Panos Y. Papalambros
Optimal Design Laboratory • University of Michigan
James B. Angell Distinguished University Professor • Donald C. Graham Professor of Engineering • Professor of Mechanical Engineering • Professor of Integrative Systems + Design, College of Engineering • Professor of Architecture and Urban Planning • Professor of Art and Design at the University of Michigan.
Director, Optimal Design (ODE) Laboratory
Contact: +1 (734) 647-8401; pyp at umich dot edu
Cambridge University Press, New York, 2017 (3d ed.), 2000 (2d ed.), 1988 (1st ed.).
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.
DESIGN OPTIMIZATION OF PRODUCTS AND SYSTEMS; DESIGN SCIENCE
Product design and decision making: Preference elicitation, preference structures and assessment • Learning algorithms and mathematical models of crowdsourcing • Emotional design: Aesthetics, proportionality, sustainability • Design for behavior modification.
System design optimization and product development: Decomposition and coordination strategies for large-scale systems• Multidisciplinary design optimization (MDO) • Design for market systems: Enterprise-wide business, marketing, engineering, public policy and economic considerations • Analytical target cascading and analytical target setting • Optimal design of product platforms, portfolios, and product lines • Optimal design of system topologies
Optimal design theory and algorithms: Monotonicity analysis • Global, parametric, mixed-discrete, and Pareto optimization • Distributed, multilevel, multidisciplinary system optimization • Artificial intelligence, expert systems and nonlinear mathematical optimization • Optimal design under uncertainty • Combined optimal design and optimal control
Analytical Craftsmanship • Architectural design • Automotive systems, especially hybrid and electric powertrains • Electromagnetic systems, especially antennas • Manufacturing and design integration • Structural design • Sustainable products and systems
Recent Courses Taught
Analytical Product Design (ME 455/DESCI 501) Design of artifacts is addressed from a multidisciplinary perspective that includes engineering, art, psychology, ergonomics, marketing, and economics. Using a decision-making framework, emphasis is placed on understanding basic quantitative methods employed by the different disciplines for making design decisions, building mathematical models, and accounting for interdisciplinary interactions throughout the design development process. Students work in teams to apply the methods on a design project from concept generation to prototyping and design verification. Open to seniors and graduate students. (Fall Term 2018)
Design Optimization (ME 555/MFG 555) Mathematical modeling of engineering design problems for optimization. Boundedness and monotonicity analysis of models. Differential optimization theory for unconstrained and constrained problems, and selected numerical algorithms for continuous nonlinear models. Emphasis on the interaction between proper modeling and computation. Students propose design term projects from various disciplines and apply course methodology to optimize designs. Open to graduate students and seniors by permission. Usually offered in Winter Term.
Design and Manufacturing I (ME 250) Basics of mechanical design: visual thinking, engineering drawing, and machine anatomy. Basics of manufacturing: processes, materials, and thermofluid aspects. Use of computers in various phases of design and manufacturing. Exposure to CAD systems and basic machine shop techniques. Design/manufacturing project. Three hours lecture and two hours laboratory.
Design Process Models (DESCI 502) Interaction and coordination of decisions based on multi-discipline design analyses is studied in the context of a newly developed artifact. Innovation and creativity are addressed as elements of the design process. Enterprise design decisions made on functionality and business criteria are analyzed within organizational, cultural and social models. Students propose and test novel analysis methods and design process models. Open to graduate students and seniors. Usually offered in the Winter Term.
DESCI 790/791: DESIGN SCIENCE COLLOQUIUM - Various topics in Design Science are presented by invited speakers, faculty and students in this community-building course. The goal is to increase cross-disciplinary understanding and define research topics in design science. (Fall Term 2018)