An Approach for Level Scheduling Mixed Models on an Assembly Line in a JIT Production System

Li Nie; Yue Wei Bai; Xin Jiang; Chang Tao Pang

doi:10.4028/www.scientific.net/AMM.697.473

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 697An Approach for Level Scheduling Mixed Models on...

An Approach for Level Scheduling Mixed Models on an Assembly Line in a JIT Production System

Abstract:

A mixed-model assembly line (MMAL) is a type of production system that is capable of producing different models of a common base product simultaneously. Mixed-model assembly line level scheduling problem (MMALSP) is a challenge for Just-in-time (JIT) production systems. In the paper, a mixed-model assembly line level scheduling model is proposed which considers multiple objectives simultaneously. The considered objectives include the variation in parts consumption considering the batch part supply, inventory cost and maximum transportation load. An approach based on genetic algorithm is proposed to solve the multiple objectives problem. In order to translate individuals in the GA population into candidate scheduling schemes a delivery scheduling algorithm (DSA) is proposed. In addition, dimensionless processing technique is employed in the design of the fitness function in order to comprehensively evaluate different individual considering three objectives simultaneously. The approach’s performance is validated through comprehensive experiment.

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Periodical:

Applied Mechanics and Materials (Volume 697)

Pages:

473-477

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.697.473

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Online since:

November 2014

Authors:

Li Nie*, Yue Wei Bai, Xin Jiang, Chang Tao Pang

Keywords:

Batched Part Supply, Genetic Algorithm (GA), Just-in-Time, Level Scheduling, Mixed Model Assembly Lines

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* - Corresponding Author

References

[1] Nils Boysen; Malte Fliedner; Armin Scholl. Level scheduling for batched JIT supply. Flexible Services and Manufacturing Journal, 2009, 21(1-2): 31-50.

DOI: 10.1007/s10696-009-9058-z

Google Scholar

[2] Kubiak W (1993) Minimizing variation of production rates in just-in-time systems: A survey. Eur J Oper Res 66: 259–271.

DOI: 10.1016/0377-2217(93)90215-9

Google Scholar

[3] LI Honghua, LAN Xiuju, CHEN Chengpin. Memetic algorithm for sequencing problems in mixed model assembly lines. Light Industry Machinery, 2013, 31(2): 96-99, 104. [in Chinese].

Google Scholar

[4] Fliedner, Malte; Boysen, Nils; Scholl, Armin. Solving symmetric mixed-model multi-level just-in-time scheduling problems. Discrete Applied Mathematics, 2010, 158(3): 222-231.

DOI: 10.1016/j.dam.2009.09.013

Google Scholar

[5] GU Wei, ZHANG Jie. Improved-ant-colony-algorithm-based optimization technology for auto mixed model production. Mechanical Manufacturing, 2008, 46(532): 10-13. [in Chinese].

Google Scholar