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AN APPROACH OF FUZZY LOGIC EVALUATION AND CONTROL IN SPC

机译:SPC中的模糊逻辑评估与控制方法

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Quality control plays an important part in most industrial systems. Its role in providing relevant and timely data to management for decision-making purposes is vital. A method that uses statistical techniques to monitor and control product quality is called statistical process control(SPC), where control charts are test tools frequently used for monitoring the manufacturing process. Engineers or managers can evaluate an abnormal process by using SPC zone rules in control charts. In the conventional use of the zone rules the user is only able to determine whether or not the process is out of control. What action should be taken to adjust the process is uncertain and is evaluated based on knowledge of the system and past experiences. This paper explores the integration of fuzzy logic and control charts to create and design a fuzzy-SPC evaluation and control(FSEC) method based on the application of fuzzy logic to the SPC zone rules. A simulation program implementing FSEC was written in Borland C++5.0 and simulation results were obtained and analysed. The abnormal processes simulated were automatically adjusted for each of the zone rules tested and showed an improved performance after the control action , thus confirming the merit of technique as a special method with the specific numerical control action based on a quality evaluation criterion.
机译:质量控制在大多数工业系统中起着重要的作用。它在为决策提供相关及时的数据给管理层中的作用至关重要。使用统计技术监视和控制产品质量的方法称为统计过程控制(SPC),其中控制图是经常用于监视制造过程的测试工具。工程师或管理人员可以通过使用控制图中的SPC区域规则来评估异常过程。在区域规则的常规使用中,用户只能确定过程是否失控。尚不确定应采取什么措施来调整过程,该不确定性是根据系统知识和以往经验进行评估的。本文探讨了模糊逻辑与控制图的集成,以基于模糊逻辑对SPC区域规则的应用来创建和设计模糊SPC评估与控制(FSEC)方法。用Borland C ++ 5.0编写了一个实现FSEC的仿真程序,并获得并分析了仿真结果。对于测试的每个区域规则,模拟的异常过程均会自动进行调整,并在控制动作后表现出改进的性能,从而基于质量评估标准确认了该技术作为具有特定数控动作的特殊方法的优点。

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