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Analyzing fuzziness in product quality reliability information flow during time-driven product-development-process

机译:在时间驱动产品开发过程中分析产品质量和可靠性信息流动中的模糊性

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This paper provides a different angle to look at quality and reliability (Q&R) problem prediction in a time-driven product-development-process (PDP) where the Q&R information is highly uncertain. Through a case study, it is demonstrated that many of the critical Q&R problems in such a product development cannot be predicted due to highly fuzzy Q&R information. Therefore, a new tool, Reliability and Quality Matrix (RQM), was developed to overcome this difficulty. It is shown that RQM can not only quantitatively indicate the severity level of an identified Q&R problem but also reflect on its associated uncertainty level due to fuzzy Q&R information. RAM was developed as an enhancement of Failure Mode Effect Analysis (FMEA) or Quality Function Deployment (QFD). If the quality of the input information is very good, RQM then presents only the results from FMEA or QFD. However, if uncertainty in the input information is obviously high, RQM can act as uncertainty/fuzziness reduction tool to strengthen the weakness of FMEA and QFD when dealing with fuzzy information.
机译:本文提供了一种不同的角度,以查看时间驱动的产品开发过程(PDP)中的质量和可靠性(Q&R)问题预测,其中Q&R信息非常不确定。通过案例研究,证明在这种产品开发中的许多关键Q&R问题无法预测由于高度模糊的Q&R信息。因此,开发了一种新的工具,可靠性和质量矩阵(RQM)以克服这种困难。结果表明,RQM不仅可以定量地指示所识别的Q&R问题的严重性级别,而且还反映了由于模糊Q&R信息引起的相关的不确定性水平。 RAM被开发为增强失败模式效果分析(FMEA)或质量函数部署(QFD)。如果输入信息的质量非常好,则RQM只能呈现FMEA或QFD的结果。然而,如果输入信息中的不确定性显然很高,则RQM可以充当不确定/模糊降低工具,以加强在处理模糊信息时进行FMEA和QFD的弱点。

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