substantial research has been conducted on flexible manufacturing systems (FMS) planning, it has predominantly centred on well-established academic layout strategies. The selection process primarily relies on fundamental principles within the intelligent system JSSE (workshop scheduling environment), with limited literature available on its application within an FMS. This article aims to investigate the performance of machine and AGV (Automated Guided Vehicle) scheduling models in reducing the number of operations within the FMS using a Greedy Algorithm (GA) approach. The methodology is evaluated under various experimental conditions through an FMS simulation model encompassing 40 different scenarios.