Panos Y. Papalambros

Optimal Design Laboratory • University of Michigan

I work in design optimization of products and systems, and in advancing design as a holistic yet scientific discipline, integrating practice-based thinking with science-based understanding. Through my research and teaching, I have aimed to establish the scholarship and use of mathematical design optimization as a standard tool in modern design practice and on how it serves society.

In extensive collaboration with industry and government agencies, I have worked on design optimization for advanced automotive systems, including electric and hybrid powertrains and structural design, and linked them with product development, commercial, and regulatory decisions to derive business and government policies. The Analytical Target Cascading (ATC) method developed in our Optimal Design Laboratory is the first proven globally convergent multi-level coordination algorithm for multidisciplinary optimization, considering both organizational and computational complexity.

In our design science research, we have studied design preference elicitation and modeling, and linked engineering design models with those from marketing, behavioral and social science, and economics.

NOTE TO STUDENTS

The 'emeritus' title means I am officially retired and I have limited my 'normal' faculty activities. I no longer advise new PhD students and my research activities are limited primarily to design for sustainable development, involving masters and undergraduate students, and collaborating with other faculty particularly based in Africa..

James B. Angell Distinguished University Professor Emeritus • Donald C. Graham Professor Emeritus of Engineering • Professor Emeritus of Mechanical Engineering • Professor Emeritus of Integrative Systems + Design, College of Engineering • Professor Emeritus of Architecture and Urban Planning • Professor Emeritus of Art & Design • Director, Optimal Design (ODE) Laboratory.

Editor-in-Chief, Design Science Journal, Cambridge University Press

Advisory Board Member and Past President (2017-19), The Design Society

Member, National Academy of Engineering

Contact: pyp at umich dot edu

AFRICA-DESIGN: Design Science for Sustainable Development in Africa

In our Africa-Design work we explore design for sustainable development as defined in the UN Sustainable Development Goals focusing at the community level in Africa. In March 2024 we held a workshop for 20 faculty across the continent on Design Science and AI at Carnegie Mellon University-Africa in Kigali, Rwanda, a very rewarding event endorsed by the US National Academy of Engineering. In October 2024 we held a second workshop in this series at the Witwatersrand University in Johannesburg, South Africa for 25 scholars from 10 African academic institutions sponsored by the Afretec Network and also endorsed by the US NAE .

The A F R I C A - D E S I G N COLLABORATIVE is a collection of projects at the University of Michigan in collaboration with other institutions, primarily Africa-based . We support the Design Society's AFRICA-DESIGN initiative to build a network of design researchers, educators, and practitioners based in African countries with particular emphasis on design for sustainable and equitable development; and to link them with colleagues in the worldwide design community. .

The AFRICA-DESIGN COLLABORATIVE @UM team projects involve

Conducting design research and education projects
Supporting research and education connections and networking
Scoping scholarly work and funding sources
Promoting early career design scholars at African Institutions

AFRICA-DESIGN is a Design Society initiative to build a network of design researchers, educators, and practitioners based in African countries and beyond, with particular emphasis on design for sustainable development; and to link them with colleagues in the worldwide design community. The initiative builds on the mutual learning opportunities in the challenges that we all share.

Principles of Optimal Design: Modeling and Computation

Cambridge University Press, New York, 2017 (3d ed.), 2000 (2d ed.), 1988 (1st ed.).

The Third Edition has thoroughly updated material and includes two new chapters on non-gradient methods and systems design optimization. Visit the dedicated site for instructors and students.

All artifacts surrounding us are the results of designing. Creating these artifacts involves making a great many decisions, which suggests that designing can be viewed as a decision-making process. An abstract description of the artifact using mathematical expressions of relevant natural laws, experience, and geometry is the mathematical model of the artifact. This model may contain many alternative designs, so criteria for comparing these alternatives can be introduced in the model. Within the limitations of such a model, the best, or optimum, design can be identified with the aid of mathematical methods.

With fond memories for Douglass J. Wilde, co-author, mentor, and friend.

Research

ORCID • LinkedIn • Google Scholar • Scopus • Publons • ResearchGate • Academia.edu

Design Optimization

Design optimization evolved in parallel to operations research as a way to codify and support design decisions mathematically. Design thinking emerged as a way to describe a user-centered design process that seeks to unpack the core values behind design decisions. In our modern definition of Design Science as the field that studies the creation of artifacts and their embedding in our physical, psychological, economic, social and digital environments, these two approaches are merging. In perspective, my research reflects this evolution in design optimization that links the engineering, business, computer, behavioral, social, and public policy sciences, primarily through mathematical modeling while explicitly recognizing the limitations of this design paradigm.

Over four decades we have studied a variety of topics in design optimization and design science broadly classified below. See the research section for more information.

Systems Design and Product Development: Business and policy integration • Modularity and optimal design of product families • Sustainable design of products and systems • Systems design thinking

Product Design and Decision Making: Aesthetic and emotional design • Preference elicitation and modeling

Optimal Design Theory and Algorithms: Artificial intelligence in optimal design • Optimal configuration and topology design • Co-Design: Optimal design and optimal control • Monotonicity analysis • Multiobjective design optimization • Design under uncertainty

Application Domains in Systems and Product Design: Architectural design • Automotive systems, especially hybrid and electric powertrains • Electromagnetic systems, especially antennas • Manufacturing and design integration • Structural design

Design Research and Education

Current projects:

Design for Sustainable Development: In this umbrella project under the AFRICA-DESIGN@UM initiative we explore how design contributes to sustainable development in the rapidly growing African countries. Typically we model Integrated Natural Resource Conservation and Development (INRCD) projects using system design optimization. These projects involve quantitatively integrating farming systems, community household needs, irrigation, and microgrids.

In particular, we look at how small agricultural communities may be affected by changing weather patterns due to global warming and how they can improve their resilience to shocks..

Power Differentials in Co-Design: How do we include marginalized individuals and communities in the design process of products and systems that directly affect them?

Select Courses Tought

Analytical Product Design

(ME 455/DESCI 501)

A benchmark, holistic, and intense design experience. Artifact design is addressed from a multidisciplinary perspective that includes engineering, art, psychology, ergonomics, marketing, and economics. Includes several rounds of prototyping.

Design Process Models

(DESCI 502)

Exploration of the science behind the design process and its elements, including the psychology of creativity and decision making, systems thinking, interaction and coordination of decisions in multi-disciplinary design settings.

Design Optimization

(ME 555/MFG 555)

Project-based introduction to the mathematical modeling and solution algorithms for engineering design optimization problems., including model analysis, gradient and non-gradient methods and system optimization.

Design and Manufacturing I

(ME 250)

A complete introductory experience to mechanical design and production. Basics in visual thinking, engineering drawing, machine anatomy, manufacturing: processes, materials, engineering analysis and prototyping.

Report abuse