To promote the performance of production, and enhance the machine utilization ratio, a scheduling method based on balancing takt of high flexibility numerical control manufacturing cells is proposed. First, the process planning is established on the basis of process characteristics and equipment capacity, then the balancing takt as optimal processing views combination is achieved on the basis of considering the preparation time, machine capacity and processing sequence. Second, the product scheduling models which considered the product changeovers time is proposed based on balancing takt result, and then a genetic algorithm is proposed to solve the model. Finally, a shell numerical control manufacturing cell is provided as example, and a comparative variable batch scheduling model and two-stage scheduling based on balancing takt is conducted. Study identified, two-stage scheduling based on balancing takt can significantly reduce the production cycle and promote the performance of numerical control machine.
ZHAO Dongfang
,
ZHANG Xiaodong
,
WANG Yiqi
,
ZHOU Hongli
. Production Takt Balancing Scheduling of High Flexibility Numerical Control Manufacturing Cells[J]. Journal of Mechanical Engineering, 2018
, 54(24)
: 216
-225
.
DOI: 10.3901/JME.2018.24.216
[1] PAJOUTAN M, GOLMOHAMMADI A, SEIFBARGHY M. CMS scheduling problem considering material handling and routing flexibility[J]. The International Journal of Advanced Manufacturing Technology, 2014, 72(5-8):881-893.
[2] CHENG H M, YING K C. Minimizing makespan in a flow-line manufacturing cell with sequence dependent family setup times[J]. Expert Systems with Applications, 2011, 38(12):15517-15522.
[3] ADB K, ABHARY K, MARIAN R. A Methodology for Scheduling Robotic Flexible Assembly Cells Using Fuzzy Logic and Simulation[D]. London:Newswood Limited, 2013.
[4] 孔继利,贾国柱. 考虑搬运时间的多品种、小批量混流制造系统批量加工模式的优化与资源调度[J]. 系统工程理论与实践, 2014, 34(11):2801-2807. KONG Jili, JIA Guozhu. Optimization of the batches processing modes and resource scheduling for mixed-model manufacturing system of multi-variety and small-batch considering handling time[J]. System Engineering Theory and Practice, 2014, 34(11):2801-2807.
[5] 张洁,秦威,宋代立. 考虑工时不确定的混合流水车间滚动调度方法[J]. 机械工程学报, 2015, 51(11):99-108. ZHANG Jie, QIN Wei, SONG Daili. Rescheduling algorithm based on rolling horizon procedure for a dynamic hybrid flow shop with uncertain processing time[J]. Journal of Mechanical Engineering, 2015, 51(11):99-108.
[6] 曾强,杨育,王小磊,等. 并行机作业车间等量分批多目标优化调度[J]. 计算机集成制造系统, 2011, 17(4):816-825. ZENG Qiang, YANG Yu, WANG Xiaolei, et al. Multi-objective optimization method for equal lot scheduling problem of Job Shop with parallel machines[J]. Computer Integrated Manufacturing Systems, 2011, 17(4):816-825.
[7] 白俊杰,龚毅光,王宁生,等. 批量生产柔性作业车间优化调度研究[J].机械科学与技术, 2010, 29(3):293-298. BAI Junjie, GONG Yiguang, WANG Ningsheng, et al. Flexible job shop scheduling of batch production[J]. Mechanical Scienceand Technology for Aerospace Engineering, 2010, 29(3):293-298.
[8] 徐本柱,费晓璐,章兴玲. 柔性作业车间批量划分与并行调度优化[J].计算机集成制造系统, 2016, 22(8):1953-1964. XU Benzhu, FEI Xiaolu, ZHANG Xingling. Batch division and parallel scheduling optimization of flexible job shop[J]. Computer Integrated Manufacturing Systems, 2016, 22(8):1953-1964.
[9] OZTURK C, TUNALI S, HNICH B, et al. Balancing and scheduling of flexible mixed model assembly lines with parallel stations[J]. The International Journal of Advanced Manufacturing Technology, 2013, 67(9):2577-2591.
[10] ANDRES C, MIRALLES C, PASTOR R. Balancing and scheduling tasks in assembly lines with sequence-dependent setup times[J]. European Journal of Operational Research, 2008, 187(3):1212-1223.
[11] ZACHARUA P T, NEARCHOU A C. A population-based algorithm for the bi-objective assembly line worker assignment and balancing problem[J]. Engineering Applications of Artificial Intelligence, 2016, 49(3):1-9.
[12] 李明,唐秋华,席忠民,等. 基于多层规划的单边多目标装配线平衡调度模型[J]. 系统工程理论与实践, 2011, 31(11):2185-2190. LI Ming, TANG Qiuhua, XI Zhongmin, et al. One-sided multi-objective assembly line balancing model based on multi-layer programming[J]. System Engineering Theory and Practice, 2011, 31(11):2185-2190.
[13] 韩煜东,董双飞,谭柏川. 基于改进遗传算法的混装线多目标优化[J]. 计算机集成制造系统, 2015, 21(6):1476-1485. HAN Yudong, DONG Shuangfei, TAN Baichuan. Multi-objective optimization for mixed-model assembly line balancing problem based on improved genetic algorithm[J]. Computer Integrated manufacturing Systems, 2015, 21(6):1476-1485.
[14] PAJOUTAN M, GOLMOHAMMADI A, SEIFBARGHY M. CMS scheduling problem considering material handling and routing flexibility[J]. The International Journal of Advanced Manufacturing Technology, 2014, 72(58):881-893.
[15] 高亮,张国辉,王晓娟. 柔性作业车间调度智能算法及其应用[M]. 武汉:华中科技大学出版社, 2012. GAO Liang, ZHANF Guohui, WANG Xiaojuan. Flexible job shop scheduling and application based on intelligence algorithm[M]. Wuhan:Huazhong University of Science & Technology Press, 2012.