation

of industries. These platforms

could provide digital pipelines between

data providers and data consumers,

as illustrated in Figure 1. We label this

concept the AI Factory (AIF). Each

pipeline represents a set of orchestrated

activities aimed to extract, transfer,

load, and process data between the

provider and the consumer; pipelines

are configurable entities, which can

utilise a palette of technologies for

communication, storage, and processing

to enable context-adaptability and

meet the users’ requirements. The selection

of appropriate technologies for

each pipeline should be based on the

context-specific requirements such as

requirements for scalability, authentication,

and authorisation.

To facilitate the development of

line-of-production and to select the

appropriate technologies in the AI

Factory platform, an Analytics Autonomy

Level (AAL) needs to be developed;

see Figure 2. The AAL aims to

identify the maturity level of analytics

in an organisation aim


DIGITALISATION

Figure 3. AI Factory’s model-driven and data-driven architecture

ing for industrial AI. When the digital

and AI maturity of an organisation are

identified, a roadmap can be developed

to support a data-driven approach based

on the current needs and future opportunities.

AI Factory (AIF:) Content and

products

The AI Factory is a virtual technology

platform which integrates technologies

and tools to facilitate engineering

and business solutions by exploiting

the power of data and data-driven

technologies. Of course, organisations

have been using data in their decisionmaking

processes for centuries, but

an AI factory platform also considers

contextual information enhancing the

quality of decision-making process.

Furthermore, the AI Factory also integrates

and uses models based on physic-of-failure

to develop engineering and

business solutions through a use-case

approach.

Digitalisation and the emerging

technologies have made an enormous

difference to the way data is collected

DIGITALISATION AND THE

EMERGING TECHNOLOGIES

HAVE MADE AN ENORMOUS

DIFFERENCE TO THE WAY DATA

IS COLLECTED AND USED FOR

DECISION-MAKING.

and used for decision-making, and this

provides the foundation for the structure

of AI Factory and its architecture.

First, digitalisation has enabled a

set of digital infrastructures in society,

industry, and transport that can be

used in various contexts, such as sharing

data and models. Second, computing

technologies have given society,

industry, and transport (among others)

the ability to run on a digital infrastructure.

Third, Internet of Things (IoT)

and sensor technology have augmented

human senses with the capability to

sense and measure new phenomena,

provided as data flowing throughout

the digital infrastructures. Finally, AI

has enabled us to discover knowledge

from a vast amount of data, using a

digital infrastructure and computing

power. These four ingredients have

changed the concept of the data-driven

approach.

Today, the data-driven approach is

associated with complex fact-based

decision-making processes using digital

infrastructures, distributed computing

(cloud/edge), sensor data, and

augmented analytics empowered by

AI. The fundamental idea of the datadriven

approach is the same: making

decisions on facts (data).

In many areas, including the maintenance

of transport systems, the datadriven

approach promises better accuracy

via fact-based decision-making,

leading to operations excellence and

system sustainability with respect to

economy, technology, and the environment.

However, the mere availability

and accessibility of data provided by an

appropriate information logistics system

is not sufficient for good maintenance

decision-making. Data needs to


DIGITALISATION

be processed, analysed, and interpreted

using digitalisation and AI technologies.

Context awareness is another important

aspect which needs to be considered

in maintenance decision-making.

Context-awareness is the ability to

sense the context in which a decision

will be made, and adapt the analytics

and information logistics to support

the decision-making process.

The following essential aspects must

be considered in a data-driven approach:

• Information logistics, representing

the digital infrastructure

• Analytics, representing knowledge

discovery through a set of algorithms,

fed by data from the information

logistic infrastructure

• Context-awareness, representing

a set of situations for which decisions

will be made, i.e., the purpose

of analytics.

To improve the accuracy of analytic

services, the AI Factory implements

an architecture that integrates modeldriven

and data-driven approaches in

a seamless manner, as illustrated in

Figure 3

AI Factory for Operation

and Maintenance

The ongoing digitalisation and implementation

of AI-technologies in operations

and maintenance depend on the

availability and accessibility of data

for geographically distributed systems.

Lulea University of Technology has

created AI Factory (AIF), a seamless

platform built on loosely coupled storage

and computing services for data

sharing. AIF is a set of smart cloud/

edge-based data services that aim to

accelerate digitalisation in industry

and transport. AIF services provide capabilities

such as acquisition, integration,

transformation, and processing

of asset-related data across all stakeholders,

where services can be invoked

on-premise or in multiple cloud-based

environments. AIF is applicable to

numerous industries. For example,

AI Factory for Railway integrates technologies

and business requirements

and other historical and contextual

information to gain deeper insight into

the performance of railway assets.

AIFs overall architecture rests on

four main pillars; see Figure 1:

• A technology platform

• A digital governance platform

(eGovernance)

• A communication platform

• A coordinating platform

An important aspect to consider when

developing decision-support solutions

based on AI and digital technology is

the users’ experience. The user experience

(UX) design process aims to

create relevance, context-awareness,

and meaningfulness for end-users. In

railway contexts, applying a humancentric

model in the development of

AI-based artefacts will enhance the

usability of the solution, with a subsequent

positive impact on decisionmaking

processes. Therefore, the

analytics services in AI Factory are

combined with other technologies such

as Virtual Reality (VR), Augmented

Reality, Mixed Reality (MR), and so on,

to improve user experience (UX) in AI

implementation.

ASSET MANAGEMENT

Strategic Success for Shutdowns –

The Importance of C-Suite Support

How do the C-Suite leaders ensure they have given the proper

direction and support, so that plant(s) have a clear message and

guidance on what STO’s mean to their company’s success?

IF YOU ASK MOST C-SUITE leaders if

they have long range planning, they will

commonly respond with a resounding

“YES”. This article’s intent is to look at

the inclusion of Strategic Asset Integrity

as part of the plan. Many times, it is left

to the plants to figure out what should be

done to “keep it running”.

Challenges without

C-Suite Support

This can create problems from the very

beginning of the process, due to overall

company alignment:

• Plants do what they think is right

with little to no direction

• They consequently do it differently

from one plant to another

• They do not measure success the

same way

• They have budgets and timing “edicts”

handed down, with little to no input

from plant subject matter experts, as


ALAN WARMACK,

DIRECTOR/PARTNER,

MARSHALL INSTITUTE

INC.

to the work scope needed in the plants

to ensure we have the appropriate

time and budget to accomplish the

right work on the right assets.

• Start dates are moved backwards

and forwards, with no thought of

the impact to the STO plan that

the plant personnel are trying to

work to, nor how it affects procurement

issues such as locking

contract resources, materials, etc.,

which cost additional money and

can have adverse effects on the

performance of the STO’s objectives

being achieved.

Industries call these events by different

names, typically based on which business

sector you fall in. Shutdown is typically

used in manufacturing and mining, Turnaround

is typically used in the energy sector,

and Outage is typically used on utilities going

down (HVAC, Compressed Air, etc.)

ASSET MANAGEMENT

Regardless of what you call it, an STO is

essentially a predetermined period, when

a defined set of planned activities are to be

completed. The work to be accomplished

should be activities that can only be performed

while the plant is out of service.

Personnel in the plant are the ones who

struggle to make these events successful.

The question we should ask is why do they

struggle to create a plan that will successfully

achieve the end results that are expected?

Oftentimes, it can be because they

don’t know what corporate leadership’s

expectations are.

It is very common to see the following

types of issues among companies in a wide

variety of industries. Below is an example

from the Petro-Chemical and Refinery Association.

*

• 95 % of post-SD recommendations

are not implemented

• 90 % of SDs do not reach expected

goals

• 90 % of SDs have scope creep of

between 10–50 %

• 80 % of SDs exceed planned costs

by 10% or more

• 50 % of SDs overrun

Importance of C-Suite

Support

It is critical that STOs are included in C-

Suite discussions when determining long

range plans. Most C-Suite leaders will

ensure they have looked at future trending

expectations, such as sales and marketing,

new product development, major expenditures

for plant expansions, brownfield

plant closures, bringing greenfield plants

online, etc.

These long-range planning meetings

should include plant management, which

will provide updates related to long term

asset conditions of the existing assets within

their plants, which would assist with an

overall understanding of the company’s

strategies over the next 5 – 10 year’s plans.

Which assets will need replacement? What

regulatory items will dictate certain timing

of outages at the site?

This is a great opportunity for the

company’s leadership to develop company

goals and drivers, with input from

the plant’s leaders, thus gaining an overall

alignment as to why the company performs

STO’s, what their importance to the health

of the company is, and how they support

the Corporate Vision and Mission. Only

then can the plant leaders can return to

their plants with a clear method of communication

on what, why, when and how.

Integrated Activity Plan

As C-Suite begins this inclusion to their

long-range planning efforts, more effective

decisions will made in direct support of

their company’s future goals and objectives

in coming years. This is called Integrated

Activity Planning. (IAP)

As the Integrated Activity Plan is formulated,

with input from all functions of

the company, decisions can then be made

in a more rational and productive manner

for all functions. Examples of corporate

leadership supporting the company’s longterm

strategies include which plant(s)

should be taken down at certain times of

the year, what sequence should the plants

go down, how to best support the market

by transitioning product flow in advance

of a plant STO event to minimize sales

impacts, what major expenditures will

LONG-RANGE PLANNING

MEETINGS SHOULD INCLUDE

PLANT MANAGEMENT, WHICH

WILL PROVIDE UPDATES

RELATED TO LONG TERM ASSET

CONDITIONS OF THE EXISTING

ASSETS WITHIN THEIR PLANTS.

be made, based on the function of each

facility, etc. These decisions should be influenced

by the plants providing their predicted

work scope, based on their plant’s

individual long-range plans. This will assist

in developing viable timing of events, as

well as a clearer understanding of future

budgeting projections.

Once the Plant Managers have this

corporate plan, they can be much more

confident in making the proper decisions

on how their STO events will be managed,

once back at their sites. They will be able

to develop their plant’s goals and drivers,

which will directly support the long-range

corporate plans. This will create significant

synergies between the company and the

plants. Corporate leaders will have greater

confidence that the sites are now managing

each site’s STO based on goals and drivers

in support of the company’s vision and

mission.

Corporate Process Guide

After development of the Integrated

Activity Plan, it is critical that corporate

leadership supports building a Corporate

Process Guide that will be used as

guidance to all plants on what a good

STO should look like. This will ensure

all plants have a clear, standardized

path to follow. Of course, each plant will

have to make minor changes based on

their size and complexity, but the point

is, while they may have to perform the

functions differently, they should be doing

these key functions. This provides a

good means for corporate to better compare

plant STO performance and results

when plants are being reviewed.

Corporate leadership should support

building the Process Guide by including

plant leadership / subject matter

experts. This allows each plant to have

input as to the content of the guide,

increasing a sense of ownership, as opposed

to an “edict” being passed down

from Corporate. They are the experts

on these events. They know what works

and what does not work. Including

them will provide a much better process

which will create alignment between

corporate and the plants, allowing a

greater chance at proper implementation

back at their site.

In Summary

These are considerations for the initial

phase of STO development. This article

touched on topics at a high level, and

there are many other details which must

be included, but it is meant as a sampling,

which hopefully if implemented will

assist in ensuring plant asset integrity

is properly supported. This will create

order for the plants, to support the company

with increased asset integrity to

support greater production, revenue, and

decreased spending.

When strategic plans are developed at

the C-suite level, individual plants gain

clarity on their ultimate targets. This clarity

provides them the ability to set their

plant-level STO strategies in support of

their company’s vision.

Not only does strategic clarity empower

each site or plant to execute shutdowns

successfully, it can and arguably should

increase safety while optimizing duration

and cost.

*WORLD CLASS Shutdown MANAGE-

MENT LESSONS BENCHMARKING,

National Petrochemical and Refiners Association,

David W. Fontenot


PARTNER ARTICLE

Benchmarking

maintenance

cost in a vacuum

It is very common that a company or a plant tries to benchmark

its maintenance cost. The maintenance cost/ton or maintenance

cost/unit is typically the benchmark of most interest.

BUT THE EFFORT to benchmark the

maintenance cost/unit produced is quite

futile if it is the sole focus. Why? First,

because the maintenance cost is extremely

hard to compare between plants

due to variability of the following:

• Company definition of maintenance

cost

• Local tax laws

• Currency exchange rate variations

(If comparing internationally)

• Company practices (and ethics)

• The maintenance debt

• Difference in production flow

• Difference in equipment selection

and engineering before plant

start up

• The age of the equipment

Second, the maintenance cost by itself

is not very interesting or even very relevant.

Perhaps it can be compared with

baseball pitches or ice hockey slap shots,

which are roughly the same speed.

A good pitch or slap shot is a tad over

100 mph. Many are obsessed with measuring

the speed of a pitch or slap shot,

but is it relevant? A little bit, but neither

baseball nor hockey is about fast pitches

and hard shots, it’s about winning the

game. Similarly, the name of the game for

any company in the world is one thing,

profit! That is why companies exist.

A paper mill in Canada had one of the

highest maintenance costs ($ Mtce cost/


PARTNER ARTICLE

ton) in the industry, but they were the

most profitable ($ profit/ ton). The mill

spent money on maintenance:

• Precision repairs

• The correct materials

• The right maintenance tools for

everyone

• Trained their people

• Organized the technical data such

as Bill of materials, equipment

registers, added work order history,

etc.

All these items cost money, mostly temporarily,

and increased the maintenance

cost. What was their return on investment?

They achieved exceptional

equipment reliability and could sell

more product. Therefore, the revenues

increased a lot more than the total cost

even though their maintenance cost was

relatively high.

The point is that the maintenance

cost by itself is not very interesting to

benchmark, and in some cases, completely

misleading for any relevant business

decision. Sub-optimizing by performing

a maintenance cost analysis by

itself is a mistake that can lead to poor

decisions by top management.

The reality I see is that many maintenance

organizations are completely

focused on reducing maintenance cost

and/or to keep within the maintenance

budget. But it is important to understand

that if the product manufactured

can be sold with a profit margin, meaning

that sales price/unit is larger than

the cost/unit to produce it, reduced

downtime (therefore increased production

time) will be more important than

cutting the maintenance cost.

It should be mentioned that there are

other factors in an organization's operation

that are important beside profit and

cost. Those factors are not explored in

this article since the focus is on maintenance

cost. Some examples of other

important factors are:

• Quality of the product. There are

few things more expensive than

poor quality.

• Safety

• Environmental compliance and

awareness

• Follow all regulations including

over and above safety and environment

• Leadership ability

• Skills

• Ethics

• Culture (perhaps just an outcome

of all above, but still)

Is Maintenance Cost / Estimated

Replacement Value (ERV)

the right benchmark to use?

A popular benchmark is the Maintenance

cost / Estimated Replacement

Value (MC/ ERV). Many consultants

have promoted this as a great number


PARTNER ARTICLE

to compare between plants. Some

have even claimed that 2 percent is

“best practice”, or “world-class”. The

2 percent is often used regardless of

what industry that is being benchmarked.

Referring to the variance

in the numerator (if a/b=c, then a is

the numerator i.e., the maintenance

cost) that we have extensively covered

above, we know that the maintenance

cost varies greatly. Trying

to benchmark the MC/ERV between

industries is preposterous and incompetent.

Take a simple example of a conveyor

belt that transports iron ore

outside in a hot, humid environment

to a similar belt that transports wood

chips indoors in a northern paper

mill. The wear of the belt that carries

rock in the sun will be more than the

one that carries wood chips indoors.

Therefore, the maintenance cost will

be higher. A pump that pumps room

temperature water wears differently

compared to one that pumps bitumen

in the oil sands.

Adding to the uncertainty of Maintenance

Cost/ Estimated Replacement

Value, is the ERV itself. Few

plants have a correct number for the

estimated replacement value since

the actual depreciation of the assets

hasn’t been kept up correctly.

Is Maintenance Cost

Useless to Benchmark?

No, it is not useless to benchmark

maintenance cost. Maintenance

cost is an important indicator

for a plant’s performance.

But, the maintenance cost must

be put in perspective with all factors

described above. The age,

past maintenance performed,

the initial investment quality

(Life Cycle Costing), and all other

factors must be analyzed. It

would be impossible to make an

analysis that encompasses all the

important factors that include

maintenance cost. Therefore, the

number shouldn’t be analyzed as

a “stand-alone” number.

What should, and can, be

analyzed is the maintenance

cost performance over time in a

specific plant without comparing

it to other plants. The cost

should be analyzed together with

a set of additional “balancing”

KPIs such as Overall Production

Efficiency (OPE), total cost, revenue,

etc.

WHAT SHOULD BE THE MAIN

GOAL FOR A MAINTENANCE

MANAGEMENT IF IT’S NOT REDUCING

MAINTENANCE COST?

Let’s look at the maintenance cost from

one more angle. If reducing maintenance

cost is the key goal for a maintenance

department, it is a very easy goal to

achieve. Simply stop doing any maintenance

work and your cost will be zero,

goal achieved! Some may say that the

idea above is silly, no mine, plant or mill

would do that. Of course not, but why

wouldn’t they?

If you stop doing maintenance work,

the equipment and the plant stops running,

and your revenue will go to nil.

Plants should define what the outcome

of the maintenance department should be.

It is a critical discussion to have because

it changes the whole approach to maintenance

in an organization. The product of

maintenance work should not be service, it

is not repair, it is not cost. The outcome of

maintenance work is equipment reliability.

If the goal for maintenance is to deliver

equipment reliability instead of reduction

of maintenance cost, high reliability will

reduce the cost over time, and you will get

the best of both worlds.


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SMART MAINTENANCE

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UNDERHALL.SE

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ASSET MANAGEMENT

Ways in Which

Manufacturers

Can Manage Their

MRO Inventory

Modern facilities are focused on streamlining production processes while lowering

operational costs and eliminating equipment downtime. Managing inventory for

different departments within an organization can be nerve-racking. Facilities must

maintain sufficient stocks of replacement parts, tools, safety supplies and other

consumables needed for Maintenance, Repair and Operations (MRO) activities.

BRYAN CHRISTIANSEN, founder and CEO of Limble CMMS.

MRO INVENTORY represents a sizable percentage

of an organization’s annual budget.

Companies are using different strategies

in a bid to optimize MRO inventory. A lean

MRO inventory ensures that companies

eliminate obsolete stocks, retain essential

supplies at safe levels, and reduce MROrelated

expenses.

Production facilities vary in size and

complexity. As a result, the number of consumables

required to keep each facility running

varies. Below are ways for companies

to manage MRO inventory to match the

changes in production technology and complement

proactive maintenance activities.

1) Vendor-Managed Inventory

(VMI)

Through this initiative, the company enlists

the services of a 3rd party partner. The

service provider is granted full authority

to manage inventories at the customer’s

location. The vendor replenishes stocks

of essential products, tools or consumables,

retaining them at the desired level at

any given time. In the VMI approach, the

supplier is at liberty to alter resupply decisions

rather than relying on fulfilment of

customer-initiated orders.

Vendor-Managed Inventory relies on

framework agreements that give vendors

clearer visibility of facility-level stock de-


ASSET MANAGEMENT

mands. By delegating stock-control activities

to an independent service provider, inhouse

employees find ample time to focus

on their core responsibilities.

By gaining full access to the facility’s

inventory, the vendor can extract sufficient

data to forecast demands. This data

reduces reliance on manually prepared

purchase orders, which are subject to repetitive

corrections and reconciliations.

Visibility in the downstream consumables

eliminates the probability of stockouts

while facilitating significant cost

savings. Fewer people will be required

for raising, validating and reconciling

purchase orders, leading to savings in

admin-related costs. In addition, companies

incur reduced costs required for

warehousing and related resources. With

this model, companies are billed based

on the consumed stock rather than the

supplied stock.

VMI initiative has its drawbacks.

Companies tend to build trust around

the approved vendors, making it difficult

INNOVATIVE MRO INVENTORY

MANAGEMENT STRATEGIES

ENSURE THAT COMPANIES

PAY FOR WHATEVER IS USED

AND NOT EVERYTHING THAT IS

SUPPLIED BY THE VENDOR.

to source products from other vendors

leading to a compromise in the quality

and pricing. For sensitive production facilities,

the VMI model is inapplicable as

non-employees would have to get access

to critical inventory data.

2) CMMS and ERP solutions

for managing inventory

Maintenance operations within the production

floors have been improved, thanks

to the robust Computerized Maintenance

Management Systems (CMMS). They can

work in collaboration with Enterprise Resource

Planning (ERP) solutions to ensure

the availability of parts and essential supplies

required to ensure smooth business

operations.

CMMS solutions that come with an

inventory module provide tools for organizations

to manage spare parts inventory.

They help to allocate parts, merging their

usage to work orders and updating future

purchase orders. Mobile CMMS solutions

often contain scanning utilities that enable

technicians to account for every part and

tool used in any MRO process.

CMMS and ERP solutions can hold a

massive amount of data enabling companies

to maintain a detailed record of their

MRO inventory. By serializing essential

supplies, the technicians can search and

identify the location of parts in a warehouse.

They enable any technician to

participate in inventory management by

generating purchase orders whenever necessary.

Maintenance planners can track incoming

inventory and use tracking details

to plan for upcoming maintenance tasks or

reorder supplies. Based on periodic data,

technicians can prioritize vendors based

on the quality of their products, cost, and

lead times.

Using CMMS and ERP to manage

MRO inventory gives in-house employees

full control over stock levels. The system

generates alerts whenever the levels fall

below a prescribed level, providing enough

insights to enhance long-term inventory

planning. They are effective for large-scale

manufacturing facilities with complex

MRO supply requirements.

3) On-site kiosks and vending

machines

Most organizations have centralized

warehousing facilities to keep stock of

essential supplies. Employees engaged in

MRO visit these stores to receive tools,

parts, protective equipment, and production

supplies. Store personnel keep records

of all outgoing products, triggering

reorders from multiple suppliers when

stocks decrease. The whole process is

time-consuming and may impact normal

production. Vending machines and onsite

kiosks can help resolve challenges

associated with centralized storage

units. They can be run by companies or

suppliers, who later bill the organization

based on consumption.

Vending machines are programmed

to dispense required MRO items round

the clock while retaining an accurate record

of all transactions. The machine is

configured for access by specific employees

with stringent limits on quantity and

frequency of use. The restrictions ensure

that inventory is properly utilized, preventing

unnecessary waste. The vending

machines generate alerts when levels fall

below pre-set limits. Data collected by

the machines are utilized in forecasting

future demand.

Vending machines are critical for

production facilities with geographically

dispersed teams. They reduce commuting

costs and have advanced control

tools to prevent wastage. That being said,

any restrictions have to be carefully set

as one doesn’t want to limit access to

tools and parts needed to perform unplanned

emergency maintenance.

Final remarks

Modern manufacturers are focusing on

sustainable production processes, proactive

maintenance, and on reducing operational

costs. Companies must prioritize

the availability of essential supplies for

all production floor teams.

Innovative MRO inventory management

strategies ensure that companies

pay for whatever is used and not everything

that is supplied by the vendor.

Depending on the size of a facility, a company

can choose one or a combination

of the above methods to optimize MRO

inventory.


CERTIFICATION

Maintenance people, get certified!

The 6+1 European maintenance organizations work together as partners in Erasmus+

funded project “Qualification, Validation and Certification of Maintenance Personnel”

to move maintenance qualifications, certifications and validations in Europe forward.

EUROPEAN INDUSTRY needs to work

smarter to increase added value,

profitability, and competitiveness.

Working smarter with a combination

of automation, digitalization and

maintenance allows higher availability

of the production processes. New

technologies like robots, autonomous

vehicles, electromobility, automated

warehouses, conveyor systems -

combined with booming and developing

industries like e-commerce, e-shops and

online groceries with same day delivery,

distribution and public transportation

- constitute a number of challenges for

maintenance and asset management,

a fact we already knew. These trends

accelerated with the COVID19

pandemic, which brought havoc into

labour markets in many countries. All

this resulted in increasing demand

for highly-qualified maintenance

personnel.

Well, new technologies - like augmented

reality, 3D printing, IoT, AI and

machine learning - also create interesting

new opportunities in maintenance,

transforming traditional maintenance

work into a whole new experience for

our personnel. This also contributes to

much higher expertise expected from

the people employed in maintenance

processes today.

These trends in maintenance, however,

are not adequately emphasized in

the vocational education as well as the

academic world. This is one of the most

important issues for the EFNMS. Higher

education is mostly orientated on

development of new technologies and

products and therefore there is a need

for theoretical and practical vocational

training.

The guidelines from the European

Centre for the Development of Vocational

Training, CEDEFOP, focuses on

the validation of non-formal and informal

learning. The total learning results

are of the highest interest for development

of an organization.

Smart and cost-effective production

including maintenance will make

great effects on the competitiveness for

European industries. Therefore, good

examples are a prerequisite for competence

development and new business

opportunities.

Erasmus+ project: Certification and

validation meet new qualification needs

One of the main aims of this Erasmus+

project was to refresh the structure of

maintenance qualifications and update

it to reflect current trends in technologies

and techniques used in industry and

maintenance. The basic objective was to

form a staircase for qualification, validation,

and certification for personnel

within the maintenance area. The outcomes

can be used for recruiting maintenance

personnel for companies and more

importantly, for competence development

and to support lifelong learning.

On top of that, the results of the

work of the 6 international partners

and EFNMS contribute to the European

maintenance certification process

by creating, fitting and finetuning a

number of validation and certification

questions and tasks. The EFNMS certification

for Maintenance Managers, Engineers

and Technicians will be in this way


CERTIFICATION

STRUCTURE OF THE

VALIDATION TEST

Figure 1. EQF levels compared with achieved education and maintenance personnel roles

Table 1. Competence requirements for maintenance professionals of eqf levels 4, 5 and 6.

boosted to reflect current qualification

needs for maintenance personnel in

Europe.

With the above explained ideas in

sight, the priorities of the project were

set to develop:

• A common platform for the

qualification, validation, and

certification of maintenance personnel

with measurable learning

outcomes.

• Detailed qualification requirements

for maintenance personnel

• System for mapping individual

competencies to the qualification

needs.

The project was divided into two consecutive

phases:

• Description of needed qualifications

with measurable learning

outcomes

The European Federation of National

Maintenance Societies (EFNMS) has built

up a database that shape the validation

system. It is based on English questions

which are then translated into local language.

This allows cross-border comparison

of competences. A validation for certificates

in Hungary can be compared to a

certificate in Sweden. Everything is done

under the auspices of the EFNMS. For

EFNMS certificates, the Certification Committee

is responsible for the requirements

and the way to operate the database.

Locally, each country's maintenance association

manages the validation systems.

The international database is divided into

seven subject groups with 26 subgroups.

Validation tests follow this structure.

Every subject has a number of questions.

The number is determined by the importance

of the subject in the professional

role. If you are going to measure a person's

capability, at least 10 questions are

required on the subject and then there

should be at least 30 questions to choose

from.

Each test involves a specific number

of questions from the database. The

number of questions per subject is determined

by the importance of the subject

in the professional role. The system randomly

chooses how the questions come

in the test. This allows test takers to sit

next to each other during the test.

The questions have four to six

answers, where one answer is right. Some

questions contain pictures or diagrams,

where the candidate is required to select

the right answer. When the test is completed,

the evaluation is quick and automated.

The test taker receives a printed

result.

The same subject report and classification

are available for all occupational

levels. Here the EU approach follows

the structure of the European Qualification

Framework training system, where

Maintenance Managers are at EQF level

7, Maintenance Engineers EQF level 6,

Maintenance Technicians EQF level 5 and

Maintenance Mechanics, Maintenance

Electricians and Automation Electricians

at EQF level 4.

For more information about the project

and its outputs, please follow the

project dedicated website http://www.

cemaint.eu. The complete structure of

qualifications for EQF levels 4, 5, 6 and

7 is also available on the website.


CERTIFICATION

• Development of validation

questions for EQF level 6 and

7 based on the structure of

required qualifications.

• There are four categories of

maintenance personnel addressed

in the project:

• EQF level 7: Maintenance

managers,

• EQF level 6: Maintenance supervisors

and engineers,


technician specialists,


mechanics, electrical and automation

electricians,

EQF stands for European Qualification

Framework. The EQF system

concerns eight reference levels

describing the learning outcomes –

what a learner knows, understands

and is able to do. Levels of national

qualifications will be placed at one

of the EQF reference levels.

The EQF levels ranging from

basic (Level 1) to advanced (Level

8) can be roughly assigned to levels

of education (academic, secondary,

primary) or achieved degrees

and diplomas (as shown in the

diagram below). However, what

really defines various EQF levels

is the learning outcomes, not an

education level achieved by an individual.

For personnel in the field of

physical asset management and

maintenance, EQF levels between

3 and 8 are generally expected.

EQF Level 3 is sufficient for Mechanics,

usually the professionals

on the lowest level in the maintenance

organization structure.

Multiskilled Mechanics are professionals

with significant experience

and flexibility to be able to perform

various advanced tasks in the field

of maintenance. For Multiskilled

Mechanics EQF level 5 is considered

adequate. Maintenance Managers

then typically recruit from

professionals on EQF levels 6, 7 or

8, with suitable academic training

combined with sufficient experience

with maintenance processes.

Besides managerial functions,

EQF level 6 also includes teachers

at vocational schools educating

maintenance technicians and mechanics.

EUROPEAN COOPERATION OF SIX COUNTRIES AND ONE

FEDERATION

Six team members - national maintenance societies federated within the EFNMS

- have been involved in this project working hard to introduce a complete system

for qualification, validation and certification for maintenance personnel throughout

the 23 member countries in the EFNMS. All project partners are members

of the EFNMS, European Federation of National Maintenance Societies, and are

responsible for maintenance developments in their own country.

By mixing experts and technical specialists from different countries and backgrounds,

a truly creative and forward-thinking team was formed.

The leading project partner responsible for project management was the Swedish

Maintenance Society, SvUH (Riksorganisationen Svenskt Underhåll). SvUH is

a non-profit organization owned by the industry, energy sector, universities and

maintenance suppliers. More than 140 companies, organisations, universities and

schools are represented as members.

The Slovenian Maintenance Society (DVS) and the University of Maribor are

responsible for training in maintenance and the associated certifications. Thanks

to the great experience of handling several Erasmus+ projects Slovenia was an

important partner in this project.

The Hungarian Maintenance Society, Magyar Ipari Karbantartók Szervezete,

MIKSZ, was founded by professionals involved in industrial management, service

and equipment distributors, and universities.

The Czech Maintenance Society (CSPU, Česká společnost pro údržbu, z.s.) is a

non-profit association for individual professionals and corporate members aiming

to improve industrial and facility maintenance.

The Finnish Maintenance Society, Promaint, is an organization of members

from industrial production and maintenance departments. Promaint has approximately

1 400 members, of which about 200 are companies or communities.

Iceland is a new member in EFNMS and the Icelandic Maintenance Society,

EVS, has a very active role in introducing new maintenance management solutions

in the country. The members cover various industries and include aluminium

smelters, power generating, engineering and IT companies. The project partner of

the Erasmus+ project on behalf of EVS was DMM Lausnir.

Last but not least, The European Federation of National Maintenance Societies,

EFNMS, acted as an umbrella organization and a body of EU political and professional

importance.

The EFNMS is the initiative organization for developing qualification and competence

for maintenance personnel in Europe. The idea for planned competence

development came from the EFNMS Training and Certification Committees.

The EFNMS has a leading role in validation and certification of European maintenance

managers since the year 1993 and European maintenance technician specialists

since the year 2005. Over the years more than 500 maintenance managers

and more than 300 maintenance technician specialists have been certified in

Europe.

The EFNMS, as a leader for 23 national maintenance societies, also plays a

key role in dissemination of this project´s results to establish maintenance as an

important factor for European industry´s continued development and improvement.

THE AUTHORS:

TOMÁŠ HLADÍK, ČSPÚ, Czech Republic

GUÐMUNDUR JÓN BJARNASON, DMM Lausnir, Iceland

MARIA BRUS LUNDELL, SvUH, Sweden

MIKAELA MALMRUD, SvUH, Sweden

INGEMAR ANDREASON, SvUH, Sweden

ILKKA PALSOLA, Promaint, FInland

ISTVÁN PÁLL, MIKSZ, Hungary

ZSOLT NYESTE, MIKSZ, Hungary


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SUPPORTING INSTITUTIONS

HOST

ASSET MANAGEMENT

Integrating information

for evidence-based

decision-making

In maintenance and asset management, decisions are sometimes based on a single

key indicator or on a strong opinion. Evidence-based asset management encourages

a broader consideration of different sources of information and knowledge and

helps in making better decisions. Information often includes written text, and thus

novel language technologies could extend the evidence base.

JESSE TERVO, HELENA KORTELAINEN, PASI VALKOKARI, VTT Technical Research Centre of Finland Ltd.

HELENA AHONEN-MYKA, Lingsoft Language Services Inc.


EVIDENCE-BASED medicine follows the

idea that the best and latest scientific

evidence should be used in patient treatment

decisions. The evidence-based

decision-making logic has also been

applied in engineering. Evidence-based

Asset Management (EBAM) originates

from the University of Toronto (https://

cmore.mie.utoronto.ca/). It could be said

that EBAM considers devices as patients

who are subjects of care – i.e., maintenance

work and other asset-related

tasks. These tasks always involve decision-making

that requires a combination

of information from different sources. In

this way, the decision-maker will be able

to justify their decision and back it up

with several information sources.

EBAM differs from data-based decision-making

as it emphasizes practical

expertise and seeks to take account of

the underlying phenomena behind the

numbers. In addition to hard statistical

data, various soft data sources – such

as tacit information – are considered

in decision-making. Tacit knowledge

is a form of information that is difficult

to exploit, as it is gained through

experience and can manifest itself in

unconscious modes of action. However,

the tacit knowledge of the field maintenance

technicians can be brought out

and put into words e.g., through various

expert procedures such as risk analysis

and reliability-centred maintenance

(RCM). Such analyses are carried out,

for example, in the context of planning

and continuous improvement.

Language technologies open

up information in text format

Valuable information can be obtained

from written text, for instance from

manufacturer manuals, factory diaries,

and maintenance reports. The challenge

with this kind of information, however,

lies in the wide variety of possible expressions

of language. As the information

is often expressed in a different way

than expected, matching of a decisionmaker's

information needs with the

content can be difficult. The content

may include non-standard words, like

incorrectly typed and incomplete words,

or abbreviations. Moreover, words often

have synonyms, or a document may

not be available in the language of the

decision-maker.

All these challenges can be addressed

with language technology tools. Linguistic

analysis can reduce the variety

of word forms by providing base forms

and even correct errors automatically.

Semantic analysis, based on machinereadable

terminologies, can further

enrich text with synonyms and other

alternative terms, which can then be

used in mapping content to information

needs. Finally, language barriers can be

overcome by machine translation.

Information is scattered

Especially for inexperienced workers,

complex and seldom disturbances

and faults, or new equipment and

novel technology pose challenges. It

would be useful to make use of several

sources of information in fault diagnosis

processes. Similarly, many asset

management and resource management

decisions, such as work planning

and investment, should take into account

not only the maintenance costs

of the equipment, but also the reasons

behind the cost increase, equipment

history and design/procurement solutions,

life cycle plans, spare parts availability,

and employee experience.

Accessing all these data sources at the

same time is difficult because there are

many different forms of information.

Images and drawings are in graphical

form, possibly as 3D models. Operating

ASSET MANAGEMENT

and maintenance instructions can be in

paper documents or practical knowledge

and the experience of operators is only

available orally; maintenance data may be

incompletely reported, and various devicespecific

analyses are archived in design

files. The employees must use several information

systems, and log in each system

with a special user ID and password. Collecting,

retrieving, and combining information

from such system silos is difficult and

time consuming. Often important information

remains in the field and is never

recorded anywhere. However, Industry

4.0 – and more specifically digitization and

cloud technologies – not only enable information

to be digitized, but also improve

the accessibility of information at every

decision-making level. Data can be stored

in a central database instead of individual

silos (Figure 1). From the database it can be

accessed by any system and anyone within

the organization.

On top of a central database, we can develop

completely new types of information

systems that support the operating model

of evidence-based asset management. Such

systems should present asset-specific data

and analyses in a way that is visual and can

be quickly embraced and combine it with

expert knowledge. One approach is to create

role-based user interfaces that support

the most common tasks of different user

groups in maintenance and asset management

and thus reduce information overload

by eliminating unnecessary data.

Figure 1. Connectivity to a single central database enables

building new products and interfaces for different user groups.


ASSET MANAGEMENT

Display only what the

user needs

The “SEED - Solid value from digitalization

in forest industry” (www.seedecosystem.fi)

project was launched in the autumn of 2019,

and forest companies opened their doors to

application developers and research. The

SEED ecosystem develops methods and

tools for business-driven asset management

and productivity improvement. The

SEED ecosystem aims to demonstrate,

through rapid experimentations (POC),

solutions to the challenges described by

industry, which can be further developed

through user feedback through the collaboration

of ecosystem actors, possibly even

towards commercial implementation.

The interviews conducted in the SEED

project highlighted challenges in the availability

and use of asset and maintenance

information, as well as in the utilization of

tacit information. As part of the project,

role-based views were developed for field

maintenance technicians and maintenance

managers to support evidence-based fault

diagnoses and equipment replacement

decisions (Tervo, J. 2021. Evidence-based

decision making for maintenance and asset

management. Master’s Thesis. LUT University).

The user interface was designed

based on the wishes and needs gathered

from users, and its development continues

in the SEED project. The POC application

combines information from different information

systems so that the user needs to

spend as little time as possible searching for

information (Figure 2). It is built around a

universal and versatile search function that

helps the users find just the information

they need. Item-specific documentation

and visualized system entries are readily

available, and information can be searched

by item name, location code, or keyword in

description texts.

The problem of data quality

It is obvious that evidence-based decisionmaking

requires high-quality data sources.

However, event logs and descriptions are

short at best, and too often information

may not be passed on at all to maintenance

technicians and subsequent shifts. There

may be several reasons for this, such as

rush, lack of expertise, technical difficulties

with the systems, or insufficient incentives

to make high-quality entries. Proper forms,

data validation and user motivation are all

key to ensuring complete and efficient information

transfer (IEC 60300-3-2:2004).

Users of the systems don’t like writing long

description texts if they don’t see them

bringing tangible benefits in their work.

This problem should be solved with the use

of an information system that incorporates

the system entries and descriptions

into decisions and rewards for quality

entries later as problem-solving speeds up.

On the other hand, the pursuit of higher

quality records may also require a greater

change in the workplace culture and incentives.

Mobile interfaces, on-the-spot dictation,

“speech-to-text”-technology, and

other new technologies may also contribute

to the quality and comprehensiveness

of human recordings in the future.

Future of evidence-based

decision-making

Businesses are becoming increasingly datadriven,

and many kinds of dashboard and

reporting solutions are emerging. Instead

of static dashboards and standard reports,

evidence-based asset management calls for

specialized reports that can be produced ondemand,

according to the information needs

of the time. The data sources behind the

reports need to be reliable, transparent, and

accessible for rapid processing. Numerical

data can be processed to KPIs and visualizations,

and written text can be analysed with

text mining and language technology tools.

This approach already forms a strong basis to

utilizing evidence in maintenance and asset

management, but there is still lots of work to be

done in finding the best possible ways to store

and display different forms of knowledge.

Linguistic

analysis

Figure 2. With the help of language technology, the search function works regardless of

non-standard words, typing errors or abbreviations.


VIBRATION ANALYSIS

THERMAL IMAGING

ULTRASOUND

MEASUREMENT

EYESIGHT – HEARING – SENSITIVITY

WE HAVE IN COMMON

MASTER THE LANGUAGE OF YOUR MACHINERY

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Maintworld Magazine 4/2021

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