Designing an applied model of statistical process control (SPC) by fuzzy mode and middle fuzzy and comparing its results with classical method case study: Dadash Baradar Ind. Co.

Statistical Process Control (SPC) is a powerful set of problem-solving tools that stabilize production processes and increase the ability to produce high quality product. Classic control diagrams, using precise and definite data, place production processes into two groups: under control or out of control; while Fuzzy sets by defining continuous membership functions and using ambiguous, indefinite data, triangular and trapezoidal Fuzzy numbers, classify into these categories: under control, relatively under control, relatively out of control and out of control which express the quality level of the product more realistically.

This research is an applied and descriptive research with the aim of designing an applied model of Statistical Process Control by Fuzzy Mode and Middle Fuzzy and comparing its results with Classical Method in Dadash Baradar Ind. Co. in Tabriz. This method of data collection to run the model follows the sampling system at the inspection station and is in the form of 30 samples of 50 chocolates.

According to the seven defects of chocolate, which include: color, taste, acidity, sugar blossom, tissue factors and foreign substances, the nature of the produced chocolate was determined. In the Classical Method, 28 cases under control and only 2 cases out of control were identified, but in the study with Fuzzy SPC Method, 20 samples under control, 4 samples relatively under control, 4 samples relatively out of control and 2 samples were out of control.

Research results shows the sensitivity of the Fuzzy SPC Method compared to the Classical Method; as a result, identifying process changes is more accurate and faster, and accordingly practical suggestions have been provided to the company.