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Utilizing the information theory of entropy to solve an off-line inspection problem

机译:利用熵信息论解决离线检测问题

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This study presents an off-line inspection problem for a batch produced from a process subject to random failures and exhibiting manufacturing variations. The objective of this paper is to develop an inspection policy in which units should be inspected in a particular order to find the transition unit in the batch under a required confidence level. This study develops an algorithm to compute the expected number of inspections. This approach uses the information theory of entropy to select an un-inspected unit to be inspected, and effectively minimizes the uncertainty of the transition unit in the production batch. A numerical example illustrates the proposed off-line inspection policy, and the effects of model parameters on the expected inspection number are investigated. The numerical example in this study indicates that full inspection is required when the required confidence level is one or the process has larger manufacturing variations.
机译:这项研究提出了离线检查问题,该问题是由随机遭受故障并显示出制造差异的过程所生产的批次产生的。本文的目的是制定一种检查策略,在该策略中,应按特定顺序检查单元,以在所需的置信度下找到批次中的过渡单元。这项研究开发了一种算法来计算预期的检查次数。该方法使用熵信息论来选择要检查的未检查单元,并有效地最小化了生产批次中过渡单元的不确定性。数值算例说明了提出的离线检验策略,并研究了模型参数对预期检验次数的影响。本研究中的数值示例表明,当所需置信度为1或过程具有较大的制造差异时,需要进行全面检查。

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