Throughput optimization for an imperfect production system with queue time constraints
-
摘要:
针对某些生产系统存在等待时间约束及设备劣化引起产品质量损失这2个问题,构建了系统的缓冲区控制和预防性维护的联合优化模型。首先,利用伽马过程对下游瓶颈工作站的劣化过程进行建模,并考虑由于其状态劣化引起的产品质量损失;其次,在此基础上,将工件的到达、中间缓冲区及下游工作站的加工过程视为一排队系统,引入M/G/1/K排队模型分别求解了在制品(WIP)被阻塞和超出等待时间约束的概率;最后,以最大化系统的“有效产出”为目标,对系统的预防性维护和缓冲区控制作了联合优化。数值实例表明:本文所提模型是切实、有效的,对带等待时间约束的生产系统的缓冲区控制、预防性维护以及产出提高具有一定的指导意义。
Abstract:To efficiently solve the problems of queue time constraints and quality loss caused by machine degradation during production activities, a joint optimization mathematical model considering both preventive maintenance and the control of the buffer capacity was constructed in this paper. First, gamma process was introduced to model the degradation of the downstream bottleneck station, and the quality loss caused by its degradation was also considered. Second, based on the model mentioned above, we treated the arrival of workpieces, the intermediate buffer and the working process of downstream station as a queuing system and obtained the probability of work in process (WIP) blocking and exceeding the queue time constraints using M/G/1/K queuing model. Finally, with the objective function of maximizing the "effective throughput", we jointly explored the optimization of the threshold of preventive maintenance and the capacity of the intermediate buffer. Numerical example shows that the proposed model is practical and effective, which has certain instructive significance to the buffer capacity control, preventive maintenance and throughput improvement for those imperfect production systems with queue time constraints.
-
Key words:
- machine degradation /
- gamma process /
- quality loss /
- queue time constraints /
- buffer
-
表 1 不同的[DP, K]对应的系统有效产出
Table 1. Effective throughput of systems under different combinations of [DP, K]
K/个 有效产出/个 DP=110μm DP=115μm DP=120μm DP=125μm DP=130μm DP=135μm 6 3365 3378 3386 3393 3400 3393 7 3378 3390 3398 3405 3412 3406 8 3365 3377 3386 3393 3399 3392 9 3346 3358 3367 3373 3380 3372 10 3328 3340 3348 3355 3361 3353 11 3312 3324 3332 3338 3344 3336 12 3299 3311 3319 3325 3331 3323 13 3290 3301 3309 3316 3321 3313 14 3283 3295 3303 3309 3314 3306 -
[1] TU Y M, CHEN H N.Capacity planning with sequential time constraints under various control policies in the back-end of wafer fabrications[J].Journal of the Operational Research Society, 2010, 61(8):1258-1264. doi: 10.1057/jors.2009.36 [2] ONO A, KITAMURA S, MORI K.Risk based capacity planning method for semiconductor fab with queue time constraints[C]//Proceedings of IEEE International Symposium on Semiconductor Manufacturing, 2006.Piscataway, NJ:IEEE Press, 2006:49-52. [3] WU K.Classification of queueing models for a workstation with interruptions:A review[J].International Journal of Production Research, 2014, 52(3):902-917. doi: 10.1080/00207543.2013.843799 [4] WU C H, LIN J T, CHIEN W C.Dynamic production control in a serial line with process queue time constraint[J].International Journal of Production Research, 2010, 48(13):3823-3843. doi: 10.1080/00207540902922836 [5] WU C H, LIN J T, CHIEN W C.Dynamic production control in parallel processing systems under process queue time constraints[J].Computers & Industrial Engineering, 2012, 63(1):192-203. http://www.sciencedirect.com/science/article/pii/S0360835212000496 [6] SHI C, GERSHWIN S B.Part waiting time distribution in a two-machine line[J].IFAC Proceedings Volumes, 2012, 45(6):457-462. doi: 10.3182/20120523-3-RO-2023.00114 [7] WU K, ZHAO N, GAO L, et al.Production control policy for tandem workstations with constant service times and queue time constraints[J].International Journal of Production Research, 2016, 54(21):6302-6316. doi: 10.1080/00207543.2015.1129468 [8] PENG H, FENG Q, COIT D W.Reliability and maintenance modeling for systems subject to multiple dependent competing failure processes[J].ⅡE Transactions, 2010, 43(1):12-22. doi: 10.1080/0740817X.2010.491502?src=recsys&journalCode=uiie20 [9] 王严, 马麟, 文佳, 等.考虑保障设备故障的装备维修保障模型[J].北京航空航天大学学报, 2012, 38(1):123-127. http://bhxb.buaa.edu.cn/CN/abstract/abstract12187.shtmlWANG Y, MA L, WEN J, et al.Maintenance-support model of materiel considering support equipment failure[J].Journal of Beijing University of Aeronautics and Astronautics, 2012, 38(1):123-127(in Chinese). http://bhxb.buaa.edu.cn/CN/abstract/abstract12187.shtml [10] 张卓琦, 吴甦, 李斌锋.考虑故障相关的两部件系统机会维修策略[J].清华大学学报(自然科学版), 2012, 52(1):122-127. http://www.cnki.com.cn/Article/CJFDTOTAL-QHXB201201025.htmZHANG Z Q, WU S, LI B F.Opportunistic maintenance policy for a two-unit system with failure interactions[J].Journal of Tsinghua University(Science and Technology), 2012, 52(1):122-127(in Chinese). http://www.cnki.com.cn/Article/CJFDTOTAL-QHXB201201025.htm [11] 翟子青. 基于随机过程的蒸汽发生器传热管腐蚀失效寿命分析[D]. 上海: 上海交通大学, 2011: 34-38.ZHAI Z Q.Stochastic modeling for the degradation of steam generator tubes due to pitting corrosion[D].Shanghai:Shanghai Jiao Tong University, 2011:34-38(in Chinese). [12] VAN NOORTWIJK J M.A survey of the application of gamma processes in maintenance[J].Reliability Engineering & System Safety, 2009, 94(1):2-21. http://www.sciencedirect.com/science/article/pii/S0951832007001111 [13] CHENG G, ZHOU B, LI L.Joint optimisation of buffer size and preventive maintenance for a deteriorating upstream machine[J].International Journal of Systems Science:Operations & Logistics, 2015, 2(4):199-210. doi: 10.1080/23302674.2015.1018366 [14] SUN J W, XI L F, DU S C, et al.Tool maintenance optimization for multi-station machining systems with economic consideration of quality loss and obsolescence[J].Robotics and Computer-Integrated Manufacturing, 2010, 26(2):145-155. doi: 10.1016/j.rcim.2009.07.005 [15] ZHOU B, LIU Z.Optimizing preventive maintenance:A deteriorating system with buffers[J].Industrial Management & Data Systems, 2016, 116(8):1719-1740. doi: 10.1108/IMDS-01-2016-0026