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Integrated Design of Multiscale, Multifunctional Materials and
Products is the first of its type to consider not only design of
materials, but concurrent design of materials and products. In
other words, materials are not just selected on the basis of
properties, but the composition and/or microstructure iw designed
to satisfy specific ranged sets of performance requirements. This
book presents the motivation for pursuing concurrent design of
materials and products, thoroughly discussing the details of
multiscale modeling and multilevel robust design and provides
details of the design methods/strategies along with selected
examples of designing material attributes for specified system
performance. It is intended as a monograph to serve as a
foundational reference for instructors of courses at the senior and
introductory graduate level in departments of materials science and
engineering, mechanical engineering, aerospace engineering and
civil engineering who are interested in next generation
systems-based design of materials.
Key Features:
* First of its kind to consider not only design of materials, but
concurrent design of materials and products.
* Treatment of uncertainty via robust design of materials
* Integrates the "materials by design approach" of Olson/Ques Tek
LLC with the "materials selection" approach of Ashby/Granta
* Distinquishes the processes of concurrent design of materials and
products as an overall systems design problem from the field of
multiscale modeling
* Systematic mathematical algorithms and methods are introduced for
robust design of materials, rather than ad hoc heuristics--it is
oriented towards a true systems approach to design of materials and
products
This book explores systems-based, co-design, introducing a
"Decision-Based, Co-Design" (DBCD) approach for the co-design of
materials, products, and processes. In recent years there have been
significant advances in modeling and simulation of material
behavior, from the smallest atomic scale to the macro scale.
However, the uncertainties associated with these approaches and
models across different scales need to be addressed to enable
decision-making resulting in designs that are robust, that is,
relatively insensitive to uncertainties. An approach that
facilitates co-design is needed across material, product design and
manufacturing processes. This book describes a cloud-based platform
to support decisions in the design of engineered systems
(CB-PDSIDES), which feature an architecture that promotes co-design
through the servitization of decision-making, knowledge capture and
use templates that allow previous solutions to be reused. Placing
the platform in the cloud aids mass collaboration and open
innovation. A valuable reference resource reference on all areas
related to the design of materials, products and processes, the
book appeals to material scientists, design engineers and all those
involved in the emerging interdisciplinary field of integrated
computational materials engineering (ICME).
In this monograph, the authors demonstrate how the integration of
adaptability, operability, and re-configurability in the design of
complex systems is indispensable for the further digitization of
engineering systems in smart manufacturing. Globalization of the
customer base has resulted in distributed and networked
manufacturing systems. However, current design methods are not
suitable to address variations in product design, changes in
production scale, or variations in product quality necessitated by
dynamic changes in the market. Adaptability, operability, and
re-configurability are key characteristics that are necessary to
address the limitations of the current methods used to design
networked manufacturing systems. In recent years, the digital
transformation driving Industry 4.0 has had an enormous impact on
globally distributed manufacturing. Digitalisation, the integration
of digital technology into networked engineered systems, is
increasingly being adopted to respond to changes in the market.
This is achieved by means of (a) the concurrent design of adaptable
systems, (b) addressing flexibility in design parameters, (c)
conducting an operability analysis, and (d) employing a
reconfiguration strategy to address faults and variances in product
quality and re-establish connectivity among the elements in the
system. The design of manufacturing systems in the age of Industry
4.0 is addressed in this monograph. The authors introduce the
concept of a 'smart platform' and a computational framework for the
digitalization of networked manufacturing systems. They also
suggest how the framework and techniques in this monograph are
applicable beyond the manufacturing domain for architecting
networked engineered systems in other industries such as chemical
processes and health care, that are being transformed through the
adoption of the Industry 4.0 construct.
"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.
A fail-safe supply network is designed to mitigate the impact of
variations and disruptions on people and corporations. This is
achieved by (1) developing a network structure to mitigate the
impact of disruptions that distort the network structure and (2)
planning flow through the network to neutralize the effects of
variations. In this monograph, we propose a framework, develop
mathematical models and provide examples of fail-safe supply
network design. We show that, contrary to current thinking as
embodied in the supply network literature, disruption management
decisions made at the strategic network design level are not
independent from variation management decisions made at the
operational level. Accordingly, we suggest that it is beneficial to
manage disruptions and variations concurrently in supply networks.
This is achieved by architecting fail-safe supply networks, which
are characterized by the following elements: reliability,
robustness, flexibility, structural controllability, and
resilience. Organizations can use the framework presented in this
monograph to manage variations and disruptions. Managers can select
the best operational management strategies for their supply
networks considering variations in supply and demand, and identify
the best network restoration strategies including facility
fortification, backup inventory, flexible production capacity,
flexible inventory, and transportation route reconfiguration. The
framework is generalizable to other complex engineered networks.
This book explores systems-based, co-design, introducing a
"Decision-Based, Co-Design" (DBCD) approach for the co-design of
materials, products, and processes. In recent years there have been
significant advances in modeling and simulation of material
behavior, from the smallest atomic scale to the macro scale.
However, the uncertainties associated with these approaches and
models across different scales need to be addressed to enable
decision-making resulting in designs that are robust, that is,
relatively insensitive to uncertainties. An approach that
facilitates co-design is needed across material, product design and
manufacturing processes. This book describes a cloud-based platform
to support decisions in the design of engineered systems
(CB-PDSIDES), which feature an architecture that promotes co-design
through the servitization of decision-making, knowledge capture and
use templates that allow previous solutions to be reused. Placing
the platform in the cloud aids mass collaboration and open
innovation. A valuable reference resource reference on all areas
related to the design of materials, products and processes, the
book appeals to material scientists, design engineers and all those
involved in the emerging interdisciplinary field of integrated
computational materials engineering (ICME).
A fail-safe supply network is designed to mitigate the impact of
variations and disruptions on people and corporations. This is
achieved by (1) developing a network structure to mitigate the
impact of disruptions that distort the network structure and (2)
planning flow through the network to neutralize the effects of
variations. In this monograph, we propose a framework, develop
mathematical models and provide examples of fail-safe supply
network design. We show that, contrary to current thinking as
embodied in the supply network literature, disruption management
decisions made at the strategic network design level are not
independent from variation management decisions made at the
operational level. Accordingly, we suggest that it is beneficial to
manage disruptions and variations concurrently in supply networks.
This is achieved by architecting fail-safe supply networks, which
are characterized by the following elements: reliability,
robustness, flexibility, structural controllability, and
resilience. Organizations can use the framework presented in this
monograph to manage variations and disruptions. Managers can select
the best operational management strategies for their supply
networks considering variations in supply and demand, and identify
the best network restoration strategies including facility
fortification, backup inventory, flexible production capacity,
flexible inventory, and transportation route reconfiguration. The
framework is generalizable to other complex engineered networks.
"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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