Optimizing Sustainable Supply Chains in Apparel Production through System Dynamics Modeling using Vensim - Tomi, Tomi (Universitas Insan Cendekia Mandiri, 2025)
Supply chain management plays a crucial role in manufacturing processes, where the flow of goods begins with raw materials and continues to the end consumer, involving various complexities and uncertainties at each stage. Computer-based modeling and simulation are highly useful methods for addressing operational issues within the supply chain, as they are capable of solving complex problems that would otherwise be time-consuming and challenging to analyze manually. On the other hand, manufacturing companies are often concerned about losing valuable time and resources during production; inaccurate estimations of raw materials, labor, and equipment not only result in financial losses but also cause adverse environmental impacts. The purpose of this study is to demonstrate that system dynamics modeling in sustainable supply chain management can be applied to apparel production in order to optimize the use of materials, labor, and equipment. This research employs Vensim as a modeling and simulation tool due to its ability to represent causal relationships, manage complex feedback loops, and visualize system dynamics over time. By utilizing Vensim, manufacturing companies can simulate various supply chain scenarios in a controlled environment, thereby minimizing resource waste and enhancing sustainability through the reduction of energy consumption, material use, and labor. Shirt manufacturing was selected as the case study because its production process is relatively straightforward, while this garment type is also widely used across the globe. The findings of this study indicate that simulation using system dynamics modeling with Vensim is an efficient method for optimizing the utilization of materials, labor, and equipment in shirt production. This leads to a more sustainable manufacturing process, as the developed model allows for the evaluation of supply chain policies and their impacts before implementation in real systems.