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"Design Engineering for Industry 4.0 (DE4.0) represents the
'human-cyber-physical view of the systems realization ecosystem
“that is necessary to accommodate the drivers of Industry 4.0
(IoX) and provide an open ecosystem for the realization of complex
systems. Seamless integration of digital threads and digital twins
throughout the product design, the development and fulfillment
lifecycle; the ability to accommodate diverse and rapidly changing
technologies; and the mechanisms to facilitate the creation of new
opportunities for the design of products, processes, services, and
systems are some of the desired characteristics of DE4.0." Jiao,
R., Commuri, S. Panchal, J., Milisavljevic-Syed, J, Allen, J.K.,
Mistree, F. and Schaefer, D., "Design Engineering in the Age of
Industry 4.0," ASME Journal of Mechanical Design, 143(7), 070801,
25 pages. In keeping with the Design Engineering 4.0 construct the
authors describe architecting a computer platform to support human
designers make decisions associated with the realization of complex
engineered systems. The platform is designed to facilitate
end-to-end digital integration, customization and personalization,
agile collaboration networks, open innovation, co-creation and
crowdsourcing, product servitization and anything-as-a-service.
Recognizing that simulation models are abstractions of reality the
authors opt for a satisficing strategy instead of an optimization
strategy. They include fundamentals and then describe tools for
architecting a knowledge-based platforms for decision support.
Challenges associated with developing a computational
platform for decision support for the realization of complex
engineered systems in the context of Design Engineering 4.0 are
identified. Constructs for formulating design decisions (e.g.,
selection, compromise, and coupled decisions), knowledge modelling
schemes (e.g., ontologies and modular templates), diagrams for
designing decision workflows (e.g., the PEI-X diagram), and some
analytical methods for robust design under uncertainty are
presented. The authors describe integrating the knowledge-based
platform to architect a cloud-based platform for decision support
promoting co-design and cloud-based design communication essential
for mass collaboration and open innovation for Design Engineering
4.0. This book is a valuable resource for researchers, design
engineers, and others working on pushing the boundary of digitized
manufacturing to include Design Engineering 4.0 principles in
designing products, processes, and services.
"Design Engineering for Industry 4.0 (DE4.0) represents the
'human-cyber-physical view of the systems realization ecosystem
"that is necessary to accommodate the drivers of Industry 4.0 (IoX)
and provide an open ecosystem for the realization of complex
systems. Seamless integration of digital threads and digital twins
throughout the product design, the development and fulfillment
lifecycle; the ability to accommodate diverse and rapidly changing
technologies; and the mechanisms to facilitate the creation of new
opportunities for the design of products, processes, services, and
systems are some of the desired characteristics of DE4.0." Jiao,
R., Commuri, S. Panchal, J., Milisavljevic-Syed, J, Allen, J.K.,
Mistree, F. and Schaefer, D., "Design Engineering in the Age of
Industry 4.0," ASME Journal of Mechanical Design, 143(7), 070801,
25 pages. In keeping with the Design Engineering 4.0 construct the
authors describe architecting a computer platform to support human
designers make decisions associated with the realization of complex
engineered systems. The platform is designed to facilitate
end-to-end digital integration, customization and personalization,
agile collaboration networks, open innovation, co-creation and
crowdsourcing, product servitization and anything-as-a-service.
Recognizing that simulation models are abstractions of reality the
authors opt for a satisficing strategy instead of an optimization
strategy. They include fundamentals and then describe tools for
architecting a knowledge-based platforms for decision support.
Challenges associated with developing a computational platform for
decision support for the realization of complex engineered systems
in the context of Design Engineering 4.0 are identified. Constructs
for formulating design decisions (e.g., selection, compromise, and
coupled decisions), knowledge modelling schemes (e.g., ontologies
and modular templates), diagrams for designing decision workflows
(e.g., the PEI-X diagram), and some analytical methods for robust
design under uncertainty are presented. The authors describe
integrating the knowledge-based platform to architect a cloud-based
platform for decision support promoting co-design and cloud-based
design communication essential for mass collaboration and open
innovation for Design Engineering 4.0. This book is a valuable
resource for researchers, design engineers, and others working on
pushing the boundary of digitized manufacturing to include Design
Engineering 4.0 principles in designing products, processes, and
services.
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