Usefulness and Time Savings Metrics to Evaluate Adoption of Digital Twin Technology 2023-01-0111
The application of virtual engineering methods can streamline the product design process through improved collaboration opportunities among the technical staff and facilitate additive manufacturing processes. A product digital twin can be created using the available computer-aided design and analytical mathematical models to numerically explore the current and future system performance based on operating cycles. The strategic decision to implement a digital twin is of interest to companies, whether the required financial and workforce resources will be worthwhile. In this paper, two metrics are introduced to assist management teams in evaluating the technology potential. The usefulness and time savings metrics will be presented with accompanying definitions. A case study highlights the usefulness metric for the “Deep Orange” prototype vehicle, an innovative off-road hybrid vehicle designed and fabricated at Clemson University. Survey responses identified factors including verification/validation and model organization as critical focus areas for future digital twin technology implementation. The results demonstrate how model repertoires can be leveraged to new product cycles and fill the knowledge gaps of new engineers joining the development team. Overall, the metrics establish a basis to generate discussions regarding embracing emerging workplace technology.
Citation: Eddy, C., Castanier, M., Wagner, J., Morris, J. et al., "Usefulness and Time Savings Metrics to Evaluate Adoption of Digital Twin Technology," SAE Technical Paper 2023-01-0111, 2023, https://doi.org/10.4271/2023-01-0111. Download Citation
Author(s):
Conner Eddy, Matthew Castanier, John Wagner, John Morris, Benjamin Moss
Affiliated:
Clemson University, US Army DEVCOM GVSC
Pages: 14
Event:
WCX SAE World Congress Experience
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Machine learning
Computer simulation
Mathematical models
Artificial intelligence (AI)
Design processes
CAD, CAM, and CAE
Additive manufacturing
Manufacturing processes
Hybrid electric vehicles
Education and training
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