Data-Driven Smart Maintenance Decision Analysis: A Drone Factory Demonstrator Combining Digital Twins and Adapted AHP
Paper in proceeding, 2023

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.

Stakeholders

Production systems

Decision analysis

Maintenance engineering

Drones

Production facilities

Digital twins

Author

Paulo Victor Lopes

Chalmers, Industrial and Materials Science, Production Systems

Siyuan Chen

Chalmers, Industrial and Materials Science, Production Systems

Juan Pablo González Sánchez

Chalmers, Industrial and Materials Science, Production Systems

Ebru Turanoglu Bekar

Chalmers, Industrial and Materials Science, Production Systems

Jon Bokrantz

Chalmers, Industrial and Materials Science, Production Systems

Anders Skoogh

Chalmers, Industrial and Materials Science, Production Systems

Proceedings - Winter Simulation Conference

08917736 (ISSN)

Vol. 2023 1996-2007
979-8-3503-6966-3 (ISBN)

2023 Winter Simulation Conference
San Antonio, Texas, USA,

Digitala Stambanan

VINNOVA (2018-04503), 2018-11-01 -- 2020-12-31.

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Reliability and Maintenance

Areas of Advance

Information and Communication Technology

Production

Driving Forces

Innovation and entrepreneurship

DOI

10.1109/WSC60868.2023.10408351

ISBN

9798350369663

More information

Latest update

3/5/2024 1