Role of Digital Twins in SAP and Cloud based Manufacturing
The integration of Digital Twins in SAP and cloud-based manufacturing systems is reshaping the landscape of industrial operations by fostering real-time data synchronization and enhancing decision-making processes. A Digital Twin, a virtual representation of physical assets, systems, or processes, offers significant benefits in monitoring, simulation, and optimization within manufacturing environments. When combined with SAP's enterprise resource planning (ERP) systems and cloud-based platforms, it enables seamless data flow and provides businesses with the ability to predict performance, mitigate risks, and optimize resources. This paper explores the pivotal role of Digital Twins in improving operational efficiency, enabling predictive maintenance, and facilitating agile manufacturing strategies. By utilizing cloud computing, manufacturers can scale their digital twin solutions without the constraints of on-premise infrastructure, ensuring a flexible and cost-effective approach. SAP’s integration with Digital Twins enhances the visibility of supply chains, inventory management, and production processes, allowing manufacturers to make informed decisions quickly and accurately. Furthermore, cloud technology provides centralized access to real-time data, which is crucial for continuous improvement and innovation. This research highlights key applications of Digital Twins in manufacturing, including process optimization, product lifecycle management, and system integration. The convergence of these technologies offers unprecedented opportunities to transform traditional manufacturing models into intelligent, data-driven operations capable of responding to dynamic market demands and operational challenges.
Authors
- V. Ravi (ORCID: https://orcid.org/0000-0002-5097-6189)
- Lalit Kumar (ORCID: https://orcid.org/0000-0001-5934-9299)
- Om Goel
- Prof. Arpit Jain
- Sridhar Jampani
- Sunil Gudavalli
Publication Details
- Journal
- Journal of Quantum Science and Technology.
- Published
- 2024-11-01
- DOI
- https://doi.org/10.63345/jqst.v1i4.101
- Citations
- 2
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.70