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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:监测模糊质量特征的模糊均值和范围控制图:使用鸡块的食品行业案例研究

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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:组织必须改善或至少保持其产品质量,才能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必然质量改进计划。在当前的研究中,开发了模糊的平均值和范围控制图来监视生产过程。模糊控制图还可以处理由于模糊,歧义和/或不完整信息导致的不确定性,以及由于质量特征测量中的随机性而导致的固有不确定性。拟议的模糊控制图通过在鸡块生产公司的案例研究进行了验证,方法是从工厂车间收集数据并将其与工厂已经用于监控过程的传统Shewhart控制图进行比较。结果表明,与传统的Shewhart控制图相比,拟议的模糊控制图可以更准确地检测生产过程中的异常偏移,因为它们使用了来自过程的更多信息。所提出的方法通过提高质量和提高生产率为公司带来了许多好处。

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