Construe of statistical process control charts with fuzzy logic and application in a yarn manufactory

Statistical process control (SPC) methods, the difference in competition for entrepreneurs wishing to open, more efficient, less time-consuming, less costly, more accurate results approaching, supplemented with fuzzy logic, which is an artificial intelligence techniques. The production process is very complex, and if there is enough information about this opinion to be given in such cases, the people and the value judgment of fuzzy logic. Fuzzy control charts to detect errors from both processed under control, although the system is out of control as well as distinguish between errors indicating that provides smooth operation of the system.In the first part of the study, detailed information about SPC and it?s techniques are given. Fuzzy logic and it?s application areas and its historical development are given detailed information. In the second part are given work of literature. In the third section, a yarn spinning machine in the spinning mill, process capability analysis for the number of yarn were examined. The adequacy of the business process Cp(2.79)>(1.33) is sufficient to show the process and Cpk(2.79)>(1.33) with the values of the process specifications are met. In the section fourth, the 8 inputs and 1 output membership functions for the data (30 Ne) 8-by-step within the limits of ± 3? range (± Out Off, ± A, ± B, ± C) were selected. System on the basis of Nelson?s 8 of the rules prepared to table out of control and monitoring of the process that determines under rule 22, and fuzzy control system processed with the method of Mamdani. Method of centroid in defuzzification stage of selecting the conclusions. In the fifth section, the number control system have been followed with thread prosesininde thread and their results. Yarn process in the textile sector on the basis of control charts are and suggested created which have been made available in a modular system, which use with the system established in all sectors. Fuzzy logic can be used in the interpretation of control tables and spinning business process control also brought up as appropriate.