Research library / 2023 / Conference paper
Data-Driven Smart Maintenance Decision Analysis: A Drone Factory Demonstrator Combining Digital Twins and Adapted AHP
Proceedings - Winter Simulation Conference · 2023
Abstract
Original English abstract
The concept of Digital Twins has gained significant attention in recent years due to its potential for improving the performance of production systems. One promising area for Digital Twins is Smart Maintenance, enabling the simulation of different strategies without disrupting operations in the real system. This study proposes a high-level framework to integrate Digital Twins to support Smart Maintenance data-driven decision making in production lines. We implement, then, a case study of a lab scale drone factory to demonstrate how the production line performance evaluation is made under different what-if maintenance scenarios. The effects of this Smart Maintenance decision analysis approach were evaluated according to Key Performance Indicators from literature. The identified contributions are: (i) Digital Twin demonstrator focused on smart maintenance; (ii) implementation of smart maintenance data-driven decision analysis concepts; (iii) design and evaluation of what-if maintenance scenarios.
Original source: Chalmers Research ↗
In brief
A drone-factory digital twin supports maintenance comparisons without interrupting real production. The demonstrator evaluates what-if scenarios and combines performance indicators with structured decision analysis.
Key points
- Develops a smart-maintenance digital twin demonstrator for a lab-scale drone production line.
- Evaluates production performance under alternative maintenance scenarios.
- Combines scenario analysis with a structured decision process and performance indicators.
Cite this work
Paulo Victor Lopes, Siyuan Chen, Juan Pablo González Sánchez, Ebru Turanoglu Bekar, Jon Bokrantz, Anders Skoogh (2023). Data-Driven Smart Maintenance Decision Analysis: A Drone Factory Demonstrator Combining Digital Twins and Adapted AHP. Proceedings - Winter Simulation Conference, 2023, pp. 1996–2007. https://doi.org/10.1109/WSC60868.2023.10408351
@inproceedings{Chen2023DigitalTwinMaintenance,
title = {{Data-Driven Smart Maintenance Decision Analysis: A Drone Factory Demonstrator Combining Digital Twins and Adapted AHP}},
author = {Lopes, Paulo Victor and Chen, Siyuan and González Sánchez, Juan Pablo and Turanoglu Bekar, Ebru and Bokrantz, Jon and Skoogh, Anders},
year = {2023},
booktitle = {2023 Winter Simulation Conference (WSC)},
volume = {2023},
pages = {1996--2007},
doi = {10.1109/WSC60868.2023.10408351},
url = {https://research.chalmers.se/en/publication/540104}
}
Abstract reproduced from the linked source record. The overview and key points are concise explanations of the study.