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Original scientific article

SUPPLY CHAIN INTEGRATION AND CLOUD BASED OPERATIONS MANAGEMENT FOR RESILIENT SMART MANUFACTURING SYSTEMS

By
Lalit Sachdeva Orcid logo ,
Lalit Sachdeva

Assistant Professor, Kalinga University , Naya Raipur, Chhattisgarh , India

Utkarsh Anand Orcid logo
Utkarsh Anand

Assistant Professor, Kalinga University , Naya Raipur, Chhattisgarh , India

Abstract

The research introduces Cloud-SCIM (Supply Chain Integration and Cloud-Based Operations Management to Resilient Smart Manufacturing) model, which aims to solve the problems of the modern manufacturing system. The model leverages cloud computing, IoT, and AI analytics to harmonize supply chain operations, boosting efficiency, flexibility, and resilience. Cloud-SCIM helps ensure effective production, demand projections, inventory maintenance, and sustainability by enabling real-time monitoring, predictive analytics, and automated decision-making. Performance indicators were compared and tested between the suggested model and traditional systems, including Overall Equipment Efficiency (OEE), Mean Absolute percentage Error (MAPE), and inventory turnover. The outcomes indicate significant changes: OEE has improved by 20 points (65 to 85), MAPE decreased by half (15 to 8), and inventory turnover has increased (5 to 9 times a year). Besides, Cloud-SCIM decreases the number of stockouts, downtime and consumes less energy as well as increases the effectiveness of risk mitigation. This study demonstrates that Cloud-SCIM can successfully modify smart manufacturing systems to provide a scalable, flexible solution that enhances operational productivity, resilience, and durability.

References

1.
Smina N, Gahi Y, Gharib J. Data Management in Smart Manufacturing Supply Chains: A Systematic Review of Practices and Applications (2020–2025). Information. 2025 Dec 27;17(1):19.
2.
Giannakis M, Spanaki K, Dubey R. A cloud-based supply chain management system: effects on supply chain responsiveness. Journal of Enterprise Information Management. 2019 Jun 18;32(4):585-607.
3.
Challouf K, Alhloul A, Nemeth N. Mapping the role of industry 4.0 technologies in green supply chain management: a bibliometric and structured text analysis. Discover Sustainability. 2025 Dec;6(1):1-32.
4.
Frank AG, Dalenogare LS, Ayala NF. Industry 4.0 technologies: Implementation patterns in manufacturing companies. International journal of production economics. 2019 Apr 1;210:15-26.
5.
Zhu Q, Sarkis J, Geng Y. Green supply chain management in China: pressures, practices and performance. International journal of operations & production management. 2005 May 1;25(5):449-68.
6.
Yang D, Li R, Liu S. Exploring the Influence of Cloud Computing on Supply Chain Performance: The Mediating Role of Supply Chain Governance. Journal of Theoretical and Applied Electronic Commerce Research. 2025 Apr 10;20(2):70.
7.
Yenugula M, Sahoo S, Goswami S. Cloud computing in supply chain management: Exploring the relationship. Management Science Letters. 2023;13(3):193-210.
8.
Ivanov D, Dolgui A, Sokolov B. Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”. Transportation Research Part E: Logistics and Transportation Review. 2022 Apr 1;160:102676.
9.
Al-Fuqaha A, Guizani M, Mohammadi M, Aledhari M, Ayyash M. Internet of things: A survey on enabling technologies, protocols, and applications. IEEE communications surveys & tutorials. 2015 Jun 15;17(4):2347-76.
10.
Surucu-Balci E, Iris Ç, Balci G. Digital information in maritime supply chains with blockchain and cloud platforms: Supply chain capabilities, barriers, and research opportunities. Technological Forecasting and Social Change. 2024 Jan 1;198:122978.
11.
Zheng X, Zhang X. Robustness of cloud manufacturing system based on complex network and multi-agent simulation. Entropy. 2022 Dec 27;25(1):45.
12.
Aron C, Sgarbossa F, Ballot E, Ivanov D. Cloud material handling systems: A cyber-physical system to enable dynamic resource allocation and digital interoperability. Journal of Intelligent Manufacturing. 2024 Dec;35(8):3815-36.
13.
Rasheed A, San O, Kvamsdal T. Digital twin: Values, challenges and enablers from a modeling perspective. IEEE access. 2020 Jan 28;8:21980-2012.
14.
Su N, Huang S, Su C. Elevating smart manufacturing with a unified predictive maintenance platform: The synergy between data warehousing, apache spark, and machine learning. Sensors. 2024 Jun 29;24(13):4237.
15.
Romero D, Stahre J. Towards the resilient operator 5.0: The future of work in smart resilient manufacturing systems. Procedia cirp. 2021 Jan 1;104:1089-94.
16.
Fowler DS, Epiphaniou G, Higgins MD, Maple C. Aspects of resilience for smart manufacturing systems. Strategic Change. 2023 Nov;32(6):183-93.
17.
Parhi S, Joshi K, Wuest T, Akarte M. Modelling resilience dynamics for smart manufacturing systems: quantification and empirical analysis. International Journal of Computer Integrated Manufacturing. 2025 Nov 2;38(11):1538-59.
18.
Farooq MS, Riaz S, Helou MA, Khan FS, Abid A, Alvi A. Internet of things in greenhouse agriculture: a survey on enabling technologies, applications, and protocols. IEEE access. 2022 Apr 11;10:53374-97.
19.
Parhi S, Kumar S, Joshi K, Akarte M, Raut RD, Narkhede BE. Evaluation of operational transformations for smart manufacturing systems. Journal of Global Operations and Strategic Sourcing. 2024 Aug 27;17(3):541- 73.
20.
Sofic A, Rakic S, Pezzotta G, Markoski B, Arioli V, Marjanovic U. Smart and resilient transformation of manufacturing firms. Processes. 2022 Dec 12;10(12):2674.

Citation

This is an open access article distributed under the  Creative Commons Attribution Non-Commercial License (CC BY-NC) License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 

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