使用DINNA图求解问题的5个维度:双Ishikawa和Naze-Naze分析

M. Hamoumi, A. Haddout, M. Benhadou
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引用次数: 0

摘要

基于完美是神圣标准的原则,过程管理一方面是为了实现卓越(近乎完美),另一方面是避免不完美。换句话说,卓越运营(EO)是一种方法,当严格使用时,旨在最大限度地提高性能。因此,要达到这样的绩效水平,掌握解决问题仍然是必要的。无论是在解决长期问题的持续改进中(KAIZEN、DMAIC、精益六西格玛…),还是在解决偶发缺陷的过程中(8D、PDCA、QRQC…),我们都可以使用许多工具。然而,这些方法通常使用相同的基本工具(石川图、5为什么、原因树…)来识别潜在原因和根本原因。这导致了三个层次的原因:发生、未检测和系统。研究表明,DINNA图[1]是一个有效的过程,它将石川图和5为什么方法联系起来,以确定根本原因并避免复发。如果两个具有相似技能的工作组分别分析同一问题,最终目标是实现相同的结果。为了实现这一目标,需要始终如一地应用稳健的方法。因此,我们谈论的是5个维度;发生、未检测、系统、有效性和效率。因此,本文提供了一种既有效又高效的解决方案,帮助工业问题解决的从业者避免错过真正的根本原因,并在做出错误决定后节省成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The 5 Dimensions of Problem Solving using DINNA Diagram: Double Ishikawa and Naze Naze Analysis
Based on the principle that perfection is a divine criterion, process management exists on the one hand to achieve excellence (near perfection) and on the other hand to avoid imperfection. In other words, Operational Excellence (EO) is one of the approaches, when used rigorously, aims to maximize performance. Therefore, the mastery of problem solving remains necessary to achieve such performance level. There are many tools that we can use whether in continuous improvement for the resolution of chronic problems (KAIZEN, DMAIC, Lean six sigma…) or in resolution of sporadic defects (8D, PDCA, QRQC ...). However, these methodologies often use the same basic tools (Ishikawa diagram, 5 why, tree of causes…) to identify potential causes and root causes. This results in three levels of causes: occurrence, no detection and system. The research presents the development of DINNA diagram [1] as an effective and efficient process that links the Ishikawa diagram and the 5 why method to identify the root causes and avoid recurrence. The ultimate objective is to achieve the same result if two working groups with similar skills analyse the same problem separately, to achieve this, the consistent application of a robust methodology is required. Therefore, we are talking about 5 dimensions; occurrence, non-detection, system, effectiveness and efficiency. As such, the paper offers a solution that is both effective and efficient to help practitioners of industrial problem solving avoid missing the real root cause and save costs following a wrong decision.
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