Simultaneous Balancing and Buffer Allocation for Assembly Line with Stochastic Task Times

被引:0
作者
Liu X. [1 ]
Liu T. [1 ]
Gu J. [1 ]
Li A. [1 ]
机构
[1] College of Mechanical Engineering, Tongji University, Shanghai
来源
| 2018年 / Science Press卷 / 46期
关键词
Assembly line balancing; Assembly line design; Buffer allocation; Integrated optimization; Station complexity;
D O I
10.11908/j.issn.0253-374x.2018.08.013
中图分类号
学科分类号
摘要
Line balancing problem and buffer allocation problem are often studied separately, but there is a complex interaction between them. Considering stochastic assembly line, the operating time variability exacerbates the interaction between the two problems. Optimizing sequentially is difficult to get the global optimal solution. Therefore, it is necessary to solve the two problems simultaneously. The probability distribution of operating time is measured as station complexity based on information entropy. An integrated optimization model is established. The optimization objectives are as follows: maximizing of the production rate and minimizing of the smoothness index of standard workstation time, the smoothness index of workstation complexity and total buffer capacities. Parametric modeling simulation is used to calculate production rate. An improved genetic algorithm is put forward to obtain integrated optimization solution. An instance of a gearbox assembly line is calculated and verified, which proves the effectiveness of the method. © 2018, Editorial Department of Journal of Tongji University. All right reserved.
引用
收藏
页码:1098 / 1106
页数:8
相关论文
共 16 条
  • [1] Lorenzo T., Simultaneous balancing and buffer allocation decisions for the design of mixed-model assembly lines with parallel workstations and stochastic task times, International Journal of Production Economics, 162, 4, (2015)
  • [2] Nkasu M.M., Leung K.H., A stochastic approach to assembly line balancing, International Journal of Production Research, 33, 4, (1995)
  • [3] Song L., Zhang Z., Cheng W., Heuristic for two-sided stochastic assembly line balancing, Industrial Engineering Journal, 14, 4, (2011)
  • [4] Adil B., Lale O., Stochastic U-line balancing using genetic algorithms, International Journal of Advanced Manufacturing Technology, 32, 1-2, (2007)
  • [5] Zhou L., Song H., Han Y., Genetic algorithm-based stochastic production line balancing, Machinery, 41, 3, (2003)
  • [6] Liu Y., Zuo D., Zhang D., Et al., Assembly line balancing with stochastic operation times, Computer Integrated Manufacturing Systems, 20, 6, (2014)
  • [7] Frizelle G., Woodall P., Big data, data loss and observation analysis, International Conference on Information Quality, pp. 1-6, (2016)
  • [8] Konstantinos E., Manufacturing systems complexity: an assessment of manufacturing performance indicators unpredictability, CIRP Journal of Manufacturing Science & Technology, 7, 4, (2014)
  • [9] Wang H., Hu S.J., Manufacturing complexity in assembly systems with hybrid configurations and its impact on throughput, CIRP Annals-Manufacturing Technology, 59, 1, (2010)
  • [10] He F., Rao Y., Shao X., Assembly line dynamic balancing problem based on assembly relationship complexity, Computer Integrated Manufacturing Systems, 19, 1, (2013)