Medical Design Briefs - June 2022 - 28

ering how a product's raw materials are extracted;
the quantity of resources required;
the materials and energy used during manufacturing,
packaging, and distribution; the
impacts of the product's functional use; and
the waste and pollution created at the end of
the product's life.
By considering every step of the product's
life cycle, an LCA leaves no stone unturned.
Once an LCA has been completed, manufacturers
can identify significant sustainability
flaws in a product, evaluate the sustainability
of products still in development, and design
new, more sustainable solutions.
Machine connectivity and sensor-embedded tools make digital machining accessible to manufacturers.
(Credit: Sandvik Coromant)
predicting upcoming maintenance needs. By making several
smaller processes more energy efficient, data can be used to
control - and reduce - overall energy consumption.
Energy inefficiencies can be identified in real time, giving
manufacturers the opportunity to identify potential causes and
solutions. For example, when looking at energy consumption
data, manufacturers may discover one piece of equipment that
uses significantly more energy than others. Using this information,
manufacturers can then identify the cause of increased
power consumption and implement improvements to streamline
machine efficiency and reduce energy waste.
Continuously analyzing data in real time can also help reduce
machine maintenance. Data analytics can identify upcoming
problems before they happen. If a machine experiences a
problem or a change in performance, it may start to produce
parts that are not up to standard, which would ultimately end
up discarded as waste. Data on machine performance can help
to identify minute changes in machine behavior as soon as they
occur so that engineers can carry out predictive maintenance
before multiple defective products are produced.
The CoroPlus®
Packaging assessment is also necessary because
the resources required to produce -
and later dispose of - packaging raises many
environmental concerns. The problem is
shared globally. In the UK, for example, nearly
44 million tons of packaging waste are produced
annually by commerce and industry,
and 28 percent of total municipal solid waste
in the United States is attributed to packaging.
Sandvik Coromant recognizes the problem with packaging,
even for products like cutting tools, and recently launched its
package selector application (PSA). The PSA uses data to analyze
a 3D CAD model of the company's product to be packaged, identifies
its critical points, and uses an AI algorithm to recommend
the smallest amount of packaging possible. This process improves
the LCA of the company's tools by reducing packaging waste produced
for tool distribution to manufacturers.
n Circularity Through Transparency
Data can also be used to facilitate a closed-loop manufacturing
chain, in which waste from one process is used as a resource
in another. Operating in this way promotes a circular
manufacturing economy, minimizing waste as much as possible
through continuous reuse.
suite of products data-driven machining offered
by Sandvik Coromant, for example, can help manufacturing
organizations improve efficiency, reduce waste, and increase
productivity. The CoroPlus Process Control monitors
machines in real time and triggers actions in accordance with
programmed protocols. If specific, predetermined issues occur,
the software automatically triggers a correctional action,
such as stopping the machine or replacing a worn cutting tool.
Conducting maintenance in this way can improve operational
efficiency by as much as 89 percent and reduces waste by allowing
manufacturers to assess data, monitor machine performance,
and identify faults before they occur.
n Considering the Whole Life Cycle
Data produced by conducting life-cycle assessments (LCA)
can also help reduce waste. An LCA outlines the environmental
impact of a product at every stage of its life span by consid28
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Using data from an LCA, along with machine data, manufacturers
can improve the efficiency and circularity of their products
through constant product and process improvements. Efficiently
implementing a production system of this kind requires
a robust data strategy. To create a strong data architecture,
manufacturers need a digital infrastructure that can easily synchronize
operations, potentially across several locations, and
identify opportunities to utilize waste that would otherwise be
in silos. Machine connectivity and sensor-embedded tools
make digital machining accessible to manufacturers, equipping
them with the close to cutting-edge data needed to make
use of their waste resources for more sustainable operations.
Data can seem overwhelming at first - with such vast quantities
available, it can be hard to determine what to do with it. The
correct, tailored strategy, however, can prove to be effective in
reducing industrial waste by improving efficiency; enabling predictive
maintenance; inspiring innovative product and packaging
development; and streamlining resource management
across machines, facilities, and even entire companies.
This article was written by V. R. Vijay Anand, Head of Digital Machining,
Sandvik Coromant, Sandviken, Sweden. For more information,
visit http://info.hotims.com/82322-343.
www.medicaldesignbriefs.com
ToC
5/25/22 4:10 PM
Medical Design Briefs, June 2022
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Medical Design Briefs - June 2022

Table of Contents for the Digital Edition of Medical Design Briefs - June 2022

Medical Design Briefs - June 2022 - Intro
Medical Design Briefs - June 2022 - Cov4
Medical Design Briefs - June 2022 - Cov1a
Medical Design Briefs - June 2022 - Cov1b
Medical Design Briefs - June 2022 - Cov1
Medical Design Briefs - June 2022 - Cov2
Medical Design Briefs - June 2022 - 1
Medical Design Briefs - June 2022 - 2
Medical Design Briefs - June 2022 - 3
Medical Design Briefs - June 2022 - 4
Medical Design Briefs - June 2022 - 5
Medical Design Briefs - June 2022 - 6
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Medical Design Briefs - June 2022 - Cov3
Medical Design Briefs - June 2022 - Cov4a
https://www.nxtbook.com/smg/techbriefs/22MDB09
https://www.nxtbook.com/smg/techbriefs/22MDB08
https://www.nxtbook.com/smg/techbriefs/22MDB07
https://www.nxtbook.com/smg/techbriefs/22MDB06
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https://www.nxtbook.com/smg/techbriefs/21MDB10
https://www.nxtbook.com/smg/techbriefs/21MDB09
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