使用六西格玛的Dmaic方法最小化玻璃容器瓶生产的低质量成本:一个瓶子和玻璃股份公司的案例研究

Besufekad Legesse, Sisay Geremew
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引用次数: 1

摘要

即使有许多工具可用于减少缺陷,六西格玛的DMAIC模型是一个工具,如果应用适当的方法,可以显著减少缺陷。在这项工作中,缺陷的减少是使用DMAIC模型作为手段来实现的。在定义阶段,主要的产品类型和缺陷是通过头脑风暴、供应商-输入-过程-输出-客户图、帕累托图以及失效模式和影响分析来设计和识别的。因此,玻璃制造工艺中选择了玻璃珠直径差、玻璃分布不均匀的玻璃。在测量阶段,采集和观察数据以显示过程的行为。应用控制图、能力分析和六包能力分析来了解工艺条件。根据前期所得数据,利用鱼骨图进行了阶段分析。该图说明了需要改进的根本原因。在分析阶段确定了根本原因即工艺参数后,采用田口技术对工艺参数进行优化,进入改进阶段。田口分析确定了决定过程输出因素的主要因素。在确定最优值后,收集结果以检验其有效性。这些改进将每百万机会的缺陷(DPMO)从149,997.8减少到50,000,并将不良质量成本从每天的ETB 429,540.3减少到ETB 143,178,结果表明与以前的产量相比,缺陷减少了30%。
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Minimizing Costs of Poor Quality for Glass Container Bottles Production Using Six Sigma’s Dmaic Methodology: A Case Study in a Bottle and Glass Share Company
Even if many tools are available to reduce defect, six sigma’s DMAIC model is one of a tool which significantly reduce defect if it is applied with appropriate methodology. In this work defect reduction is achieved using DMAIC model as a means. At the define phase major product types and defects are crafted and identified by using brainstorming, supplier-input-process-output-customer diagram, Pareto Diagram and failure mode and effect analysis. So that poor bead diameter and uneven glass distribution have been selected from the glass making processes. At the measuring phase data has taken and observed to display how the process behaves. Control charts, capability analysis and six pack capability analysis are applied to understand the process condition. Based on the data obtained from the preceding phase analysis undertaken using Fishbone diagram. The graph illustrates the root causes that are in need to improve. After the analysis phase identified the root causes i.e. process parameters, the improvement phase has held by using Taguchi technique to optimize the process parameters. The Taguchi analysis identified the main factors which determine the processes output factors. After the optimum value is decided the result is collected to check its effectiveness. these improvements decreased defects per million opportunities (DPMO) from 149,997.8 to 50,000 and reduced poor quality cost from ETB 429,540.3 to ETB 143,178 per day and the result showed that defect has reduced by 30% compared with the previous output.
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