Digital Twin: Embracing the Fourth Industrial Revolution in Food Supply Chain Management (A Dynamic Analysis)
Subject Areas : ICT
Hajar Soleymanizadeh
1
,
Seyed mahmoud Zanjirchi
2
*
,
Habib Zare Ahmadabadi
3
,
Seyyed Habibollah Mirghfoori
4
1 - PhD student in industrial management (production and operations), Faculty of Economics, Management and Accounting, Yazd University, Yazd, Iran
2 -
3 - University of Yazd
4 - Yazd university
Keywords: Supply Chain, Fourth Industry, Digital Twin, System Dynamics, Food Industry, Technology Deployment.,
Abstract :
Today, the food supply chain is facing various challenges, including long supply chains, complexity, uncertainty, and food waste. With the advent of advanced technologies such as digital twins, these challenges can be addressed. The aim of this study is to investigate the causal relationships between the influencing factors and the results of implementing digital twins in the food supply chain using system dynamics. A descriptive-causal approach with an application-oriented goal was employed, involving a field study among food industry experts, managers, and specialists. Data was collected from various sources such as interviews, reports, documents, and databases. System dynamics was used to analyze the causal relationships between the implementation and application of digital twins in the food supply chain. Three scenarios were considered to provide solutions for the best possible use of digital twin technology in the food industry. The findings showed that an increase in the cost of upgrading internet speed and technology infrastructure, as well as an increase in the training rate of employees, are factors that influence the creation of digital twins. However, the quality of using digital twins in the early years is not optimal due to the lack of skills and knowledge of employees and their resistance to accepting this technology. By training employees and using experts in the field of digital twin technology, employee resistance can be reduced and their understanding of the benefits of using this technology can be increased. In addition, the results showed that the implementation of digital twins can improve product quality, increase consumer willingness to purchase, and reduce the total cost of the product in the long term.
[1] Davis, K.F., S. Downs, and J.A. Gephart, Towards food supply chain resilience to environmental shocks. Nature Food, 2021. 2(1): p. 54-65.
[2] Iftekhar, A. and X. Cui, Blockchain-based traceability system that ensures food safety measures to protect consumer safety and COVID-19 free supply chains. Foods, 2021. 10(6): p. 1289.
[3] Mesterházy, Á., J. Oláh, and J. Popp, Losses in the grain supply chain: Causes and solutions. Sustainability, 2020. 12(6): p. 2342.
[4] Talaie, H., M. Ziaeian, and P. Malekinejad, Designing the establishment and implementation model of quality 4.0 with the integrated approach of interpretive structural modeling and structural equation modeling. Journal of quality engineering and management, 2022. 12(1): p. 51-68.
[5] Patidar, A., et al., Traceability and transportation issues in the food supply chain, in Operations and Supply Chain Management in the Food Industry: Farm to Fork. 2022, Springer. p. 73-93.
[6] Ayokanmbi, F.M. and J. Oluwoye, Improving consumer confidence in food safety and nutritional quality. J. Multidiscip. Eng. Sci. Technol, 2020. 7: p. 12723-12728.
[7] Sharif, A.M. and Z. Irani, Policy making for global food security in a volatile, uncertain, complex and ambiguous (VUCA) world. Transforming Government: People, Process and Policy, 2017. 11(4): p. 523-534.
[8] Paciarotti, C. and F. Torregiani, The logistics of the short food supply chain: A literature review. Sustainable Production and Consumption, 2021. 26: p. 428-442.
[9] Kumar, A. and S. Agrawal, Challenges and opportunities for agri-fresh food supply chain management in India. Computers and Electronics in Agriculture, 2023. 212: p. 108161.
[10] Shen, G., et al., The status of the global food waste mitigation policies: experience and inspiration for China. Environment, Development and Sustainability, 2024. 26(4): p. 8329-8357.
[11] Jayalath, M.M., et al. Adopting Circular Economy Paradigm to Waste Prevention: Investigating Waste Drivers in Vegetable Supply Chains. in IFIP International Conference on Advances in Production Management Systems. 2023. Springer.
[12] مقدم, ز.ک. و غ. ثالث, بهبود سیستم تشخیص نفوذ در اینترنت اشیاء صنعتیِ مبتنی بر یادگیری عمیق با استفاده الگوریتمهای فراابتکاری. فصلنامه فناوری اطلاعات و ارتباطات ایران. 57(57): ص 165.
[13] شمس، و همکاران., بهبود مدیریت منابع در اینترنت اشیا با استفاده از محاسبات مه و الگوریتم بهینهسازی شیر مورچه. فصلنامه فناوری اطلاعات و ارتباطات ایران. 57(57): ص 237.
[14] Attaran, S., M. Attaran, and B.G. Celik, Digital Twins and Industrial Internet of Things: Uncovering operational intelligence in industry 4.0. Decision Analytics Journal, 2024. 10: p. 100398.
[15] Liu, Y., et al., A review of digital twin capabilities, technologies, and applications based on the maturity model. Advanced Engineering Informatics, 2024. 62: p. 102592.
[16] Sutar, P., J. Olivares-Aguila, and A. Vital-Soto, An Offline Digital Twin for Resilience and Supplier Reliability in Perishable Food Supply Chains.
[17] Zafar, M.H., E.F. Langås, and F. Sanfilippo, Exploring the synergies between collaborative robotics, digital twins, augmentation, and industry 5.0 for smart manufacturing: A state-of-the-art review. Robotics and Computer-Integrated Manufacturing, 2024. 89: p. 102769.
[18] Liao, H., et al., Climate change, its impact on emerging infectious diseases and new technologies to combat the challenge. Emerging Microbes & Infections, 2024(just-accepted): p. 2356143.
[19] Ahire, J.J., et al., Quality Management of Probiotics: Ensuring Safety and Maximizing Health Benefits. Current Microbiology, 2024. 81(1): p. 1.
[20] Myshko, A., et al., Towards twin transition in the agri-food sector? Framing the current debate on sustainability and digitalisation. Journal of Cleaner Production, 2024: p. 142063.
[21] Lim, K.Y.H. and C.-H. Chen, Incorporating supply and production digital twins to mitigate demand disruptions in multi-echelon networks. International Journal of Production Economics, 2024: p. 109258.
[22] Maheshwari, P., et al., Digital twin-driven real-time planning, monitoring, and controlling in food supply chains. Technological Forecasting and Social Change, 2023. 195: p. 122799.
[23] Dyck, G., et al., Digital Twins: A novel traceability concept for post-harvest handling. Smart Agricultural Technology, 2023. 3: p. 100079.
[24] Omrany, H., et al., Digital twins in the construction industry: a comprehensive review of current implementations, enabling technologies, and future directions. Sustainability, 2023. 15(14): p. 10908.
[25] Drobnyi, V., et al., Construction and maintenance of building geometric digital twins: state of the art review. Sensors, 2023. 23(9): p. 4382.
[26] Mohandes, S.R., et al., Determining the stationary digital twins implementation barriers for sustainable construction projects. Smart and Sustainable Built Environment, 2024.
[27] Venkatesh, K.P., G. Brito, and M.N. Kamel Boulos, Health digital twins in life science and health care innovation. Annual Review of Pharmacology and Toxicology, 2024. 64: p. 159-170.
[28] Subasi, A. and M.E. Subasi, Digital twins in healthcare and biomedicine, in Artificial Intelligence, Big Data, Blockchain and 5G for the Digital Transformation of the Healthcare Industry. 2024, Elsevier. p. 365-401.
[29] Kaul, R., et al., The role of AI for developing digital twins in healthcare: The case of cancer care. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2023. 13(1): p. e1480.
[30] Damtew, A.W., Roles of digital twins on material performances and utilization on upstream industry (The case of automotive industry). The International Journal of Advanced Manufacturing Technology, 2024. 130(7): p. 3525-3536.
[31] Li, X., W. Niu, and H. Tian, Application of Digital Twin in Electric Vehicle Powertrain: A Review. World Electric Vehicle Journal, 2024. 15(5): p. 208.
[32] Burgos, D. and D. Ivanov, Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions. Transportation Research Part E: Logistics and Transportation Review, 2021. 152: p. 102412.
[33] Melesse, T.Y., et al., Machine learning-based digital twin for monitoring fruit quality evolution. Procedia Computer Science, 2022. 200: p. 13-20.
[34] Singh, G., et al., Resilience and sustainability enhancements in food supply chains using Digital Twin technology: A grey causal modelling (GCM) approach. Computers & Industrial Engineering, 2023. 179: p. 109172.
[35] Melesse, T.Y., et al., Analyzing the Implementation of Digital Twins in the Agri-Food Supply Chain. Logistics, 2023. 7(2): p. 33.
[36] Maheshwari, P., et al., Digital twin implementation for performance improvement in process industries-A case study of food processing company. International Journal of Production Research, 2023. 61(23): p. 8343-8365.
[37] Talaie, H., M. Ziaeian, and P. Malekinejad, Towards quality 4.0 in home appliances: definitions, deployment scenarios, and future perspectives. Journal of Manufacturing Technology Management, 2024. 35(7): p. 1416-1438.
[38] Größler, A., J.H. Thun, and P.M. Milling, System dynamics as a structural theory in operations management. Production and operations management, 2008. 17(3): p. 373-384.
[39] Manzini, R. and R. Accorsi, The new conceptual framework for food supply chain assessment. Journal of food engineering, 2013. 115(2): p. 251-263.
[40] Ghandar, A., et al., A decision support system for urban agriculture using digital twin: A case study with aquaponics. Ieee Access, 2021. 9: p. 35691-35708.
[41] Onwude, D., et al., Physics-driven digital twins to quantify the impact of pre-and postharvest variability on the end quality evolution of orange fruit. Resources, Conservation and Recycling, 2022. 186: p. 106585.
[42] Gallego-García, S., D. Gallego-García, and M. García-García, Sustainability in the agri-food supply chain: a combined digital twin and simulation approach for farmers. Procedia Computer Science, 2023. 217: p. 1280-1295.
[43] Yadav, V.S. and A. Majumdar, What impedes digital twin from revolutionizing agro-food supply chain? Analysis of barriers and strategy development for mitigation. Operations Management Research, 2024: p. 1-17.
[44] Sterman, J., System Dynamics: systems thinking and modeling for a complex world. 2002.
[45] Möllers, T., et al. Design and evaluation of a system dynamics based business model evaluation method. in Designing the Digital Transformation: 12th International Conference, DESRIST 2017, Karlsruhe, Germany, May 30–June 1, 2017, Proceedings 12. 2017. Springer.
[46] Adane, T.F., et al., Application of system dynamics for analysis of performance of manufacturing systems. Journal of Manufacturing Systems, 2019. 53: p. 212-233.
[47] Turner, B.L., et al., System dynamics modeling for agricultural and natural resource management issues: Review of some past cases and forecasting future roles. Resources, 2016. 5(4): p. 40.
[48] Ziaeian, M., et al., Investigating how knowledge management affects the implementation of Industry 4.0 in the home appliance industry of the country. Sciences and Techniques of Information Management, 2023. 9(4): p. 261-292.
[49] Karnopp, D.C., D.L. Margolis, and R.C. Rosenberg, System dynamics: modeling, simulation, and control of mechatronic systems. 2012: John Wiley & Sons.
[50] Sterman, J.D., System dynamics modeling: tools for learning in a complex world. California management review, 2001. 43(4): p. 8-25.
[51] Fildes, R., S. Ma, and S. Kolassa, Retail forecasting: Research and practice. International Journal of Forecasting, 2022. 38(4): p. 1283-1318.
[52] Van Nguyen, T., et al., Predicting customer demand for remanufactured products: A data-mining approach. European Journal of Operational Research, 2020. 281(3): p. 543-558.
[53] Anisere-Hameed, R.A. and T.D. Bodunde, The impact of inventory management on the profitability of manufacturing companies in Nigeria. International Journal of Innovative Research and Advanced Studies (IJIRAS), 2021. 8(1): p. 9-15.
[54] Sakib, S.N., The application of the inventory models to manage and control overstocking in the production system. 2021.
[55] Altekar, R.V., Supply chain management: Concepts and cases. 2023: PHI Learning Pvt. Ltd.
[56] Hutt, M.D. and T.W. Speh, Business marketing management: B2B. 2021: South-Western, Cengage Learning.
[57] Hasfar, M., T. Militina, and G.N. Achmad, Effect of customer value and customer experience on customer satisfaction and loyalty PT meratus samarinda. International Journal of Economics. Business and Accounting Research (IJEBAR), 2020. 4(01).
[58] Jaiswal, S. and A. Singh, Influence of the determinants of online customer experience on online customer satisfaction. Paradigm, 2020. 24(1): p. 41-55.
[59] Putri, P., The effect of operating cash flows, sales growth, and operating capacity in predicting financial distress. International Journal of Innovative Science and Research Technology, 2021. 6(1): p. 638-646.
[60] Giarto, R.V.D. and F. Fachrurrozie, The effect of leverage, sales growth, cash flow on financial distress with corporate governance as a moderating variable. Accounting Analysis Journal, 2020. 9(1): p. 15-21.
[61] Zakirova, A., et al. Organizational and methodological approach to managing financial flows of agricultural enterprises. in E3S web of conferences. 2020. EDP Sciences.
[62] Atmaja, D.S., et al., Actualization Of Performance Management Models For The Development Of Human Resources Quality, Economic Potential, And Financial Governance Policy In Indonesia Ministry Of Education. 2022.
[63] Fedushko, S., T. Ustyianovych, and M. Gregus, Real-time high-load infrastructure transaction status output prediction using operational intelligence and big data technologies. Electronics, 2020. 9(4): p. 668.
[64] Hou, C.-K., The effects of IT infrastructure integration and flexibility on supply chain capabilities and organizational performance: An empirical study of the electronics industry in Taiwan. Information Development, 2020. 36(4): p. 576-602.
[65] Plawsky, J.L., Transport phenomena fundamentals. 2020: CRC press.
[66] Verlinghieri, E. and T. Schwanen, Transport and mobility justice: Evolving discussions. Journal of Transport Geography, 2020. 87: p. 102798.
[67] Zhang, X., et al., A critical review on challenges and trend of ultrapure water production process. Science of The Total Environment, 2021. 785: p. 147254.
[68] Santos, D., J.A.L. da Silva, and M. Pintado, Fruit and vegetable by-products' flours as ingredients: A review on production process, health benefits and technological functionalities. Lwt, 2022. 154: p. 112707.
[69] Mahsyar, S. and U. Surapati, Effect of service quality and product quality on customer satisfaction and loyalty. International Journal of Economics, Business and Accounting Research (IJEBAR), 2020. 4(01).
[70] Chaerudin, S.M. and A. Syafarudin, The effect of product quality, service quality, price on product purchasing decisions on consumer satisfaction. Ilomata International Journal of Tax and Accounting, 2021. 2(1): p. 61-70.
[71] Mubaslat, E.A., Introduction to waste management. 2021, Jordan.
[72] Liboiron, M. and J. Lepawsky, Discard studies: Wasting, systems, and power. 2022: MIT Press.
[73] Sharma, A.K., et al., Mapping the impact of environmental pollutants on human health and environment: A systematic review and meta-analysis. Journal of Geochemical Exploration, 2023: p. 107325.
[74] Ajibade, F.O., et al., Environmental pollution and their socioeconomic impacts, in Microbe mediated remediation of environmental contaminants. 2021, Elsevier. p. 321-354.
[75] Osborne, D. and F. Dempsey, Supply chain management for bulk materials in the coal industry, in The Coal Handbook. 2023, Elsevier. p. 619-664.
[76] Basyal, D.K. and P.D.J. Wan, Employees’ resistance to change and technology acceptance in Nepal. South Asian Studies, 2020. 32(2).
[77] Elgohary, E. and R. Abdelazyz, The impact of employees' resistance to change on implementing e‐government systems: An empirical study in Egypt. The Electronic Journal of Information Systems in Developing Countries, 2020. 86(6): p. e12139.
[78] Paluri, R.A. and A. Mishal, Trust and commitment in supply chain management: a systematic review of literature. Benchmarking: an international journal, 2020. 27(10): p. 2831-2862.
[79] Nguyen, C.T., Trust as an unquestioning attitude. 2022.
[80] Pu, G., et al., Innovative finance, technological adaptation and SMEs sustainability: the mediating role of government support during COVID-19 pandemic. Sustainability, 2021. 13(16): p. 9218.
[81] Chen, C.-L., et al., Role of government to enhance digital transformation in small service business. Sustainability, 2021. 13(3): p. 1028.
[82] Liu, T.Y. and C.C. Lee, Exchange rate fluctuations and interest rate policy. International Journal of Finance & Economics, 2022. 27(3): p. 3531-3549.
[83] Alasha, R.U., The impact of exchange rate fluctuations on economic growth in Nigeria. A Project Submitted in Partial Fulfillment of the Requirements for The Award of Bachelors of Science (B. Sc.) Degree in Economics. Department of Economics, Faculty of Management and Social Sciences Baze University, Abuja, 2020.
[84] Liu, J., Y. Liu, and L. Yang, Uncovering the influence mechanism between top management support and green procurement: The effect of green training. Journal of Cleaner Production, 2020. 251: p. 119674.
[85] Zhen, J., Z. Xie, and K. Dong, Impact of IT governance mechanisms on organizational agility and the role of top management support and IT ambidexterity. International Journal of Accounting Information Systems, 2021. 40: p. 100501.
[86] Mehale, K.D., C.M. Govender, and C.M. Mabaso, Maximising training evaluation for employee performance improvement. SA Journal of Human Resource Management, 2021. 19: p. 11.
[87] Burhan Ismael, N., et al., The role of training and development on organizational effectiveness. Ismael, NB, Othman, BJ, Gardi, B., Hamza, PA, Sorguli, S., Aziz, HM, Ahmed, SA, Sabir, BY, Ali, BJ, Anwar, G.(2021). The Role of Training and Development on Organizational effectiveness. International Journal of Engineering, Business and Management, 2021. 5(3): p. 15-24.
[88] Hajiali, I., et al., Determination of work motivation, leadership style, employee competence on job satisfaction and employee performance. Golden Ratio of Human Resource Management, 2022. 2(1): p. 57-69.
[89] Saniuk, S., D. Caganova, and A. Saniuk, Knowledge and skills of industrial employees and managerial staff for the industry 4.0 implementation. Mobile Networks and Applications, 2023. 28(1): p. 220-230.
[90] Kush, R.D., et al., FAIR data sharing: the roles of common data elements and harmonization. Journal of biomedical informatics, 2020. 107: p. 103421.
[91] Papadimitroulas, P., et al., Artificial intelligence: Deep learning in oncological radiomics and challenges of interpretability and data harmonization. Physica Medica, 2021. 83: p. 108-121.
[92] Zainab, A., et al., Big data management in smart grids: Technologies and challenges. IEEE Access, 2021. 9: p. 73046-73059.
[93] Diène, B., et al., Data management techniques for Internet of Things. Mechanical Systems and Signal Processing, 2020. 138: p. 106564.