Research on the Assembly Line Scheduling of Fixed Objects for the Large Complex Products

According to the complexity of the assembly line for the large complex products, a new production pattern with fixed objects for the mixed model assembly line is proposed. Improved GA is used to solve the scheduling problem .In this paper, a production scheduling system is developed. It can speed up the production cycle, lower the cost, improve the productivity and so on.

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Design of Mixed-Model Assembly Lines Integrating New Energy Vehicles

Machines ◽

10.3390/machines9120352 ◽

2021 ◽

Vol 9 (12) ◽

pp. 352

Author(s):

Qidong Yin ◽

Xiaochuan Luo ◽

Julien Hohenstein

Keyword(s):

Assembly Line ◽

Mixed Model ◽

Mixed Integer ◽

Assembly System ◽

Benchmark Problems ◽

New Production ◽

New Energy ◽

Mixed Model Assembly Line ◽

Mixed Model Assembly ◽

New Energy Vehicles

The automotive industry is undergoing a transformational period where more and more new energy vehicles (NEVs) are being produced and delivered to the market. Accordingly, some new challenges arise during the manufacturing process for car companies. Since the mixed-model assembly line has been widely used, how to integrate the NEVs into the existing assembly system that was designed for the production of gasoline cars is a key issue. A practical approach assigning a specific workforce to handle NEV assembly work is applied at the BMW assembly shop. This work studies this new production pattern and focuses on the design of the assembly system under this pattern. This work aims to develop a method for minimizing the production cost of NEV assembly. Thus, an exact algorithm for hierarchically solving the assembly line balancing problem and vehicle model sequencing problem is proposed. Mixed integer programming mathematical models that describe these two problems are formulated for the first time. Three new benchmark problems and one industry case that include the NEV models are created to evaluate the effectiveness of the proposed method. Results of numerical tests demonstrate that the developed algorithm can quickly generate reconfiguration solutions of the assembly line for various model mix scenarios and production rates. High flexibility of the manufacturing system can be obtained using the proposed approach.

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The Fault Diagnosis Method of Mixed-Model Assembly Line Based on Dynamic Causality Bayesian Network

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.310.592 ◽

2013 ◽

Vol 310 ◽

pp. 592-595

Author(s):

Jie Cheng

Keyword(s):

Fault Diagnosis ◽

Bayesian Network ◽

Set Theory ◽

Production Scheduling ◽

Assembly Line ◽

Mixed Model ◽

Model Flow ◽

Diagnosis Method ◽

Mixed Model Assembly Line ◽

Mixed Model Assembly

For timely diagnosing the faults of mixed-model assembly line, and highly eliminating abnormal the production line, the time causality relation in the faults of mixed-model assembly line was Fuzzy discretized by the introduction of fuzzy set theory, and the fault diagnosis method of mixed-model assembly line based on dynamic causality bayesian network was established in this paper. Finally, a fault diagnosis simulation system of mixed-model assembly line based on dynamic causality bayesian network was demonstrated and validated by QUEST software. It has shown the proposed method can improve the benefit of production scheduling, and provide a support for adapting to complex and dynamic production scheduling in mixed-model flow production.

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