Medical Design Briefs - June 2022 - 27

How Data Can Help Solve Manufacturing's Waste Problem
I
n reshaping the world toward a new, post-pandemic normal,
the industry must leverage digital transformation at an accelerated
pace. This shift is already happening - according to
IBM, 67 percent of manufacturers have accelerated digital projects
since the start of the COVID-19 pandemic. While improved
operational efficiency is typically the reason for these changes,
the industry should capitalize on the convergence of Industry
4.0 and environmental, social, and governance (ESG) goals to
improve their sustainability credentials. Analyzing and acting
on related data, however, could hold the key to reducing manufacturing's
waste problem.
Despite the increased incorporation of digital tools, only 59
percent of manufacturers cite improved sustainability as a reason
to digitalize their operations. Digitalization's potential extends
far beyond its perceived applications, however. Data collated
by the Association of Swedish Engineering Industries
(Teknikföretagen) emphasizes the importance of digital tools
in achieving sustainability goals. Leveraging IT technology in
other sectors, such as manufacturing, has the potential to reduce
total CO2
emissions by as much as 20 percent.
Increasing digital tool use is vital to aligning manufacturing
activity with the Paris Agreement, increasing resource efficiency
and reducing waste. Globally, industrial waste generation is
almost 18 times greater than municipal solid waste, according
to the most recent data from the World Bank.
All manufacturing facilities generate waste, but a lot of that
waste could be prevented. Overproduction and defect output
are two of the most common contributors to waste generation.
Facilities running on legacy technologies that lack the
sophistication to deal with the challenges of modern-day manufacturing
are far too common. Machine shops that rely on
older (legacy) machines and systems that aren't, or haven't
yet been, upgraded to today's Industry 4.0 standards. Such
shops are missing out on the potential of digitalization to
tackle issues like overproduction and defect output. However,
this doesn't mean that manufacturers should accept huge
waste generation as an unavoidable consequence of production.
Industrial waste must be reduced, and data can play a key
role in achieving this goal - if manufacturers know what to do
with the data.
n Improving Operational Efficiency
Every manufacturing facility, regardless of its size, complexity,
or age, generates a significant amount of data every day. In
a smart factory, this data can include everything from equipment
performance tracking to product quality assessment and
is collected via sensors installed on each machine. Starting
small, with each individual machine's data, is a good starting
point to reduce waste on a large scale.
Small changes to individual processes can collectively have a
huge impact on operational efficiency. Analyzing data from
machinery on the shop floor, for example, can enable manufacturers
to monitor and improve processes based on the data.
Individual machine processes that significantly contribute to
overall energy use can be optimized by detecting inefficient
processes, streamlining production and logistics planning, and
Starting small, with each individual machine's data, is the first method of a good starting point to reducing waste on a large scale. (Credit: Sandvik Coromant)
Medical Design Briefs, June 2022
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Medical Design Briefs - June 2022

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