Please use this identifier to cite or link to this item:
https://repository.iimb.ac.in/handle/2074/21350
DC Field | Value | Language |
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dc.contributor.advisor | Hazra, Jishnu | |
dc.contributor.author | Harish Kumar, V | |
dc.contributor.author | Goutham, R | |
dc.date.accessioned | 2022-07-01T12:30:16Z | - |
dc.date.available | 2022-07-01T12:30:16Z | - |
dc.date.issued | 2021 | |
dc.identifier.uri | https://repository.iimb.ac.in/handle/2074/21350 | - |
dc.description.abstract | As per Gartner, it is a digitalised or computerised version of a physical entity or system. It differs from the traditional computer model or 3D models as it dynamically updates the physical state of the system into the digital model and predicts the future state or runs scenarios to help optimize business performance. Digital Twin needs historical data for better prediction and detailed enough to study the supply chain interactions for various scenarios including some historical disruption data. The data should help in creating the extent of scenarios in the twin model for demand variability, financial flows and various scenario testing. Digital twin requires update on the physical system that need to be up to date for processes such as shipment details, vehicle tracking and location, inventory levels. Digital Twin aid in short-term and mid-term supply chain decision-making, better learning, reasoning and understanding of the physical system for the decision makers. For mid-term application of digital twin to supply chain entails a detailed model of company’s supply chain processes for predicting the supply chain dynamics in terms of supply chain behaviour, predicting abnormal situations and catering to supply chain disruptions and to figure out the action plan. The application of digital twin makes the processes and resources to be reviewed and improved for supply chain resilience. For short term it helps in identifying problems, analysis of the problem and possible solutions and implications for the supply chain disruptions like transportation optimisation potential, bullwhip effect and external disruptions. | |
dc.publisher | Indian Institute of Management Bangalore | |
dc.relation.ispartofseries | PGP_CCS_P21_140 | |
dc.subject | Digital twins | |
dc.subject | Technological innovations | |
dc.subject | Supply chain | |
dc.subject | Information technology | |
dc.title | Plan to procure business process digital twin for dell supply chain | |
dc.type | CCS Project Report-PGP | |
dc.pages | 15p. | |
Appears in Collections: | 2021 |
Files in This Item:
File | Size | Format | |
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PGP_CCS_P21_140.pdf | 1.8 MB | Adobe PDF | View/Open Request a copy |
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