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Maintworld 1/2019

Condition Monitoring in the Age of the of the IIoT // Digital line of sight // Harnessing change for a successful business // Energy savings 4.0

Condition Monitoring in the Age of the of the IIoT // Digital line of sight // Harnessing change for a successful business // Energy savings 4.0

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PARTNER ARTICLE<br />

However today, we are still at the beginning<br />

of this new era of Industry 4.0<br />

and some people are convinced that future<br />

history books will name the world<br />

wide web (or the “Internet” in short) as<br />

the key trigger for these massive changes.<br />

And of course, this fourth industrial<br />

revolution will change the way in which<br />

we work and live together as it always<br />

did in the eras before. There is hope and<br />

good reason to assume that it will not<br />

only be for the worse but for the better<br />

– as seen in the past summary of historical<br />

industrial revolutions. But what<br />

challenges and impacts can be expected<br />

for maintenance employees in almost<br />

daily changing working environments?<br />

The Industrial Internet of<br />

Things – challenge or solution?<br />

Predictions are hard to make but already<br />

today there are sophisticated challenges<br />

that need to be resolved, especially when<br />

considering the IIoT environment. The<br />

more Things mankind connects to each<br />

other – starting from computers through<br />

mobiles up to industry and everyday devices<br />

– the more data are produced and<br />

collected. These require not only huge<br />

amounts of storage space, but even intelligent<br />

management. On an industrial level<br />

those connected Things are the machines<br />

and assets, their control systems and the<br />

net of sensors that measure and finally<br />

steer the variables of all those machines.<br />

Let’s pick a typical example of a<br />

temperature sensor on a motor that<br />

transmits the information into a Programmable<br />

Logic Controller (PLC) or<br />

database. Ok, this alone is not sufficient<br />

to talk about a new paradigm change.<br />

But let’s scale this onto a higher level.<br />

There is not just one sensor in an industrial<br />

plant or mill, there are thousands<br />

of different sensors that transmit their<br />

data into a storage mine that is filled<br />

with other plant’s data, too. A data lake<br />

– rather a sea – is created. Intelligent<br />

algorithms will mine through this data<br />

lake in order to find problems, but also<br />

better operating parameters for plants<br />

worldwide. Though innovative solutions<br />

for the maintenance world have<br />

been available for some time, new questions<br />

arise due to this technology: How<br />

to manage, store and secure this huge<br />

amount of data? How can this data be<br />

prepared for algorithms? Who is responsible<br />

for the results of self-learning<br />

algorithms that work with all those data,<br />

especially when it comes to machine<br />

damage or even people’s death due to<br />

wrong decisions being made?<br />

What’s next?<br />

The answers to all the questions above<br />

certainly will not come as early as tomorrow<br />

but maybe with the next industrial<br />

revolution since not just technical, but<br />

even social, ethical and juristic questions<br />

need to be answered. But in any<br />

case, what we can learn from the history<br />

above, is that the maintenance sector is<br />

changing faster and with greater impact<br />

than ever before.<br />

Employees in the maintenance sector<br />

for now and in the future have to be<br />

able to read, understand and interpret<br />

algorithms and their results. Their profession<br />

is rather turning from a skilled<br />

craftsman to a “data lake manager”.<br />

Wherever the journey of maintenance<br />

will go to in the future, one thing<br />

certainly cannot be captured by any<br />

machine or algorithm: Decision making<br />

based on real world experience. This is<br />

and certainly always will be a humanonly<br />

skill. But self-learning algorithms<br />

and their results (based on giga- and<br />

terabytes of measurement data) are going<br />

to support the professional maintenance<br />

employee of the future to decide<br />

how to solve maintenance issues.<br />

PRUFTECHNIK has been delivering<br />

and optimizing industrial solutions<br />

for maintenance personnel throughout<br />

more than 40 years and always adapted<br />

to changes within the industrial environment.<br />

Its laser shaft alignment<br />

systems are using the latest microelectromechanical<br />

systems (MEMS)<br />

technology in the sensors with in-built<br />

intelligence.<br />

PRUFTECHNIK handheld and<br />

online Condition Monitoring systems<br />

keep the productivity of plants high in<br />

actually any industry sector around the<br />

globe. PRUFTECHNIK implements<br />

the latest technology always with the<br />

goal to create ultimate benefit to their<br />

customers. The German maintenance<br />

specialist therefore is excited and curious,<br />

too, what the future will bring and<br />

will keep on supporting maintenance<br />

personnel in their daily life with highest<br />

quality and latest technology precision<br />

tools and monitoring solutions.<br />

www.pruftechnik.com<br />

Within the fourth<br />

industrial revolution<br />

maintenance practices<br />

will change their shape,<br />

too, and will become<br />

more data-driven and<br />

automated. Mining<br />

through the big data<br />

lake of a plant promises<br />

to drive productivity to<br />

higher levels.<br />

14 maintworld 1/<strong>2019</strong>

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