Nowadays statistical control process plays an important role in quality control of products. So wide variety of methods are utilized to do so. But since the most percentage of available information in the discrete control charts are verbal terms, fuzzy and vague ,in most cases it is difficult for us to refine them into the quantitative data. Thus in this article we are to change these verbal data into the quantitative data by fuzzy logic and furthermore to provide new method to control discrete process.
In this research that has been executed in the Irankhodroo, Mehvarsazan Company, fuzzy control charts suggested by Rose & Wang examined. Results achieved from this research represent when we have to use verbal variables, fuzzy control charts present clearer and better results than classic control charts. This method particularly when the process is out of control will give a faster alert and will report existence of a disorder in the process. The number of verbal terms used for defining quality level of product influence on accuracy and sensitivity of control charts and the more verbal terms used for defining quality level of product , the less probability of second-type error(?) or stretching a point in control limit sides(LCL & UCL).
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