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小批量生产过程VSI控制图经济设计 被引量:6

Economic design of VSI control chart for short-run production
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摘要 本文设计了一种面向小批量生产过程的变抽样区间(variable sample interval,VSI)控制图.根据参数的变化情况,变参数(variable parameter,VP)控制图被分为包括VSI控制图在内的几种不同类型的控制图.在带来成本节省的同时,VP控制图也增加了操作的复杂性;综合考虑成本节省和操作复杂性,VSI控制图被证明是最有效的一种控制图.经济设计控制图的核心是成本的最优化,传统经济图在设计时,没有考虑扰动发生的时刻对成本的影响.本文对过程状态进行重新划分,考虑了扰动发生的不同时刻对过程成本的影响;利用马尔科夫链和贝叶斯理论,构造了抽样区间随过程信息更新而变化的动态控制图.仿真结果表明:相比于已有的VSI控制图,本文设计的控制图更具有成本优势,因此具有更大的实用价值. This paper presents an economically designed VSI control chart for short-run production. According to the different parameter/parameters that changes/change over time, VP (variable parameter) control charts can be classified into several different types, including VSI control chart. While bringing cost savings, VP control chart adds up to the complexity of the operation. VSI chart has been reckoned one of the most effective and efficient sort of control chart considering both cost savings and operational complexity. The crux of the economic design of control chart is the optimization of cost, but the impact of the occurrence time of the disturbance on cost has not been taken into account in the traditional economic design of control charts. In this paper, process state is re-divided and the influence of the time of the disturbance occurrence on process cost is taken into consideration. Employing the Markov chain method and the Bayesian theory, we construct a dynamic control chart of which the sampling interval changes with the update of the process information. Simulation results show that compared to prior VSI control chart, control chart designed in this paper is more cost-advantageous and thus of more practical value.
出处 《系统工程理论与实践》 EI CSSCI CSCD 北大核心 2013年第5期1185-1191,共7页 Systems Engineering-Theory & Practice
基金 国家自然科学基金(70872091) 高等学校博士点专项基金(20090201110031)
关键词 小批量生产 贝叶斯过程控制 马尔科夫链 经济设计 short-run Bayesian process control Markov-chain economic design
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参考文献11

  • 1Castillo E D, Montgomery D C. A general model for the optimal economic design of charts used to control short or long run processes[J]. IIE Transactions, 1996, 28(3): 193-201.
  • 2Ho L L, Trindade A. Economic design of an X chart for short-run production[J]. International Journal of Production Economics, 2009, 120(2): 613-624.
  • 3Nenes G, Tagaras G. The economically designed two-sided Bayesian control chart[J]. European Journal of Operational Research, 2007, 183(1): 263-277.
  • 4Tagaras G, Nikolaidis Y. Comparing the effectiveness of various bayesian control charts[J]. Operations Research, 2002, 50(5): 878-888.
  • 5Park C, Reynolds M R. Economic design of a variable sampling rate chart[J]. Journal of Quality Technology, 1999, 31(4): 427-443.
  • 6Prabhu S S, Runger G C, Keats J B. An adaptive sample size chart[J]. International Journal of Production Research, 1993, 31(3): 2895-2909.
  • 7Marion R. Variable sampling interval control charts with sampling at fixed times[J]. IIE Transactions, 1996, 28(4): 497-510.
  • 8Bai D S, Lee K T. An economic design of variable sampling interval X control chart[J]. International Journal of Production Economics, 1998, 54(1): 57-64.
  • 9Tagaras G. Dynamic control charts for finite production runs[J]. European Journal of Operational Research, 1996, 91(1): 38-55.
  • 10Duncan A J. The economic design of X-bar charts when there is a multiplicity of assignable causes[J]. Journal of the American Statistical Association, 1971, 66(1): 107-121.

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  • 3IPCC. Climate change 2007:impacts, adaptation and vulnera bility:contribution of working group II to the fourth assess ment report of the intergovernmental panel on climate change [ M]. Cambridge, UK :Camhridge University Press, 2007.
  • 4LIU M, LIU C, XING L, et al. Study on a tolerance grading allocation method under uncertainty and quality oriented for remanufactured parts[J ]. The International Journal of Ad- vanced Manufacturing Technology, 2013: 1-8. DOI: 10. 1007/ s00170-013-4826-z.
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  • 9BURNHAM A, HAN J, CLARK C E, et al. Life-cycle greenhouse gas emissions of shale gas, natural gas, coal, and petroleum[J]. Environmental Science and Technology,2012, 46(2) : 619-627.
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