Fuzzy AHP for supplier selection: a case study in an electronic component manufacturer

Abstract

Supplier selection has become an essential effect on the entire electronic supply chain network on performance. The case study company produces a nano sim-card connector which four primary raw materials are processed into four primary parts (Plastic, Nickel, Phosphor bronze, and Stainless steel). Nevertheless, the case study company faces a penalty and order reduction because of the quality issue. Although an appraisal record from the case study company is able to select a proper raw material supplier, the cost becomes the priority when the candidate suppliers are categorized as the same level, leading to increasing potential risks, e.g., a penalty, rework in OEM, and order reduction. Additionally, the appraisal record is measured by the procurement team that the probability bias and personal preference tend to affect the final decision. This thesis proposes a Fuzzy Analytic Hierarchy Process (Fuzzy AHP) model for raw material supplier selection by collecting data from two departments (Procurement and Engineering) and clients to address qualitative and quantitative elements, uncertainty, and linguistic vagueness based on the case study company scenario in three parts. First, the main criteria and sub-criteria are selected by related decision makers. Second, the Fuzzy AHP is proposed to identify scores for each raw material supplier. Then, the sensitivity analysis is applied to observe how the decision changes when the model parameters, e.g., the quality consistency, delivery delays, etc., change. The proposed model can offer better information and solutions for the DM in the case study company to differentiate the crucial main criteria and sub-criteria and select the suitable raw material suppliers effectively.