Optimizing production performances with simulation: A case study in the fashion Industry

This paper presents the follow up results of a project related to the development of a decision support tool for improving production performances in the fashion supply chain (SC). In detail, the work presents the application of a discrete-event simulation model on an optimized production plan in order to include stochastic events and manage their effects on the production scheduling KPIs (Key Performance Indicators) in the leather industry. The relevance of this work is related to the fact that one of the main critical issues considering scheduling in the fashion industry is the evidence that suppliers usually have to face with stochastic events, mainly referable to rush orders and delays in the expected delivery of critical components that require to be managed. For this reason, one of the main challenges they have is not trying to avoid the occurrency of these events, which strictly depends on the industry nature, but managing them, in order to understand their impacts on performances and reorganized the production plan. According to this, a dashboard of KPIs represents one of the main results of the developed simulation tool. The model has been applied to a real company, where rush orders and delays in the delivery of critical components are introduced to simulate the impact of stochastics events on the production plan.