Industrial Innovations

Industrial Innovations

Modeling for a Resilient Supply Chain under Disruption risk: A Case Study of Dairy Products

Document Type : Original Article

Authors
Fatemeh Eshaghi
Ashkan Mohsenzadeh Ledari
Department of Industrial Engineering, Mazandaran University of Science and Technology, Behshahr, Iran.
10.66224/jii.3.3.83
Abstract
This study develops a comprehensive nationwide supply chain network model for perishable dairy products, integrating a domestic supplier, multiple production facilities and distribution centers, and geographically dispersed customer demand points. A discrete-event simulation model was constructed using AnyLogistix software to holistically analyze dynamic network behavior and quantify key performance indicators, including total profitability, system-wide inventory levels, order-to-delivery lead times, and service level fulfillment rates. To accurately assess resilience, deliberate capacity disruptions were incorporated. Two high-impact, prolonged disruption scenarios were modeled: a complete 90-day production center shutdown and a parallel 90-day distribution center shutdown, both initiating in the fifth operational month. For each scenario, a suite of proactive and reactive managerial response strategies was rigorously evaluated to determine optimal pathways for enhancing supply chain robustness and recovery. Simulation results demonstrate that during a production disruption, activating a pre-negotiated emergency production outsourcing contract significantly improves network redundancy, restores effective capacity, and mitigates losses in profitability and customer service levels. For distribution network failures, the optimal response is contingent upon strategic priorities: inventory policy adjustments across the remaining network offer a cost-efficient solution, while establishing a pre-qualified backup distribution center provides superior service continuity at a higher fixed cost. The core contribution of this research is a validated, dynamic simulation framework designed to support data-driven strategic decision-making for building resilience in critical food supply chains against unforeseen operational shocks. This versatile tool enables managers and planners to proactively stress-test the network, benchmark multiple mitigation strategies, and ultimately maintain stringent service level agreements while optimizing overall cost-efficiency and operational continuity in the face of disruptions.
Keywords
Dairy supply chain
Dynamic simulation
Resilience
Capacity disruption
supply chain risk
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  • Receive Date 26 November 2025
  • Revise Date 31 January 2026
  • Accept Date 01 February 2026