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Digital twin-driven real-time planning, monitoring, and controlling in food supply chains

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  • Maheshwari, Pratik
  • Kamble, Sachin
  • Belhadi, Amine
  • Venkatesh, Mani
  • Abedin, Mohammad Zoynul

Abstract

There needs to be more clarity about when and how the digital twin approach could benefit the food supply chains. In this study, we develop and solve an integrated problem of procurement, production, and distribution strategies (PPDs) in a medium-scale food processing company. Using the digital twin approach, the model considers the industrial symbiosis opportunities between the supplier, manufacturer, and customer using interval and sequence variables operating in a constrained environment using mixed-integer linear programming (MILP) and agent-based simulation (ABS) methodology. The study optimizes the make-span and lead time, simultaneously achieving a higher level of digitalization. The analysis demonstrates how digital twin accelerates supply chain productivity by improving makespan time, data redundancy (DR), optimal scheduling plan (OSP), overall operations effectiveness (OOE), overall equipment effectiveness (OEE), and capacity utilization. Our findings provide compelling evidence that the seamless integration PPDs enormously enhance production flexibility, resulting in an excellent service level of 94 %. Managers leverage real-time simulation to accurately estimate the replenishment point with minimal lead time, ensuring optimized operations.

Suggested Citation

  • Maheshwari, Pratik & Kamble, Sachin & Belhadi, Amine & Venkatesh, Mani & Abedin, Mohammad Zoynul, 2023. "Digital twin-driven real-time planning, monitoring, and controlling in food supply chains," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    • Handle: RePEc:eee:tefoso:v:195:y:2023:i:c:s0040162523004845
    DOI: 10.1016/j.techfore.2023.122799
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    1. Haitao Liu & Zhaoxia Guo & Zhengzhong Zhang, 2021. "A hybrid multi-level optimisation framework for integrated production scheduling and vehicle routing with flexible departure time," International Journal of Production Research, Taylor & Francis Journals, vol. 59(21), pages 6615-6632, November.
    2. Zhang, Guoqing & Shang, Xiaoting & Alawneh, Fawzat & Yang, Yiqin & Nishi, Tatsushi, 2021. "Integrated production planning and warehouse storage assignment problem: An IoT assisted case," International Journal of Production Economics, Elsevier, vol. 234(C).
    3. Shijin Wang & Ming Liu & Chengbin Chu, 2015. "A branch-and-bound algorithm for two-stage no-wait hybrid flow-shop scheduling," International Journal of Production Research, Taylor & Francis Journals, vol. 53(4), pages 1143-1167, February.
    4. Kamble, Sachin S & Gunasekaran, Angappa & Parekh, Harsh & Mani, Venkatesh & Belhadi, Amine & Sharma, Rohit, 2022. "Digital twin for sustainable manufacturing supply chains: Current trends, future perspectives, and an implementation framework," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    5. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    6. Ezra Wari & Weihang Zhu, 2019. "A Constraint Programming model for food processing industry: a case for an ice cream processing facility," International Journal of Production Research, Taylor & Francis Journals, vol. 57(21), pages 6648-6664, November.
    7. Eldon A. Gunn & Corinne A. MacDonald & Andrea Friars & Glen Caissie, 2014. "Scotsburn Dairy Group Uses a Hierarchical Production Scheduling and Inventory Management System to Control Its Ice Cream Production," Interfaces, INFORMS, vol. 44(3), pages 253-268, June.
    8. Ricci, Riccardo & Battaglia, Daniele & Neirotti, Paolo, 2021. "External knowledge search, opportunity recognition and industry 4.0 adoption in SMEs," International Journal of Production Economics, Elsevier, vol. 240(C).
    9. Srivastava, Deepak Kumar & Kumar, Vikas & Ekren, Banu Yetkin & Upadhyay, Arvind & Tyagi, Mrinal & Kumari, Archana, 2022. "Adopting Industry 4.0 by leveraging organisational factors," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    10. Utama, Dana Marsetiya & Santoso, Imam & Hendrawan, Yusuf & Dania, Wike Agustin Prima, 2022. "Integrated procurement-production inventory model in supply chain: A systematic review," Operations Research Perspectives, Elsevier, vol. 9(C).
    11. Manu Sharma & Anil Kumar & Sunil Luthra & Sudhanshu Joshi & Arvind Upadhyay, 2022. "The impact of environmental dynamism on low‐carbon practices and digital supply chain networks to enhance sustainable performance: An empirical analysis," Business Strategy and the Environment, Wiley Blackwell, vol. 31(4), pages 1776-1788, May.
    12. Shou-feng Ji & Xiao-shuai Peng & Rong-juan Luo, 2019. "An integrated model for the production-inventory-distribution problem in the Physical Internet," International Journal of Production Research, Taylor & Francis Journals, vol. 57(4), pages 1000-1017, February.
    13. Dmitry Ivanov, 2017. "Simulation-based ripple effect modelling in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 2083-2101, April.
    14. Núñez-Merino, Miguel & Maqueira-Marín, Juan Manuel & Moyano-Fuentes, José & Castaño-Moraga, Carlos Alberto, 2022. "Industry 4.0 and supply chain. A Systematic Science Mapping analysis," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    15. Wenqiang Dai & Zhuolin Yang & Yi Feng & Meng Zheng, 2020. "Real-time procurement policy with yield and price uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 58(3), pages 758-782, February.
    16. Meng, Qingfeng & Li, Zhen & Liu, Huimin & Chen, Jingxian, 2017. "Agent-based simulation of competitive performance for supply chains based on combined contracts," International Journal of Production Economics, Elsevier, vol. 193(C), pages 663-676.
    17. Sumona Mukhuty & Arvind Upadhyay & Holly Rothwell, 2022. "Strategic sustainable development of Industry 4.0 through the lens of social responsibility: The role of human resource practices," Business Strategy and the Environment, Wiley Blackwell, vol. 31(5), pages 2068-2081, July.
    18. Gharbi, Ali & Kenné, Jean-Pierre & Kaddachi, Rawia, 2022. "Dynamic optimal control and simulation for unreliable manufacturing systems under perishable product and shelf life variability," International Journal of Production Economics, Elsevier, vol. 247(C).
    19. Farajpour, Farnoush & Hassanzadeh, Alireza & Elahi, Shaban & Ghazanfari, Mehdi, 2022. "Digital supply chain blueprint via a systematic literature review," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    20. Nguyen, Tiep & Duong, Quang Huy & Nguyen, Truong Van & Zhu, You & Zhou, Li, 2022. "Knowledge mapping of digital twin and physical internet in Supply Chain Management: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 244(C).
    21. D. G. Mogale & Naoufel Cheikhrouhou & Manoj Kumar Tiwari, 2020. "Modelling of sustainable food grain supply chain distribution system: a bi-objective approach," International Journal of Production Research, Taylor & Francis Journals, vol. 58(18), pages 5521-5544, September.
    22. Latino, Maria Elena & Menegoli, Marta & Lazoi, Mariangela & Corallo, Angelo, 2022. "Voluntary traceability in food supply chain: a framework leading its implementation in Agriculture 4.0," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    23. Florio, Alexandre M. & Hartl, Richard F. & Minner, Stefan, 2020. "Optimal a priori tour and restocking policy for the single-vehicle routing problem with stochastic demands," European Journal of Operational Research, Elsevier, vol. 285(1), pages 172-182.
    24. Dhar, Suparna & Tarafdar, Pratik & Bose, Indranil, 2022. "Understanding the evolution of an emerging technological paradigm and its impact: The case of Digital Twin," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
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