Green Economy Journal Issue 60

MANUFACTURING
Smart
Manufacturing’s
Great
Convergence:
Most manufacturers’ concerns revolve around figuring out how to improve the supply of raw
materials and meet demand while controlling both costs and quality. For many manufacturers,
the solutions to these issues have emerged in the application of the technologies known
collectively as Industry 4.0.
BY KEARNEY CONSULTING*
INDUSTRY 4.0
The costs associated with adopting robots continue to decline,
making them more accessible even for small and medium-size
businesses due to rising labour costs. The unit cost is expected to
drop 50% to 60% by 2025. A decrease in material and technology
costs, improvements in IIoT and cloud infrastructure, as well as the
ease of connecting robots to existing systems all allow for easier
and cheaper transitions for manufacturers.
The introduction of co-bots has made advanced robotics more
accessible to enterprises of all sizes and significantly reduced the
required upfront investment, making it the perfect choice for mass
adoption in the manufacturing sector.
Advanced robots, especially for material handling, are undergoing
a revolution along with advances in autonomous driving and battery
life with automatic guided vehicles. This trend is coupled with pickand-place
robots for simple operations on assembly lines.
Wearables
Wide adoption of wearable technologies across industries has
intensified competition and driven innovation and investments
across the ecosystem. The global industrial wearables market is
expected to reach $8.4-billion by 2027, up from $3.8-billion in 2019.
Cost-effective and more sophisticated AR/VR headsets from
original equipment manufacturers such as Sony, Google, Microsoft,
Apple, Facebook and HTC have emerged in both the consumer and
industrial spaces. AR and VR software developers now implement ML
and AI in apps for wearables, allowing systems to see and analyse
anything in their fields of vision.
The Industrial Internet of Things
The IIoT uses connected assets to provide visibility and transparency
in factory operations. A typical smart factory IIoT ecosystem includes
sensors, connected devices, networking and connectivity solutions,
edge and cloud infrastructures, IIoT platforms and gateways and
analytics applications. This ecosystem is rapidly advancing and
becoming more sophisticated, resulting in the rapid deployment of
MANUFACTURING
new IIoT applications and services to improve quality and productivity.
According to Gartner, 50% of industrial enterprises will use IIoT
platforms by 2025 to improve factory operations, up from 10% in
2020. The global IIoT market stood at $216.1-billion in 2020 and is
expected to reach $1.1-trillion by 2028.
The emergence of 5G-enhanced IoT applications is helping
manufacturers realise their vision of Industry 4.0 more than any
other development.
Artificial intelligence
AI is still a nascent technology in manufacturing, but recent
breakthroughs in ML techniques (deep learning) have sparked
high expectations for future applications. Cognitive modes such as
natural language processing, computer vision, pattern recognition
and reasoning with ML techniques are widening the array of potential
applications for manufacturers.
This growth is being driven by the digitisation of data, rapid
growth in IIoT data sources, hardware developments and the
democratisation of AI and data, among others. Relative to other
Industry 4.0 technologies, the hardware cost for AI is small, and
most of the investment is spent on developing and rolling out the
software solution. Consulting, maintenance and training services
do incur additional costs.
Advanced analytics and ML create tremendous value in applications
where yield and process waste is a big issue, especially in process
industries where even a percentage point of improvement is in the
millions. While the technology continues to advance, many firms
struggle to extract the full value.
THREE CHALLENGES
The shortage economy
Many global manufacturers and distributors have been unable to
achieve their desired outputs because of a shortage of raw materials
or other components, a lack of resources to run their operations or
limitations to internal capacity due to asset or space constraints.
These challenges must be addressed through better planning,
installing more long-term capacity and improving the allocation of
resources. However, when manufacturers look at what they can do
immediately, they should seek to answer one key question: How do we
make better use of the resources we do have? This requires enabling
DEVELOPMENTS IN INDUSTRY 4.0
3D printing
3D printing (3DP) is getting faster and stock material prices are falling.
Even though 3DP’s contribution to manufacturing is minuscule (about
0.1%) compared with traditional manufacturing methods, the growing
number of applications and demand for custom manufacturing will
continue to expand the market. One major driver of the increasing
speeds for prototyping in a production environment is lasers, which
enable faster sintering or bonding of the build.
The emergence of 5G-enhanced IoT
applications is helping manufacturers
realise their vision of Industry 4.0.
3D printers will continue to evolve, using artificial intelligence
(AI) and machine learning (ML) to improve build rates and quality
while continuing to push the break-even point with traditional
processes. The focus will be on producing cost-effective metal
powders to become even more cost-competitive.
Advanced robotics
The adoption of advanced robotics in manufacturing has steadily
accelerated, with the pandemic’s unique challenges adding a catalyst
for the transformation. The global average industrial robot density
in manufacturing reached an all-time high of 126 robots per 10 000
employees in 2021, compared with 66 robots per 10 000 workers in
2015. Advancements in technology platforms such as the Industrial
Internet of Things (IIoT) and connected systems are upgrading
the functionality of robots and paving the way for collaborative
robots (co-bots).
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