Optimizing supply chain management using fuzzy approach

Abstract

Purpose The purpose of this paper is to propose a fuzzy multi‐criteria decision‐making procedure and it is applied to find a set of optimal solution with respect to the performance of each supplier. This method with the use of Monte Carlo simulation produces overall desirability level less imprecise and more realistic than those of the conventional QFD methods for engineering design evaluation. Design/methodology/approach A few responses obtained from customers are simulated using a triangular fuzzy QFD algorithm, Monte Carlo simulation and a multi‐objective model to optimise the total user preferences. Findings The proposed approach provides decision‐making with an optimal solution less imprecise in a QFD‐based collaborative product design environment. Research limitations/implications The proposed approach depends on the few responses and the random numbers derived from simulation. The random numbers need to be used after passing them through random number testing methods. The responses obtained from the customer are considered to be genuine and original. Originality/value The triangular fuzzy, Monte Carlo simulation and multi‐objective optimisation are embedded into QFD environment to make the decisions less imprecise than that of conventional QFD and it is tested for a case study problem. It definitely helps the managers in a collaborative product design environment.

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