This paper presents the case study of fuzzy statistical process control which has been simulated for variable and discontinuous production within a particular time frame in a key manufacturing work-shop. In order to reduce waste production and increase productivity, dimensional inspection from raw product is categorized into three groups: product of type A, product of type B, and discard. In first part, the appearance characteristics of product is defined as fuzzy membership function as the input of the system in order to allocate the output obtained from fuzzy inference of product to one of the three quality levels. Afterwards, each quality level is assigned to its own group by means of Monte Carlo simulation techniques. In the second part, with fuzzy development of a multinomial p chart, the production process is illustrated as a control chart within the particular period of time.

The aim of this paper is to integrate fuzzy approach into statistical process control in order to provide a comprehensive description of an operator’s performance. To this end, all influential factors in quality of a product are simultaneously controlled to assess the performance in each working day. Then a fuzzy x̄ chart is used for statistical modeling process during a month. This paper shows that the fuzzy controller chart can provide a good indication to evaluate a person's work performance.