Assembly Sequence Planning Using Inductive Learning

Takeshi Murayama; Bungo Takemura; Fuminori Oba

doi:10.20965/jrm.1999.p0315

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JRM Vol.11 No.4 pp. 315-320

doi: 10.20965/jrm.1999.p0315

(1999)

Paper:

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Assembly Sequence Planning Using Inductive Learning

Takeshi Murayama^*, Bungo Takemura^** and Fuminori Oba^*

^*Department of Machine Design Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-hiroshima, Hiroshima 739-8527, Japan

^**Energy and Industrial Systems Center, Mitsubishi Electric Corporation, 6-14 Maruo-Machi, Nagasaki, 850-91, Japan

Received:

April 1, 1999

Accepted:

April 2, 1999

Published:

August 20, 1999

Keywords:

assembly planning, machine learning, CAD, CAPP

Abstract

The authors propose acquiring heuristic rules automatically for generating assembly sequences efficiently. Heuristic rules are reduced from training examples by inductive learning. Additional training examples are made from information on assembly sequences and used for modifying heuristic rules. As the assembly sequence generation and modification of heuristic rules are executed more, heuristic rules are refined and assembly sequences are generated efficiently. An experiment demonstrated the effectiveness of the approach.

Cite this article as:

T. Murayama, B. Takemura, and F. Oba, “Assembly Sequence Planning Using Inductive Learning,” J. Robot. Mechatron., Vol.11, No.4, pp. 315-320, 1999.

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This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

Assembly Sequence Planning Using Inductive Learning

Takeshi Murayama*, Bungo Takemura** and Fuminori Oba*

Takeshi Murayama^*, Bungo Takemura^** and Fuminori Oba^*