标题: 制程能力指标应用于低不良率制程的工具汰换问题
Tool Replacement Management Policy for Processes with Low Fraction Defective
作者: 徐雅甄
Ya-Chen Hsu
彭文理
W. L. Pearn
工业工程与管理学系
关键字: 可归属原因;临界值;最小平方法;制程能力指标;工具汰换;工具磨损;Assignable cause;Critical value;Ordinary least square estimate;Process capability index;Tool replacement;Tool wear
公开日期: 2006
摘要: 在产品制造过程中,工具磨损之监控是一个非常重要的议题。由于机具设备持续运转制造产品,工具将逐渐产生磨损的现象。通常工具磨损发生于生产过程中,包含有铣床、钻床、车床等制程。由于此种磨损是无法避免的,因此必须对工具作有效的监控以维持产品品质。在工具管理上,其中一个很重要的议题就是工具汰换策略。过早做工具汰换会增加生产之成本,相对地,太晚作工具汰换则会导致不良的生产品质。因此如何找出最佳工具汰换时机,俨然成为一个重要的课题。制程能力分析是对制程的产出绩效提供一个数值的衡量方法,根据这些数值,生产者可作为衡量制程能力好坏及制程是否达到对产品品质要求的重要标准。实际上;无论是消费者订购产品或是工程师制造生产时,都会事先预设一个制程能力指标的最小值。若因严重的工具磨损而无法达到预设之制程能力的最小值,则会认为制程能力是不够的并且开始作工具的汰换。由于制程能力分析可以被应用在决定汰换工具的最佳时间点,而且此方法对于在低不良率的制程下维护低生产成本和高品质产品而言是特别有效的。然而,必须要注意到的是,在计算制程能力时应该考虑到可归属原因的影响。工具磨损正是制程里一个非常普遍的可归属原因之一,当我们在进行制程能力的运算时应该将此项因素考量进来,否则所得到的制程能力值可能会产生严重的偏差,所以希望能透过修正后的制程能力指标之运用,让我们正确的估算制程能力并且找出合适的工具汰换时机。因此,在本文中,我们首先提出一个透过 Cpk (被视为良率基础的指标)来找出工具汰换的最佳时间点之方法。接着对于单边规格制程,也提出单边指标 CPU 和 CPL 的应用去找出最佳工具汰换的时间点。因为 Cpmk 指标结合三个基本的指标 Cp , Cpk 和 Cpm 的优点。所以,我们也提出以 Cpmk 找出最佳工具汰换时间点的分析方法。在考虑制程能力为动态地改变时,我们将探讨这些制程能力指标之估计式及推导出各个指标的统计抽样分配。此外;并提供在低不良率要求下之生产制程,如何寻找出工具汰换最佳时间点之程序。因此操作人员将可以根据所提出的方法来判断他们的制程是否达到所设定的制程能力水准,而作出正确的工具汰换决策。最后为说明其应用,我们将会列举三个例子以完整地说明整个工具汰换之作业程序。
Tool wear control is an important component to many manufacturing factories for producing quality products. As the manufacturing activities keep on going, the tool wears gradually. Tool wear occurs in production process involving milling machines, drilling machines, lathes, etc. While such wear is unavoidable, tool wear must be controlled to maintain product quality and efficient tool utilization. One important issue for tool wear control is the tool replacement policy. Early tool replacement increases the production cost. Overtime tool replacement, however, results in poor production quality. Consequently, detecting suitable time for tool replacement operation becomes essential. Process capability analysis is to provide numerical measures for determining whether a process is capable and meets the required quality standards. In practice, a minimal capability requirement would be preset by the customers/engineers. If the prescribed minimum capability fails to be met due to severe tool wear, one would conclude that the process is incapable and a tool replacement activity must be initiated. Process capability analysis is applied to determine the optimal tool replacement time. The proposed approach is useful, particularly, for low fraction defective processes requiring low production cost and stringent quality standards. Process capability can be calculated accurately if the data contains no assignable cause variation. Tool wear, however, is a dominant and irremovable component in many machining processes, which is a systematic assignable cause. The ordinary measures of process capability are inaccurate because the process data is contaminated by the assignable cause variation. In order to determine the optimal tool replacement time to maintain minimal product quality, conventional capability calculation must be modified. In this dissertation, we first proposed a method based on capability index Cpk, a yield-based index, to find the appropriate time for tool replacement. For unilateral processes, a procedure for finding the appropriate tool replacement time based on the one-sided process capability index CPU (or CPL) is obtained. The index Cpmk combines the merits of the three basic indices Cp , Cpk and Cpm. Therefore, we also present an analytical approach using Cpmk to find optimal tool replacement time. Considering process capability changes dynamically, the estimators of these indices are investigated. Closed form of the exact sampling distribution is derived. An effective tool management procedure for finding optimal tool replacement time is presented for processes with low fraction defective to meet manufacturing requirement. The practitioners can use the proposed method to determine whether their process meets the preset capability requirement, and make reliable decisions regarding the tool replacement time. For illustration purpose, three application examples involving tool wear are presented.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT009333812
http://hdl.handle.net/11536/79520
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