Manufacturing Technology 2018, 18(2):337-342 | DOI: 10.21062/ujep/102.2018/a/1213-2489/MT/18/2/337

Research on Evolution Balancing for Product Family Assembly Line in Big Data Environment

Yongming Wu1,2, Yanxia Xu1, Lifei Luo1, Han Zhang1, Xudong Zhao1
1 Modern Manufacturing Key Laboratory of Guizhou University, Guizhou Guiyang 550025, China
2 Public Big Data Key Laboratory of Guizhou Province, Guizhou, Guiyang, 550025, China

Aiming at the problem of product family assembly line (PFAL) evolution balancing, an evolution balancing model for PFAL is established and an improved algorithm based on NSGA_II is also proposed. Firstly, the product family evolution and assembly line characteristics are researched and analyzed in big data environment. Tasks on PFAL are divided into platform and personality tasks, and the stability of assembly tasks is mainly considered especially. In the optimization process, a chromosome encoding based on TOP sorting algorithm is adopted, and a new density selection and decoding algorithm is proposed to make up for the deficiencies in traditional algorithms. Finally, an example of PFAL planning is given to verify the effectiveness and feasibility of the improved NSGA_II.

Keywords: Big Date, Product Family Assembly Line, Evolution Analyzing, Balancing Optimization

Published: April 1, 2018  Show citation

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Wu Y, Xu Y, Luo L, Zhang H, Zhao X. Research on Evolution Balancing for Product Family Assembly Line in Big Data Environment. Manufacturing Technology. 2018;18(2):337-342. doi: 10.21062/ujep/102.2018/a/1213-2489/MT/18/2/337.
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