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Fuzzy mean and range control charts for monitoring fuzzy quality characteristics: A case study in food industries using chicken nugget

机译:模糊均值和范围控制图,用于监测模糊品质特征 - 以鸡块食品工业为例

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Organizations must improve or at least maintain the quality of their products to be competitive in today's market. Thus, developing a new approach which could utilize more information from the production process has become an inevitable quality improvement program for each organization. In current study, a fuzzy mean and range control charts were developed to monitor the production process. Fuzzy control charts could handle the uncertainty due to vagueness, ambiguity and/or incomplete information in addition to the inherent uncertainty due to randomness in quality characteristic measurements. The proposed fuzzy control charts were validated through a case study at the chicken nugget production company by collecting data from the factory floor and comparing it to the traditional Shewhart control charts which have been already applied by the factory for monitoring the process. The results reveal that the proposed fuzzy control charts could detect abnormal shifts in the production process more accurately than the traditional Shewhart control charts, as they had used more information from the process. The proposed approach has several benefits for the company by improving the quality and increasing the productivity.
机译:组织必须完善或至少维护其产品质量在当今市场上具有竞争力。因此,开发一种可以利用生产过程中更多信息的新方法已成为每个组织的不可避免的质量改进计划。在目前的研究中,开发了一种模糊均值和范围控制图来监测生产过程。除了由于质量特征测量中的随机性而导致的隐形,歧义和/或不完整的信息,模糊控制图可以处理不确定性。通过收集来自工厂地板的数据并将其与工厂已经应用的传统棚顶控制图进行比较,通过鸡块生产公司进行案例研究验证了拟议的模糊控制图。结果表明,所提出的模糊控制图可能比传统的牧草控制图更准确地检测生产过程中的异常变化,因为它们已经使用了该过程的更多信息。通过提高质量和提高生产力,该拟议的方法对公司有几个好处。

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