Estimation of effectiveness of control system by quality with the use of tool of fuzzy logic

Abstract

The necessity for improving the efficiency assessment system for design products quality management system (QMS) in case of fuzzy input data was caused by a number of objective reasons. A high portion of subjective assessments and quality characteristics at QMS assessment complicates greatly an objective assessment of the system state with conventional methods. Therefore assessment of the system by means of fuzzy logics tools was proposed. In the course of the research an efficiency assessment model for QMS using fuzzy set theory was proposed: at the first stage of the research justified selection of mathematical apparatus for QMS efficiency assessment was made; at the second stage a system analysis of business process of several design companies was carried out for the purposes of system efficiency assessment and process group, processes and subprocesses of QMS were identified; at the third stage a system efficiency assessment model was built. At that, using a fuzzy clustering method, possible states of design products QMS were identified, hierarchical architecture of fuzzy inference system for assessment of QMS efficiency was determined, input, output and intermediate assessment data were described in terms of fuzzy logics. The contents of input and output indicators were determined. A membership function was assigned to each of them. Fuzzy system knowledge bases were developed with the assistance of the experts from design companies. Aggregation operation by min-max method was used for all 18 created blocks of production rules. A fuzzy model characterized by hierarchical pattern that allows to eliminate the subjective factor at determination of the weightage of some indicators when assessing QMS efficiency was developed in the course of the research. Assessment of intermediate efficiency indicators for processes and process groups is provided for better visualization and transparency of calculations. The use of the developed model improves adequacy of management decision-making in the field of quality management