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Adaptive and dynamic process planning using neural networks

Title
Adaptive and dynamic process planning using neural networks
Authors
Joo, JPark, SCho, HB
POSTECH Authors
Cho, HB
Date Issued
Jan-2001
Publisher
TAYLOR & FRANCIS LTD
Abstract
Although feature-based process planning plays a vital role in automating and integrating design and manufacturing for efficient production, its off-line properties prevent the shop floor controller from rapidly coping with dynamic shop floor status such as unexpected production errors and rush orders. This paper proposes a conceptual framework of the adaptive and dynamic process planning system that can rapidly and dynamically generate the needed process plans based on shop floor status. In particular, the generic schemes for constructing dynamic planning models are suggested. The dynamic planning models are constructed as neural network forms, and then embedded into each process feature in the process plan. The shop floor controller will execute them to determine machine, cutting tools, cutting parameters, tool paths and NC codes just before the associated process feature is machined. The dynamic nature of process planning enables the shop floor controller to increase flexibility and efficiency in unexpected situations.
URI
http://oasis.postech.ac.kr/handle/2014.oak/19426
Article Type
Article
Citation
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, vol. 39, no. 13, page. 2923 - 2946, 2001-01
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조현보CHO, HYUNBO
Dept of Industrial & Management Enginrg
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