Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement—Intuitionistic Fuzzy Sets and Genetic Algorithm Approach

The aim of this research is to propose a hybrid decision-making model for evaluation and selection quality methods whose application leads improved reliability manufacturing in the process industry. Evaluation failures determination their priorities are based on failure mode effect analysis (FMEA), which widely used framework practice combining with triangular intuitionistic fuzzy numbers (TIFNs). all-existing uncertainties relative importance risk factors (RFs), values, applicability methods, as well implementation costs described by pre-defined linguistic terms modeled TIFNs. stated rubber knapsack problem decomposed into subproblems certain number solution elements. found using genetic algorithm (GA). verified through case study real-life data originating from significant organizations one region. It shown that proposed highly suitable tool improving small medium enterprises (SMEs)