Logistics Management for Supplier Evaluation in an Industry Using Artificial Intelligence (Fuzzy Logic) for Decision Making

Abstract

Quality management is essential for the production of goods and services in a highly competitive market. This study analyzes factors influencing the performance and evaluation of an international supplier in the watch industry for the years 2019 and 2020. The objective is to collect indicators of rejected parts in the receiving inspection and assembly process, as well as deadlines for replacing defective parts, using fuzzy logic to support decision-making regarding supplier approval or disqualification. The quantitative approach involved data collection through spreadsheets extracted from the SAP system. Finally, improvement actions were suggested for the company based on the fuzzy method, aiming to minimize losses and optimize the supplier evaluation process.