Digital Twins
Bridge Product Design and Manufacturing
Image Source:
Gorodenkoff/Stock.adobe.com
By Dr. Michael Grieves for Mouser Electronics
Published January 30, 2023
The underlying premise in product manufacturing is that tasks are broken into two categories: (1) The most
efficient use of physical resources and (2) physical resource waste. Lean manufacturing has enabled
manufacturers to reduce time within the production system as well as response times from suppliers and
customers. Industry 4.0 has enhanced efficiencies by shortening the time between discovering and fixing problems
in real time. These and related advances have improved efficiencies, but ever-increasing demands for speed,
quality, low cost, and customization are driving manufacturers to find new ways to meet these needs.
Design manufacturability is the general engineering practice of designing products so that they
are efficient to manufacture. The use of digital twins (DTs) is emerging as a solution that bridges the gap
between design and manufacturing, with long-term potential to maximize efficiency and minimize wase.
Gaps between Design and Manufacturing
Even today, with advanced engineering and manufacturing capabilities, it is common for products to be well
designed but ultimately not manufacturable. For example, a design may specify a 2-cm wall between compartments
to meet harsh environmental requirements, but the manufacturer may not be able to manufacture this thickness or
work with the alloy the design specifies. Similarly, a design may specify a single bar with a groove in it to be
made using subtractive manufacturing, but the manufacturer can create the groove only by using a single bar with
two other bars welded on top of the first. The potential manufacturability issues are limitless.
Part of the problem is that design engineering and manufacturing have become siloed phases of the product life
cycle, each with its own requirements and information. Rather than manufacturability being part of engineering
design, the teams and processes are separate and sequential, with designers not getting a full view of the
manufacturing capabilities, limitations, and requirements they need.
Manufacturing design guidelines help bridge this gap, but they are not a panacea. As with other areas of the
product life cycle, guidelines and best practices continue to evolve to meet rapidly-changing customer demands.
Similarly, transparency into existing components and products used in design may not be available or may be
outdated.
Product modeling and simulation tools have advanced design engineering considerably, but they are limited in
terms of design manufacturability, too. Simulations replicate products in their current state, which limits
designers’ ability to test different configurations, components, and materials without building additional
models. Even aggregated simulation data are rooted in testing history, and simulation results may not be
accurate because human input and assumptions are part of the simulation equation.
As a result, product designs may meet functional requirements but ultimately not be manufacturable—or at
least manufacturable in a way that meets cost or delivery demands. And so, an extended back-and-forth between
designers and manufacturers ensues to address manufacturability issues, wasting considerable resources even
before production begins.
Digital Twins: The Bridge to Manufacturability
Over the past several years, the use of Digital Twins (DTs) has increased across a broad swath of industries,
including aerospace, automotive, ship building, oil rigs, and medical devices. The idea of a DT is to be able to
design, test, manufacture, and support products using virtual reality before any work is done in the physical
environment.
DTs are the digital counterparts of physical objects and processes in real-time. The digital twin is a computer
program that simulates how a product or process will perform based on real-world data. Data scientists,
engineers, and IT professionals can run cost-effective simulations to optimize a physical asset's state, predict
its response to changes, or improve operations. Additionally, DTs can be used to identify potential flaws early
in the design phase of an object or process. Artificial Intelligence, the Internet of Things, Industry 4.0, Big
Data, and software analytics can all be utilized to enhance the output of DTs. Product drawings and engineering
specifications have evolved from handmade drawings to computer-assisted designs to model-based systems, and now
to DTs.
Among many efficiency gains that span the entire product life cycle, DTs can bridge the divide between design and
manufacturing like no other solution or combination of solutions can. A DT prototype (DTP) is akin to a product
recipe that includes all the design pieces that would go into a complete product but in digital form, including
the product’s physical attributes, properties, physics, computational flow, operating parameters, test
procedures, bill of materials, and manufacturing bill of process.
The DTP is the most realistic representation of in-development products, and it can be handled and manipulated at
various levels of granularity—at the part, product, or whole-system level. The result is a level of detail
about manufacturability that enables designers to account for the many interdependencies between the two
functional areas. What’s more, a DTP’s algorithmic engine can extrapolate how changes in design,
materials, and components affect manufacturability, eliminating the need for multiple physical prototypes.
DTs can also model manufacturing processes and help guide design decisions that have manufacturing implications.
For instance, DTs can determine whether additive or subtractive processes would be better from cost,
functionality, and durability standpoints. They can further represent the variety of processes used to
manufacture complete products—injection molding, broaching, turning, machining, or any number of others.
For additive manufacturing to become a dominant manufacturing process, DTs are a core requirement.
Finally, DTs not only bridge today’s design-manufacturing gaps: They are also the bridge to future needs.
For instance, today’s customers are demanding product options and personalization as part of core product
offerings, which pose additional manufacturing headaches in terms of manufacturing setup, materials inventory,
time to market, and more. There are no limits to how many DTs can be produced during initial or subsequent
design processes. Further, information gained throughout a product’s life cycle can be used to determine
future customized and personalized products—and their manufacturability.
A Look Ahead
Gaps between engineering design and product manufacturing can result in significant waste even before
manufacturing begins. DTPs have enormous potential to close these gaps and optimize designs for manufacturing
and beyond. Creating DTs is not inexpensive, but the cost of information is still far lower than the cost of
creating multiple physical prototypes or manufacturing by trial and error. In the quest to meet increasing
demands for good, fast, cheap, and customized products, using DTs across the entire product life cycle
will be the only way to meet tomorrow’s manufacturing demands.
Author Bio
Dr. Michael
Grieves splits his time between the business and academic worlds. He is the author of the seminal books on
Product
Lifecycle Management (PLM): “Product Lifecycle Management: Driving the Next Generation of Lean Thinking”
(McGraw-Hill, 2006) and Virtually Perfect: Driving Innovative and Lean Products through Product Lifecycle
Management” (SCP, 2010).
Dr. Grieves is an acknowledge world expert in PLM and lectures world-wide on engineering, manufacturing, and PLM
in
both industry and academia conferences. In addition to his books, Dr. Grieves has numerous publications and
articles. Dr. Grieves consults with a number of leading international manufacturers and governmental
organizations
such as NASA.
Dr. Grieves has been a Co-Director of the Purdue PLM Center of Excellence, where he still participates, and
served
as a Visiting Professor at the Purdue University College of Technology. Dr. Grieves has also been affiliated
with
the Eller School of Business MIS Department at the University of Arizona, where he was designated Director –
Industry Research for the MIS Department and Director, Information Technology Industry Research Center (ITIRC)
at
the University of Arizona. He served on the advisory board for the MIS department.
Dr. Grieves is Chairman Emeritus of Oakland University’s School of Business Board of Visitors. He has taught
in the United States, China, and Europe at the university senior undergraduate, and graduate school levels and
has
authored and taught executive education courses. Dr Grieves is a Professor at CIMBA University, Asolo, Italy
with an
appointment at the University of Iowa. He also has an appointment as Research Professor at the Florida Institute
of
Technology.
Dr. Grieves is a founder and Chairman of Interactive Frontiers, Inc. the world leader in golf and sport
instructional software, Dr. Grieves has over thirty years experience in the computer and data communications
industry. He has been a senior executive at both Fortune 1000 companies and entrepreneurial organizations during
his
career. He founded and took public a $100 million systems integration company and subsequently served as its
audit
and compensation committee chair. Dr. Grieves has substantial board experience, including serving on the board
of
public companies in both China and Japan.
Dr. Grieves has a BSCE from Michigan State University and an MBA from Oakland University. He received his
doctorate
from the Case Western Reserve University Weatherhead School of Management.
