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Knowledge-based model for constructing master assembly sequence
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DOI：10.1016/j.jmsy.2014.10.004.png)
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Abstract
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A novel knowledge-based mixed-integer programming (MIP) model is presented for generating the assembly sequence of a given product based on available assembly sequence data of similar products. The proposed mathematical model finds the optimal consensus assembly sequence tree for an existing product family based on the assembly sequence trees of individual product family members. The proposed model is inspired by problems studied in biology and phylogenetics where a consensus species classification for a set of conflicting classifications is sought. The generated consensus tree serves as a master assembly sequence tree and is used to generate the assembly sequence for new product variants that falls within, or significantly overlaps with, the boundary of the considered family of products. The developed model is demonstrated using a family of pilot valves. The knowledge-based MIP model supports automatic assembly sequence generation, hence, reduces assembly planning effort and cost and improves productivity. (C) 2014 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
Keywords:
Master assembly sequence
Consensus trees
Knowledge discovery
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