,
Assistant Professor, Kalinga University , Naya Raipur, Chhattisgarh , India
Assistant Professor, Kalinga University , Naya Raipur, Chhattisgarh , India
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.
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.
0
The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.