Optimizing assembly sequence planning using precedence graph-based assembly subsets prediction method
ISSN: 0144-5154
Article publication date: 29 November 2019
Issue publication date: 30 March 2020
Abstract
Purpose
Assembly sequence planning (ASP) plays a vital role in assembly process because it directly influences the feasibility, cost and time of the assembly process. The purpose of this study is to solve ASP problem more efficiently than current algorithms.
Design/methodology/approach
A novel assembly subsets prediction method based on precedence graph is proposed to solve the ASP problem. The proposed method adopts the idea of local to whole and integrates a simplified firework algorithm. First, assembly subsets are generated as initial fireworks. Then, each firework explodes to several sparks with higher-level assembly subsets and new fireworks are selected for next generation according to selection strategy. Finally, iterating the algorithm until complete and feasible solutions are generated.
Findings
The proposed method performs better in comparison with state-of-the-art algorithms because of the balance of exploration (fireworks) and exploitation (sparks). The size of initial fireworks population determines the diversity of the solution, so assembly subsets prediction method based on precedence graph (ASPM-PG) can explore the solution space. The size of sparks controls the exploitation ability of ASPM-PG; with more sparks, the direction of a specific firework can be adequately exploited.
Practical implications
The proposed method is with simple structure and high efficiency. It is anticipated that using the proposed method can effectively improve the efficiency of ASP and reduce computing cost for industrial applications.
Originality/value
The proposed method finds the optimal sequence in the construction process of assembly sequence rather than adjusting order of a complete assembly sequence in traditional methods. Moreover, a simplified firework algorithm with new operators is introduced. Two basic size parameters are also analyzed to explain the proposed method.
Keywords
Acknowledgements
Support from the National Natural Science Foundation of China (grant Nos 51490663, 51935009, 51875517) and Key Research and Development Program of Zhejiang Province (grant No. 2017C01045) is gratefully acknowledged.
Citation
Zhang, N., Liu, Z., Qiu, C., Hu, W. and Tan, J. (2020), "Optimizing assembly sequence planning using precedence graph-based assembly subsets prediction method", Assembly Automation, Vol. 40 No. 2, pp. 361-375. https://doi.org/10.1108/AA-02-2019-0031
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited