International Journal of Multimedia and Ubiquitous Engineering Vol.12, No.1 (2017), pp.79-86 http://dx.doi.org/10.14257/ijmue.2017.12.1.07 ISSN: 1975-0080 IJMUE Copyright ⓒ 2017 SERSC Identifying Effectiveness of Supply Chain Management Using Fuzzy Customer Feedback System Sayed Sayeed Ahmad 1 , Harsh Purohit 2 and Manuj Darbari 3 1 College of Engineering and Computing, Al Ghurair University, Dubai, UAE, E- mail: sahmed@agu.ac.ae 2 Faculty of Management Studies, WISDOM, Banasthali Vidyapith, Rajasthan, E- mail: 3 Computer Science & Engineering Department, BBD University, Lucknow, E- mail: Abstract The product quality is an important aspect that directly affects the supply chain management. The production of low quality products in the market leads to failure in their operational mode. This hurts the trust of customers on the company and creates a bad image of company in the market. The continuous degrade in the quality may lead to a big financial loss in the company. In this paper an approach related to the generation of a index to a particular company that can be used further in the supply chain management strategy change. The proposed system is implemented using Fuzzy System using FISPro, open access software tool. Keywords: Fuzzy Sets, Guaje, Supply Chain Management, Product Quality 1. Introduction Supply chain management [1-2] is the systematic approach to deal with the issues from raw material to the delivery of the product in the market. A supply chain is a network of facilities and distribution options that performs the functions of procurement of materials, transformation of these materials into intermediate and finished products, and the distribution of these finished products to customers [3-4]. Supply chains exist both in service and manufacturing organizations. An essential condition to the success of a company is the conception of a strategy for coordinating the several business unities in a supply chain, leading to an effective management at strategic, tactical and operational levels. The efficiency of a supply chain is influenced by several factors, such as: stock management, production planning, production costs, scheduling and distribution strategies, and customer-specific demand, among others [5]. Planning and modelling the production, stocking and distribution systems of a supply chain is an important support for decision making in a competitive market. Humans are capable to use linguistic information precisely in their decision making. Due to imprecise and uncertain nature of the linguistic information, machines are not capable to use them in decision making processes using traditional methods. To make the machines intelligent, like humans in this regard, Fuzzy Techniques are used. The idea of the Fuzzy Logic [12] was first introduced by Professor Lotfi Ahmad Zadeh, at University of Berkeley, California in his seminal paper “Fuzzy Sets”. Fuzzy Logic is a form of multi-valued logic derived from fuzzy set theory to deal with approximate reasoning. It provides the means to represent and process the linguistic information and subjective attributes of the real world. Fuzzy Logic is the extension of Boolean Crisp Logic to deal with the concept of partial truth. Fuzzy Logic is applied in the number of areas, i.e. engineering applications, medical applications, economics and