Methodology for Constructing Fuzzy Individual and Moving Range Control Chart

Abstract

The main importance of the control charts is to process the error occurring in the production processes before it occurs. In this paper, single-sample fuzzy moving range control charts will be applied. One of the main problems facing this type of application is the data fuzzing process, that is, the uncertainty of the production process and measurements in the data environment. Choosing the appropriate alpha-fuzzy value (which is used to convert data from crisp values into fuzzy data) depends on experts in the production institute. In this work, the alpha-fuzzy value was chosen based on the arithmetic average of the process, the target average, and the type of production process as well. The wire drawing process was applied in this research as a case study to apply the proposed methodology, a code of the MATLAB-2020 program was applied in the calculation and drawing operations, and the results were compared with the Minitab-2021 program, which draws the traditional control charts. The proposed methodology was applied on a wire drawing process for copper and aluminum wires to control the diameter of the wires. The results showed that the methodology used in the paper was efficient in choosing the right alpha-fuzzy as long as it did not cause high change in the standard deviation of the process. The fuzzy control charts were more flexible and accurate than the traditional control charts, observation 17 of the aluminum wire was out-of-control in the traditional control chart while it was under control in the fuzzy control chart.