Sustainable Plastics - March/April 2024 - 25

additive manufacturing
AM is at the forefront
of sustainable
manufacturing.
Now supported by AI
Much has written about the
sustainability aspects of additive
manufacturing. It addresses the
challenges posed by traditional
methods, in terms of material use, energy
and the production of scrap, amongst
others. Today, it is also one of the areas
of manufacturing in which artifi cial
intelligence has gained a foothold. The
synergy between the two is opening up
untold opportunities. By Karen Laird
A
rtificial intelligence,
it would
seem, is suddenly
everywhere.
And, if the experts are to be
believed, this is just the start.
Broadly speaking, artificial
intelligence - AI - refers to
computer systems that are
capable of performing complex
tasks that traditionally
only humans could
do, such as recognising
speech
and reasoning,
making decisions, or identifying
patterns and solving problems.
As used today, AI comprises a
broad range of technologies that
includes machine learning, deep
learning, and natural language
processing (NLP). In manufacturing,
these technologies can
support and optimise manufacturing
processes, amongst
others, through improved data
analysis and decision-making.
And while manufacturing may
seem to lag somewhat behind
other sectors in adopting the use
of AI, this is due to change. The
global artificial intelligence market
for manufacturing, estimated
to be worth $3.2 billion in 2023,
is projected to reach a value of
USD 20.8 billion by 2028, said
the authors of a recent report
published by Markets and Markets.
This growth will mainly be
driven by the rising need to handle
increasingly large and complex
datasets, emerging IoT and
automation technology.
According to a recent MIT
Technology Review Insights
Report, compiled in collaboration
with marketing intelligence
company Dataiku, manufacturing
companies can use AI to 'streamline
processes and fight downtime,
adopt robotics that promote
safety and speed, allow AI to detect
anomalies quickly through
computer vision, and develop AI
systems to process vast volumes
of data to identify patterns and
predict customer needs'.
Specifically, therefore, there
are five areas where AI can provide
productivity gains in manufacturing,
says the U.S. National
Institute of Standards and Technology.
These can be summed up
as predictive maintenance; predictive
quality; scrap reduction;
increasing yield and throughput;
and demand and inventory forecasting.
One of the manufacturing
technologies currently
benefitting from AI technology is
additive manufacturing. How?
Leveraging AI in AM
There are diff erent ways in
which the use of artificial intelligence
can benefit additive
manufacturing. In the past, one
problem has been the high defect
and scrap rates that have
hampered a widespread adoption
of AM processes in industry,
combined with the fact that
the complex shapes enabled by
AM can be diff icult and expensive
to inspect after production.
Artificial intelligence can enhance
quality assurance and
defect detection through the
use of vision systems to monitor
the production process in real
time. Potential defects can be
detected as they occur - even
when not visible to the naked
eye - reducing the number of
potentially defective products
produced. One eff ort in this
area was, for example, a project
called AMAI - Additive Manufaccontinued
on page 28
March/April 2024
25
Sustainable Plastics - March/April 2024

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