Prof. Maria C Yang

Gail E Kendall (1978) Professor of Mechanical Engineering
Deputy Dean of Engineering
Faculty Academic Director, D-Lab
Founder and Director, Ideation Lab
Margaret MacVicar Faculty Fellow

Primary DLC

Department of Mechanical Engineering

MIT Room: 3-449B

Assistant

Maral Banosian
maralb@mit.edu

Areas of Interest and Expertise

Design Methods
Design Process
Product Design
Information Capture and Retrieval
Interaction Design

Research Summary

Engineering design is concerned with the creation of physical artifacts, from simple consumer products to complex, large scale engineering systems. Dr. Yang's research considers the processes used to bring these products and systems into being. Her work focuses on the very earliest stage of design because of its critical role in the success of a product. It is estimated that 70% of the cost of a design is fixed in the first 30% of the design process. Early stage design process generally includes defining the requirements of a design, followed by generation of ideas to fulfill those requirements, then selection among those ideas. However, the early stage of the design process is still fraught with ambiguity and iteration, particularly for novel designs where there is little existing physical knowledge to build upon. How can the design team know that the design requirements have been specified appropriately? How can the team be sure that it has generated a good idea? How can they be confident that the best idea has been selected? Dr. Yang's research is in establishing fundamental strategies for assessing the process of design in this early stage. Quantitative assessment of such ambiguous processes has long been a challenge. Her innovative approach is to extract formal structures from rich, informal representations of designer behavior such as sketches, prototypes, and language. Her vision is to formulate metrics and tools for assessing early stage design that can be used to inform stakeholders about the potential of their design based on their process. This approach would provide a data driven way to understand both design process and the behavior of the designer, and will help the design team be more effective at producing appropriate, carefully considered designs.


(summary updated 11/2011)

Recent Work