Multilevel, multidisciplinary optimization methods are important for designing complex systems, wiht many componeents and and many disciplines involved in a distributed design environment. We study rigorous methods to partition and coordinate the decomposed problem solution, and to examine solution properties under conditions of uncertainty. Applications include hybrid powertrains, vehicle design, electronic devices, product development, architecture.

Keywords: multidisciplinary optimization (MDO), analytical target cascading (ATC), reliability-based design optimization (RBDO), robust optimal design, optimal partitioning and coordination, uncertainty, validation, verification and testing

Sponsors: National Science Foundation, US Army Automotive Research Center, Ford Motor Company, General Motors Corporation.

Design of modern engineered systems is characterized by synergistic integration of mechanical, electrical, electronic, computer, optical and control disciplines—what has become known as mechatronics. We use the term “controlled systems” to include all systems where control functions are critical elements of their performance, and the term “co-design” (combined design) to indicate that design of the “plant” in the controls jargon and of the plant controller must be done in a combined, integral manner. We study theoretical foundations for quantifying the coupling between design and control functionality based on optimizing overall system performance.  We also study how learning algorithms can be used for autonomous decision making in vehicle powertrain control. Applications include automotive vehicles, elevators, MEMS devices.

Keywords: optimal design, optimal control, global sensitivity, coupling strength, robust control, q-learning, markov decision processes

Sponsors: National Science Foundation, Ford Motor Company, US Army Automotive Research Center

Faculty collaborator: A. Galip Ulsoy, Dennis Assanis

An interdisciplinary team of faculty and students from Art and Design, Business, Mathematics, Mechanical Engineering, and Psychology is exploring how to bridge the disciplinary viewpoints towards artifact creation and design. The emphasis is on developing a commonly understood quantification that employs modeling tools from the various disciplines, while also understanding the boundaries of rational quantification.

Sponsors: Horace H Rackham School of Graduate Studies, the Provost's office and the participating academic units at the University of Michigan.

Engineers often stipulate the existence of user preferences in formulating decision models. Research in psychology and the behavioral sciences indicate that preference structures are much more complex than we often assume and frequently contain inconsistencies. This research merges engineering and psychology research to understand the structure of preferences and derive preference assessment tools that are rigorous from the behavioral sciences viewpoint and useful to product designers. Applications include environmentally sustainable products and product aesthetics

Keywords: Product semantics, preference incosistency, Kano method, interactive IGAs, conjoint analysis, prefmaps

Sponsors: National Science Foundation, Ford Motor Company, Graham Chair Endowment.

Faculty Collaborators: Richard Gonzalez, Jan-Henrik Anderson, Greg Wakefield

The Ford BlockM Sustainability Laboratory Project develops a new, innovative product model for mobility specifically considering environmental sustainability along with other traditional product facets.  The U-M research will assist Ford in trhee areas: (a) Include environmental sustainability as a customer driven attribute, similar to safety, in an evaluation model, (b) Explore cost and business models that include lifecycle environmental sustainability, and (c) Generate product cues that customers associate with environmental sustainability. 

Sponsor: Ford Motor Company, U-M Innovation Alliance

Faculty Collaborators: Jan-Henrik Anderson, Fred Feinberg, Richard Gonzalez, Greg Keoleian, Colleen Seifert, Steven Skerlos

The multi-University project studies modeling methods to analyze materials flows that result from policy instruments aimed at reducing greenhouse gas emissions (GHG) emissions from passenger cars and light trucks. A set of linked models account for producer and consumer behavioral responses to GHG reduction policies. These forecasted market responses are integrated into a novel framework for predictive life cycle and material flow analyses (LCA/MFA). Major tasks are: 1) model vehicle design options and materials use for their costs and performance; 2) evaluate the market penetration of these options by modeling their performance in the context of market-based and regulatory policy instruments, producer objectives, and consumer preferences; and, 3) evaluate the consequences of market responses on global materials flows and life cycle emissions using a system optimization framework.  

Sponsor: National Science Foundation (Steve Skerlos project director)