Abstract

Many companies analyze field data to enhance the quality and reliability of their products and service. In many cases, it would be too costly and difficult to control their actions. The purpose of this paper is to propose a model that captures fuzzy events, to determine the optimal warning/detection of warranty claims data. The model considers fuzzy proportional-integral-derivative (PID) control actions in the warranty time series. This paper transforms the reliability of a traditional warranty data set to a fuzzy reliability set that models a problem. The optimality of the model is explored using classical optimal theory; also, a numerical example is presented to describe how to find an optimal warranty policy. This paper proves that the fuzzy feedback control for warranty claim can be used to determine a reasonable warning/detection degree in the warranty claims system. The model is useful for companies in deciding what the maintenance strategy and warranty period should be for a large warranty database.

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