TY - GEN
T1 - ASUPPA
T2 - ASME 2000 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2000
AU - Li, Xiaomin
AU - Kambhampati, Subbarao
AU - Shah, Jami
N1 - Funding Information:
This research is supported by NSF young investigator award(NYI) IRI-9457634 to Kambhampati. We would like to thank Bernie Bettig, Kartheek Hirode and Sachi Solkhan for their help in implementation.
Publisher Copyright:
Copyright © 2000 by ASME.
PY - 2000
Y1 - 2000
N2 - The limited success and acceptance of automated process planning methods in the industry can be traced to the fact that most existing approaches aim at complete automation. We believe that the quest for complete automation is flawed, both because in practice optimality metrics for process plans are context-sensitive, and because there is significant organizational resistance to approaches that completely eliminate humans from the process planning framework. In this paper, we present an interactive and iterative planning framework, called ASUPPA, which focuses instead on providing intelligent assistance to a human process planner. After generating a "good"default process plan, ASUPPA engages in a "present - elicit criticism - revise"loop with an expert process planner. To operate successfully, ASUPPA needs access to the full search space of process plans, and have the ability to incrementally modify plans in response to expert criticism. The former is provided by basing ASUPPA on ASU Features Testbed, a comprehensive and systematic framework for recognizing and reasoning with features in machinable parts. To support the latter, the system is equipped with an iterative and interactive search mechanism. We will discuss the operational details of the resultant system, called ASUPPA.
AB - The limited success and acceptance of automated process planning methods in the industry can be traced to the fact that most existing approaches aim at complete automation. We believe that the quest for complete automation is flawed, both because in practice optimality metrics for process plans are context-sensitive, and because there is significant organizational resistance to approaches that completely eliminate humans from the process planning framework. In this paper, we present an interactive and iterative planning framework, called ASUPPA, which focuses instead on providing intelligent assistance to a human process planner. After generating a "good"default process plan, ASUPPA engages in a "present - elicit criticism - revise"loop with an expert process planner. To operate successfully, ASUPPA needs access to the full search space of process plans, and have the ability to incrementally modify plans in response to expert criticism. The former is provided by basing ASUPPA on ASU Features Testbed, a comprehensive and systematic framework for recognizing and reasoning with features in machinable parts. To support the latter, the system is equipped with an iterative and interactive search mechanism. We will discuss the operational details of the resultant system, called ASUPPA.
UR - http://www.scopus.com/inward/record.url?scp=85148761152&partnerID=8YFLogxK
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U2 - 10.1115/DETC2000/CIE-14628
DO - 10.1115/DETC2000/CIE-14628
M3 - Conference contribution
AN - SCOPUS:85148761152
T3 - Proceedings of the ASME Design Engineering Technical Conference
SP - 1
EP - 15
BT - 20th Computers and Information in Engineering Conference
PB - American Society of Mechanical Engineers (ASME)
Y2 - 10 September 2000 through 13 September 2000
ER -