بهینه‌سازی زنجیره تأمین هوشمند تحت سیاست‌ ‌مدیریت موجودی توسط فروشنده با رویکرد انتخاب فناوری مرتبط با اینترنت اشیا

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه مهندسی صنایع، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.

2 دانشیار، گروه کسب‌وکار جدید، دانشکده کارآفرینی، دانشگاه تهران، تهران، ایران.

3 دانشیار، گروه مهندسی صنایع، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.

4 دانشیار، گروه مدیریت صنعتی، دانشکده مدیریت، دانشگاه تهران، تهران، ایران.

چکیده

هدف: هدف این پژوهش مدل‌سازی ریاضی زنجیره تأمین هوشمند، تحت سیاست مدیریت موجودی توسط فروشنده با رویکرد اینترنت اشیا، برای بهینه‌سازی و رفع چالش‌های زنجیره تأمین سنتی، از قبیل عدم اطمینان، هزینه و تغییر تقاضای مشتریان است.
روش: بر اساس نیازها و اهداف، یک مدل ریاضی دوهدفه ارائه شد که هدف‌های اول و دوم آن، به‌ترتیب حداقل‌ساختن هزینه و حداقل‌ساختن زمان زنجیره تأمین است. در این مدل، یک زنجیره تأمین چهارسطحی در نظر گرفته شده است که ارتباط مستقیم از تأمین‌کننده به تولیدکننده و از تولیدکننده به خرده‌فروش و ‌‌از خرده‌فروش به مشتری را امکان‌پذیر می‌کند. ماهیت این زنجیره هوشمند است‌ و سطوح زنجیره از فناوری‌های شبکه حسگر بی‌سیم (WSN)، شناسایی فرکانس رادیویی (RFID)، بلاکچین و فروش اینترنتی بهره می‌برد.
یافته‌ها: در این پژوهش، پس از اعتبارسنجی مدل به‌کمک نرم‌افزار گمز، یک مسئله پایه‌ای با روش constraint-  حل شد که نتایج حاصل از حل مدل و نمودار پارتو ارائه شده است. بهینگی پیاده‌سازی فناوری‌های مزبور و همچنین واکنش زمان و هزینه به این پیاده‌سازی، کارآمدی مدل را نشان می‌دهد.
نتیجه‌گیری: در این پژوهش یک مسئله پایه‌ای با روش constraint-  حل شده است. مقادیر توابع هدف و نمودار پارتو، نتایج مطلوبی را نشان می‌دهد. با حل مدل در ابعاد کوچک و متوسط در نرم‌افزار گمز، مقادیر توابع هدف و زمان حل ارائه شده است که نتایج گویای اعتبار مدل است و می‌توان آن را در ابعاد بزرگ‌تر حل کرد. به‌دلیل کمبود حافظه نرم‌افزار گمز، برای حل ابعاد بزرگ مدل، باید از نرم‌افزار متلب و الگوریتم‌های فراابتکاری استفاده شود.

کلیدواژه‌ها


عنوان مقاله [English]

Optimizing Smart Supply Chain with Vendor Managed Inventory through the Internet of Things

نویسندگان [English]

  • Tahereh Mohammadi 1
  • Seyed Mojtaba Sajadi 2
  • Seyed Esmaeil Najafi 3
  • Mohammadreza Taghizadeh Yazdi 4
1 Ph.D. Candidate, Department of Industrial Engineering, Faculty of Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2 Associate Prof., Department of New Business, Faculty of Entrepreneurship, University of Tehran, Tehran, Iran.
3 Associate Prof., Department of Industrial Engineering, Faculty of Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
4 Associate Prof., Department of Industrial Engineering, Faculty of Management, University of Tehran, Tehran, Iran.
چکیده [English]

Objective: The purpose of this research was to provide a mathematical model for smart supply chains with Vendor Managed Inventory (VMI) through the Internet of Things (IoT) technology to overcome traditional supply chain challenges and solve problems such as uncertainty, high costs, and changes in customer demands. Creating an intelligent and agile supply chain is essential to tackle these challenges and problems. Generally, customers are still skeptical and doubtful of the smart supply chain, and this skepticism is more likely to arise in the financial context. To improve efficiency, all organizations and institutions need to adapt themselves to external and internal changes, maintain supply chain inventory, and be flexible with customer demands.
Methods: Previous studies discussed intelligent supply chains, IoT, and their combination and described the advantages and disadvantages of using these technologies. Despite much research in this field, no mathematical modeling has been done for a smart supply chain that incorporates technology and automation. Based on such needs and objectives, this study sought to design a two-objective mathematical model, with a four-level supply chain. In this model, there is a direct relationship from suppliers to manufacturers, from producers to retailers, and from retailers to customers. The supply chain was intelligently designed, and the chain levels used Wireless Sensor Network (WSN) technologies, Radio Frequency Identification (RFID), blockchain, and Internet sales.
Results: The designed model in this research was validated by GAMS software. The researchers identified 10 problems of small and medium dimensions in the model. They presented the results in the form of objective function values ​​and solution time. The basic problem was solved using the -constraint method. The results obtained from solving the model and the Pareto diagram were presented in detail. The optimal implementation of the mentioned technologies, as well as the time and cost response to this implementation, proved the efficiency of the model.
Conclusion: The present study put forward a two-objective mathematical planning model. The first and second objectives of this model were to minimize the cost and decrease the time of the supply chain, respectively. By solving the basic problem, using the -constraint method, the values ​​of the objective functions and the Pareto diagram showed desired results. Solving the model in small and medium-sized dimensions using GAMS software, the values of the objective functions and the solution time were achieved. Also, the results proved the validity of the provided model suggesting that it can be used in larger dimensions. However, due to the lack of memory in GAMS software, for large dimensions, the suggested mathematical model for the smart supply chain needs to be checked using MATLAB software and meta-heuristic algorithms.

کلیدواژه‌ها [English]

  • Internet of things
  • Smart supply chain
  • Wireless sensor network
  • Mathematical modeling
References
Abdel-Basset, M., Manogaran, G. & Mohamed, M. (2018). Internet of Things (IoT) and Its Impact on Supply Chain: A Framework for Building Smart, Secure and Efficient Systems. Future Generation Computer Systems, 86: 614–28.
Agrawal, T. K., Sharma, A., & Kumar, V. (2018). Blockchain-Based Secured Traceability System for Textile and Clothing Supply Chain. In S. Thomassey & X. Zeng (Eds.), Artificial Intelligence for Fashion Industry in the Big Data Era (pp. 197–208). https://doi.org/10.1007/978-981-13-0080-6_10
Angeles, R. (2005). Rfid Technologies: Supply-Chain Applications and Implementation Issues. Information Systems Management, 22(1), 51–65.
Bai, C. & Sarkis, J. (2020). A Supply Chain Transparency and Sustainability Technology Appraisal Model for Blockchain Technology. International Journal of Production Research, 58(7), 2142–2162.
Ben-Daya, M., Hassini, E. & Bahroun, Z. (2017). Internet of Things and Supply Chain Management: A Literature Review. International Journal of Production Research, 7543(November): 1–24. https://doi.org/10.1080/00207543.2017.1402140.
Bhat, S.A., Huang, N.F., Sofi, I.B. & Sultan, M. (2022). Agriculture-Food Supply Chain Management Based on Blockchain and IoT: A Narrative on Enterprise Blockchain Interoperability. Agriculture, 12(1). https://www.mdpi.com/2077-0472/12/1/40.
Center, Auto-ID. (2002). NTechnology Guide. Auto-ID Center.
Chen, Y. & Chen, G. (2022). Optimization of the Intelligent Asset Management System Based on WSN and RFID Technology. ed. Chih-Cheng Chen. Journal of Sensors. https://doi.org/10.1155/2022/3436530.
Christopher, M. (2000). The Agile Supply Chain. Industrial Marketing Management, 29(1), 37–44.
Chung, D.B., Kim, S.I.I., Lee, J.S. (2018). Dynamic Supply Chain Design and Operations Plan for Connected Smart Factories with Additive Manufacturing. Applied Sciences8(4), 583. https://doi.org/10.3390/app8040583
Cole, R., Stevenson, M. & Aitken, J. (2019). Blockchain technology: implications for operations and supply chain management. Supply Chain Management: An International Journal, 24(4), 469–483. https://doi.org/10.1108/SCM-09-2018-0309
Dujak, D. & Sajter, D. (2019). Blockchain Applications in Supply Chain. In SMART Supply Network (pp. 21-46). Springer, Cham.
Greengard, S. (2015). Putting the Internet of Things to Work. In The Internet of Things, MIT Press, 111–34. https://ieeexplore.ieee.org/document/7087520.
Grewal, D., Motyka, S. & Levy, M. (2018). The Evolution and Future of Retailing and Retailing Education. Journal of Marketing Education, 40(1), 85–93.
Gupta, S., Drave, V.A., Bag, S. & Luo, Z. (2019). Leveraging Smart Supply Chain and Information System Agility for Supply Chain Flexibility. Information Systems Frontiers 21(3), 547–64.
Hardgrave, B.C., Aloysius, J. & Goyal, S. (2013). RFID-Enabled Visibility and Retail Inventory Record Inaccuracy: Experiments in the Field. Production and Operations Management, 22(4), 843–56.
Holmström, J. (1998). Business Process Innovation in the Supply Chain - A Case Study of Implementing Vendor Managed Inventory. European Journal of Purchasing and Supply Management, 4(2–3), 127–31.
Jimenez, D., Valdes, S., & Salinas, M. (2019). Popularity Comparison between E-Commerce and Traditional Retail Business. International Journal of Technology for Business1(1), 10-16.
Kamilaris, A., Fonts, A., & Prenafeta-Boldύ, F. X. (2019). The rise of blockchain technology in agriculture and food supply chains. Trends in Food Science & Technology, 91, 640–652. https://doi.org/https://doi.org/10.1016/j.tifs.2019.07.034
Kouhizadeh, M., Zhu, Q., & Sarkis, J. (2020). Blockchain and the circular economy: potential tensions and critical reflections from practice. Production Planning \& Control, 31(11–12), 950–966. https://doi.org/10.1080/09537287.2019.1695925.
Kshetri, N. (2018). 1 Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80–89. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2017.12.005
Lee, I. & Lee, K. (2015a). The Internet of Things (IoT): Applications, Investments, and Challenges for Enterprises. Business Horizons, 58(4), 431–40. https://linkinghub.elsevier.com/retrieve/pii/S0007681315000373.
López, T.S., Ranasinghe, D.C., Patkai, B. & McFarlane, D. (2011). Taxonomy, Technology and Applications of Smart Objects. Information Systems Frontiers, 13(2), 281–300. https://doi.org/10.1007/s10796-009-9218-4.
Mansouri Bakvand, G. (2019). The Impact of Blockchain Technology on Trust in the Supply Chain, Master’s of Logistics and Supply Chain Management, Lund University.
Mohan, T. (2018). Improve Food Supply Chain Traceability using Blockchain, Master of Science the Pennsylvania State University, The Graduate School, College of Engineering.
Nayyar, A. & Puri, W. (2016). Data Glove: Internet of Things (IoT) Based Smart Wearable Gadget. British Journal of Mathematics & Computer Science, 15(5), 1-12.
Nayak, G. & Dhaigude, A. S. (2019). A conceptual model of sustainable supply chain management in small and medium enterprises using blockchain technology. Cogent Economics & Finance, 7(1), 1667184. https://doi.org/10.1080/23322039.2019.1667184
Pundir, A. K., Jagannath, J. D., Chakraborty, M., & Ganpathy, L. (2019). Technology Integration for Improved Performance: A Case Study in Digitization of Supply Chain with Integration of Internet of Things and Blockchain Technology. 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC), 170–176. https://doi.org/10.1109/CCWC.2019.8666484
Queiroz, M. M., Telles, R. & Bonilla, S. H. (2020). Blockchain and supply chain management integration: a systematic review of the literature. Supply Chain Management: An International Journal, 25(2), 241–254. https://doi.org/10.1108/SCM-03-2018-0143.
Raja Santhi, A. & Muthuswamy, P. (2022). Influence of Blockchain Technology in Manufacturing Supply Chain and Logistics. Logistics, 6(15), 2-22.
Saberi, S., Kouhizadeh, M., & Sarkis, J. (2019). Blockchains and the Supply Chain: Findings from a Broad Study of Practitioners. IEEE Engineering Management Review, 47(3), 95–103. https://doi.org/10.1109/EMR.2019.2928264
Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117–2135.
Schmidt, C. G., & Wagner, S. M. (2019). Blockchain and supply chain relations: A transaction cost theory perspective. Journal of Purchasing and Supply Management, 25(4), 100552. https://doi.org/https://doi.org/10.1016/j.pursup.2019.100552
Sharifi, H., Ismail, H.S. & Reid, I. (2006). Achieving Agility in Supply Chain through Simultaneous ‘Design of’ and ‘Design for’ Supply Chain. Journal of Manufacturing Technology Management, 17(8), 1078–98.
Shousong, C., Xiaoguang, W. & Yuanjun, Z. (2019). Revenue Model of Supply Chain by Internet of Things Technology. IEEE Access, 7(c): 4091–4100.
Tan, W.C. & Sidhu, M.S. (2022). Review of RFID and IoT Integration in Supply Chain Management. Operations Research Perspectives 9: 100229. https://www.sciencedirect.com/science/article/pii/S2214716022000070.
Tian, F. (2016). An Agri-Food Supply Chain Traceability System for China Based on RFID Amp; Blockchain Technology. In 2016 13th International Conference on Service Systems and Service Management (ICSSSM), 1–6.
Wu, X., Yue, X., Jin, A. & Yen, D.C. (2016). Smart Supply Chain Management: A Review and Implications for Future Research ed. Yue Xiaohang. The International Journal of Logistics Management, 27(2), 395–417. https://doi.org/10.1108/IJLM-02-2014-0035.
Zhang, L.H., Li, T. & Fan, T.J. (2018). Inventory Misplacement and Demand Forecast Error in the Supply Chain: Profitable RFID Strategies under Wholesale and Buy-Back Contracts. International Journal of Production Research 56(15), 5188–5205. https://doi.org/10.1080/00207543.2018.1463110.
Zhou, K., Liu, T. & Zhou, L. (2015). Industry 4.0: Towards Future Industrial Opportunities and Challenges. In 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2147–52.
Zhu, X.N., Peko, G., Sundaram, D. & Piramuthu, S. (2021). Blockchain-Based Agile Supply Chain Framework with IoT. Information Systems Frontiers, 24(2), 563-578. https://doi.org/10.1007/s10796-021-10114-y.
Zhu, Q., & Kouhizadeh, M. (2019). Blockchain Technology, Supply Chain Information, and Strategic Product Deletion Management. IEEE Engineering Management Review, 47(1), 36–44. https://doi.org/10.1109/EMR.2019.2898178