نوع مقاله : مقاله پژوهشی- فارسی
نویسندگان
1 گروه مهندسی صنایع، دانشگاه صنعتی مالک اشتر، تهران، ایران.
2 گروه مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران.
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Supply chain resilience in the food sector, particularly for protein products, has gained increasing importance in the presence of disruptions such as sudden demand fluctuations. In this study, a simulation-based digital twin is developed for the distribution network of protein products to evaluate network behavior under normal conditions and various disruption scenarios using real operational data and the AnyLogistix platform. The proposed model represents a network structure consisting of multiple suppliers, a cross-dock facility, and a set of customers, and its performance is assessed using key indicators such as service level and recovery time. In addition to a scenario involving a threefold increase in demand for a specific customer, several other disruption scenarios—including supply disruption, cross-dock capacity limitation, and transportation fleet failure—are designed and analyzed. The results indicate that both the type and severity of disruptions significantly affect network performance and recovery capability, with certain capacity bottlenecks preventing full restoration of the system to its pre-disruption state. As a prototype digital twin, the proposed model provides a decision-support platform for evaluating and comparing managerial policies aimed at enhancing supply chain resilience.
کلیدواژهها [English]
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