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Center for e-Design (eDesign)

Brigham Young University

Iowa State University

Oregon State University

Penn State University

University at Buffalo-SUNY

University of Massachusetts Amherst

Wayne State University

Last Reviewed: 01/13/2020

The Center for e-Design creates and develops new design paradigms, electronic design tools, and design processes integrating information throughout the full product lifecycle that assist in generating high quality products and systems at a reduced cost while also reducing the time associated with designing complex engineering products and systems.

Center Mission and Rationale

The mission of the Center for e-Design is to serve as a nationally recognized center of excellence in design where innovation and creativity are integrated with fundamental principles of science, mathematics, and engineering in the development, testing, and implementation of new methods and technologies for the design of products and systems focused on faster time-to-market, better product quality, and significantly reduced costs. 

The Center for e-Design focuses its efforts in three major areas to deliver value to its industry/government partners:

  1. Fundamental Research focuses on creating methods, tools, and technologies to address industry relevant needs in e-tools-enabled product development and realization including: integration of design information and knowledge, enhancing information infrastructure, enhancing design innovation through collaborative design and manufacturing, and incorporating intelligence into the product development lifecycle.
  2. Research Testbed focuses on integration of interdisciplinary research activities to validate developed tools, methods, and technologies.
  3. Engineering Education and Technology Transfers, which focus on educating a new generation of engineers and scientists proficient in e-design and rapidly transferring results into usable applications for industry and government.

Research program

Design Education

The objective of the Design Education research thrust is to prepare and support students and practitioners to take on current and future challenges in engineering design. Research in this area focuses on improving design pedagogy through training on new design tools and method, integrating design thinking into engineering design processes, and providing training on and understanding decision making under uncertainty in local, distant, and distributed learning environments. The ultimate goal of this thrust is to prepare individuals for careers in intelligent product and system design, development, and realization.

Industrial Relevance

This thrust is critical for industry as the premise is to transform the way engineers think, act and analyze as they engineer new and/or improved products, systems and processes. A state-of-the-art education that prepares and trains future and current engineers in design thinking is imperative to the competitiveness of the nation. With such training, engineers will be better prepared to: tolerate ambiguity; embrace and demonstrate expertise in systems thinking and systems design; handle uncertainty; make decisions; work as part of a team in a social process; and think and communicate in varied modes and models of design.  This new knowledge will   better prepare engineers to contribute the solutions required to solve industry’s complex, interdependent design and product realization challenges.


·       Educational courses, modules, and workshops on a wide variety of topics associated with design education (design thinking).  These can be targeted to K-12, colleges/universities, industry, and/or government, or can be widely applicable.

·       Example design education research and development topics:

o   Team-based learning

o   Project-based learning

o   Conceptual design methods and tools

o   Creativity and innovation

o   Distributed collaboration

o   Communication skills

o   Interdisciplinary or multidisciplinary collaboration

o   Systems thinking

o   Decision making methods and tools

o   Complexity and uncertainty

o   Immersive environments

o   Gaming and learning



The objective is to develop new methods and tools that more closely integrate engineering design with engineering analysis, manufacturing, supply chain, maintenance, and sustainability, and the end user.  Research in this area focuses on integration of information, knowledge, tools, and models across the product lifecycle to enable innovative designs, decreased time to market, and reduced total lifecycle costs.

Industrial relevance

Disrupting the traditional siloes of design, manufacturing, maintenance, and lifecycle processes with emerging methods (e.g., digital thread).  Developments in these areas will lead to increased innovation in designs and manufacturing processes, decreased time to market for new and innovative products, and reduced total lifecycle costs for the developed products.


·       Design for X-abilities. For example, design for manufacture-ability (legacy and developing processes, such as subtractive, additive, hybrid manufacturing, assembly), use-ability (usability), recycle-ability, automation, maintain-ability, sustain-ability, and end of life. 

·       Tools, processes, methodologies, and procedures that feed the data and information along the product digital thread forward and backward to provide insight to each function along the chain.

·       Interoperability tools and methods for remote and heterogeneous systems.

·       Engineered tools with scalability, extensibility, and portability.

·       Collaboration among all stakeholders throughout the life cycle.

Information Infrastructure

The objective is to explore and develop new software, hardware, information modeling approaches (e.g., ontologies), and secure data handling processes and storage, necessary to improve product development processes used by corporations and their supply chains.

Industrial relevance

Industry generates significant and proprietary data which could be better leveraged to improve their processes. Strong and secure infrastructure provides a foundation for intelligent, integrated, and innovative strategies (e.g., big data analytics, cloud computing) to improve design, manufacturing, and maintenance of complex products. Future employees with skills and experience in data analytics and computational processes add value to the enterprise.


·       Cloud computing

·       Cloud-based digital manufacturing

·       Modeling; data, network, and graph analysis

·       Internet of Things, Services and People

·       Information security

·       Universally available accessible technical data package (TDP)

·       Dynamic remote real-time collaboration


The objective of this research thrust is to develop new engineering design processes and methodologies to improve creativity and innovation in design of products, systems, production systems, and supply chains.  Research in this area focuses on collaboration tools, measuring and improving creativity in designs of products and service systems, and social centric design processes.

Industrial relevance

Innovative designs, design tools, and methods result in more desirable products and services, produced at lower cost and reduced time to market.  This capability leads to increased, longer-term market share and improved customer capabilities.


·       Technologies enabling collaborative design and the participation of others in the design process

·       Measuring, analyzing, and improving creativity as a process, and an outcome.

·       Social-centric design practices (crowd-sourced design, collaborative design, etc.)

·       Customer interaction with products and services


The objective of this research thrust is to develop methods that enable better and faster decision making through intelligent, data/information-driven and model-based systems.  Research in this area focuses on the development of tools, methods, and algorithms,  that enhance capabilities of the designers through collaboration with computing resources such as artificial intelligence, cloud-based digital design, data mining, sensor and sensor networks data science and machine learning.

Industrial relevance

Leverage or drive advances in computing and analytics infrastructure, advanced algorithms, methods and tools to provide critical decision making information to the right person at the right time. This focus addresses the needs of industry to effectively use large amounts of data and information to improve design quality, innovation, and time to market.


·       supply chain modeling and analysis

·       sensors and sensor networks

·       analytics for complex data sets

·       smart manufacturing systems development

·       product life cycle optimization

·       Internet of Things utilization


Special Activities

Spring IAB Meeting

  • Dates:     April 7-9, 2020
  • Location: Knoxville, TN (University of Tennesse Knoxville)
  • Final Meeting before NSF graduation.

Facilities and Laboratory

FAME Lab - Factory for Advanced Manufacturing Education



University of Massachusetts Amherst

160 Governors Dr.

Amherst, Massachusetts, 01003

United States

University at Buffalo-SUNY

5 Norton Hall

Buffalo, New York, 14260-4400

United States

Brigham Young University

435F CTB

Provo, Utah, 84602

United States


Wayne State University

4815 Fourth St.
Rm. 2067

Detroit, Michigan, 48202

United States

Iowa State University

3004 Black Engineering Bldg.

Ames, Iowa, 50011-2164

United States

Oregon State University

418 Rogers Hall

Corvallis, Oregon, 97331-6001

United States

Penn State University

310 Leonhard Building

University Park, Pennsylvania, 16802

United States