Integrated optimization of production planning and scheduling for fixed- position assembly workshop with rework

被引：0
|
作者：
Jiang N.-Y. [1 ,2 ,3 ]
Yan H.-S. [1 ,2 ]
机构：
[1] School of Automation, Southeast University, Nanjing
[2] The MOE Key Laboratory of Measurement and Control of Complex Systems of Engineering, Southeast University, Nanjing
[3] Department of Economics and Management, Nanjing Technology University, Nanjing
来源：
Jiang, Nan-Yun (jiangnanyun@163.com) | 2017年 / Northeast University卷 / 32期
关键词：
Fixed-position; Integrated optimization of production planning and scheduling; Memetic algorithm; Rework;
D O I：
10.13195/j.kzyjc.2016.1151
中图分类号：
学科分类号：
摘要：
Considering that the rework of nonconforming product leads to the unfeasible production planning and scheduling in the fixed-position assembly workshop, an integrated optimization method for the production planning and scheduling based on delaying rework is proposed. Firstly, rough-cut production planning based on delaying rework is made. After this plan was delivered and performed, the nonconforming products of every cycle are put into the buffer. Correspondingly, at the beginning of the next cycle, the production plan is adjusted and its corresponding schedule is optimized. Both of them are identified whether to satisfy the requirement of load rate of assembly teams. Alternate iteration of the production plan and schedule is proceeded until the optimization and balance are achieved simultaneously. Finally, the examples are given to illustrate the feasibitily and effectiveness. © 2017, Editorial Office of Control and Decision. All right reserved.
引用
收藏
页码：2045 / 2055
页数：10
相关论文
共 18 条
  • [11] Wan F., Liu J.H., Ning R.X., Et al., Visual production scheduling technology for the complex product assembly process, Computer Integrated Manufacturing Systems, 19, 4, pp. 755-765, (2013)
  • [12] Hu S.Q., Zhang B.X., Zhang X.W., Et al., Decision-making of planning input quantity based on qualified rate and effective rework rate, Mathematics in Practice and Theory, 44, 8, pp. 1-9, (2014)
  • [13] Zhang G.H., Gao L., Liu W.J., Dynamic scheduling optimization strategy based on memetic algorithm, China Mechanical Engineering, 19, 15, pp. 1827-1831, (2008)
  • [14] Wu M.C., Han W.M., Sun X.M., Et al., Research on the multi-period virtual cellular dynamic scheduling with cycle-driven in outfitting, Shanghai Management Science, 37, 3, pp. 65-69, (2015)
  • [15] Yan H.S., Zhang X.D., Dong H., Optimal production planning for workshops with demand constraints, J of Systems Engineering, 16, 1, pp. 24-29, (2001)
  • [16] Moscato P., An introduction to population approaches for optimization and hierarchical objective functions: A discussion on the role of Tabu search, Annals of Operations Research, 41, 1-4, pp. 85-121, (1993)
  • [17] Tavakkoli M.R., Safaei N., Sassani F., A memetic algorithm for the flexible flow line scheduling problem with processor blocking, Computer Operation Research, 36, pp. 402-414, (2009)
  • [18] Cai B., Wang S.L., Hu H.B., Genetic algorithm with local search for job shop scheduling problem, Advances in Information Sciences and Service Sciences, 3, 9, pp. 42-49, (2011)
12