NDLI: Inverse engineering: A methodology for learning models to support engineering design

Content Provider	IEEE Xplore Digital Library
Author	Rao, R.B. Lu, S.C.-Y.
Copyright Year	1993
Description	Author affiliation: Univ. of Illinois, Urbana, IL, USA (Rao, R.B.; Lu, S.C.-Y.)
Abstract	Synthesis tasks in engineering design are currently performed by iteratively using computer-based analysis simulators in a generate-and-test fashion. In the inverse engineering methodology machine learning techniques are used to learn bi-directional models which can directly provide synthesis support. This greatly reduces design iterations. Inverse engineering provides decision-making support during the early stages of design. The authors focus on supporting early product design in parameterized domains. They present the three main phases of the inverse engineering methodology and briefly describe the model formation and selection phases. The emphasis is on the final model-utilization phase where the models learned are used by the design engineer to efficiently explore the tradeoffs in the design space in an interactive fashion. Two examples from the early design of combustion chambers for diesel engines are presented.<>
Starting Page	205
Ending Page	211
File Size	685071
Page Count	7
File Format	PDF
ISBN	0818638400
DOI	10.1109/CAIA.1993.366609
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1993-03-01
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Design engineering Performance analysis Computational modeling Analytical models Computer simulation Machine learning Bidirectional control Decision making Product design Combustion
Content Type	Text
Resource Type	Article

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