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  • 标题:Absorbing Markov Chain Models to Determine Optimum Process Target Levels in Production Systems with Dual Correlated Quality Characteristics
  • 本地全文:下载
  • 作者:Mohammad Saber Fallah Nezhad ; Hasan Hosseini Nasab
  • 期刊名称:Pakistan Journal of Statistics and Operation Research
  • 印刷版ISSN:2220-5810
  • 出版年度:2012
  • 卷号:8
  • 期号:2
  • 页码:205-212
  • DOI:10.1234/pjsor.v8i2.268
  • 语种:English
  • 出版社:College of Statistical and Actuarial Sciences
  • 摘要:For a manufacturing organization to compete effectively in the global marketplace, cutting costs and improving overall efficiency is essential. A single-stage production system with two independent quality characteristics and different costs associated with each quality characteristic that falls below a lower specification limit (scrap) or above an upper specification limit (rework) is presented in this paper. The amount of reworks and scraps are assumed to be depending on the process parameters such as process mean and standard deviation thus the expected total profit is significantly dependent on the process parameters. This paper develops a Markovian decision making model for determining the process means. Sensitivity analyzes is performed to validate, and a numerical example is given to illustrate the proposed model. The results showed that the optimal process means extremely effects on the quality characteristics’ parameters.
  • 关键词:Markov Chain, Process Mean, Bi-variate Normal Distribution
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