International Journal of Industrial Engineering & Production Management

 Shewhart charts are the main tools for statistical process control. They are used for detecting assignable causes which affect quality of process output. From them, X and MR charts are two univariate control charts for monitoring mean and variation of measurable quality characteristics. The main drawbacks of these charts are: weakness of X chart against non-normal distribution of process data, autocorrelation of consecutive MR values, and inability of MR chart in detecting decrease in process variation. These drawbacks have declined their effectiveness. This paper presents a simple method for monitoring two parameters of normal distribution, based on fuzzy logic, resolving above drawbacks. The proposed method can detect non-random patterns of the process data. Here a fuzzy expert system is developed to assess individual measurements. This results in considerable improvement in decreasing out-of-control average run length versus the traditional control charts. Moreover, performance of fuzzy control chart for recognizing unnatural process behaviors has investigated using Mont-Carlo simulation and advantages of this novel method have been investigated.