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Incorporating supply and production digital twins to mitigate demand disruptions in multi-echelon networks

Author

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  • Lim, Kendrik Yan Hong
  • Dang, Le Van
  • Chen, Chun-Hsien

Abstract

In today's globalized environment, supply chain (SC) and manufacturing operations are intrinsically linked to satisfy consumer demand. Faced with rising preferences for personalized goods, convenience, and price competitiveness, many companies pivot towards e-commerce strategies and product family approaches to offer wider product varieties and shorten delivery times. This is evident in the fast-moving consumer goods (FMCG) industry, where multi-echelon networks are often utilized to optimize inventory and lower costs. While these methods can fulfill consumer expectations, decreased network resilience is a key obstacle, leaving supply networks vulnerable to supply and demand disruptions. Hence, a holistic approach is required to mitigate disruptions impacts in multi-echelon networks. As a digital enabler, digital twin (DT) technology can manage disruptions in SC networks and manufacturing shop floors. However, these solutions typically operate in silos without context considerations, resulting in illogical solutions. To overcome these challenges, this study proposes a novel supply and production (S&P) DT system to enhance resilience and disruption management in multi-echelon networks. A four-tier technology stack is introduced first, then resilience evaluation, SC replanning, and shop floor rescheduling methods are explored. Based on this, a DT-enabled disruption mitigation mechanism is proposed and featured in an F&B-oriented demand spike disruption case study. Results show the role of the hybrid S&P DT system in improving demand fulfillment rate and reducing production make span to enhance operational continuity.

Suggested Citation

  • Lim, Kendrik Yan Hong & Dang, Le Van & Chen, Chun-Hsien, 2024. "Incorporating supply and production digital twins to mitigate demand disruptions in multi-echelon networks," International Journal of Production Economics, Elsevier, vol. 273(C).
  • Handle: RePEc:eee:proeco:v:273:y:2024:i:c:s0925527324001154
    DOI: 10.1016/j.ijpe.2024.109258
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