Decision rule mining for machining method chains based on rough set theory

Rui Wang, Xiangyu Guo, Shisheng Zhong, Gaolei Peng and Lin Wang ()
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Rui Wang: Harbin Institute of Technology
Xiangyu Guo: Harbin Institute of Technology
Shisheng Zhong: Harbin Institute of Technology
Gaolei Peng: Harbin Institute of Technology
Lin Wang: Harbin Institute of Technology

Journal of Intelligent Manufacturing, 2022, vol. 33, issue 3, No 11, 799-807

Abstract: Abstract Decision rules for machining method chains mined from historical machining documents can help technologists quickly design new machining method chains. However, the main factor that limits the practical application of existing rough set models is that the boundary regions are too large. Therefore, a decomposition-reorganization method (DRM) is proposed to mine rules for machining method chains. First, binary coding is used to decompose the existing machining method chains, and the decision rules for a single machining method are mined based on rough set reduction. Then, machining method chains are obtained by reorganizing the machining methods in accordance with the decision rules. DRM can eliminate the boundary regions without human intervention and recommend machining method chains for all features whose parameters have appeared in historical machining documents. Finally, three types of shell parts are used to verify the effectiveness of DRM.

Keywords: Machining method; Process planning; Rule mining; Rough set theory; Derivation rules (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10845-020-01692-w

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