Automated guided vehicle mission reliability modelling using a combined fault tree and Petri net approach

Yang, Rundong; Jackson, Lisa M.; Dunnett, Sarah J.

Abstract

Automated guided vehicles (AGVs) are being extensively used for intelligent transportation and distribution of materials in warehouses and autoproduction lines due to their attributes of high efficiency and low costs. Such vehicles travel along a predefined route to deliver desired tasks without the supervision of an operator. Much effort in this area has focused primarily on route optimisation and traffic management of these AGVs. However, the health management of these vehicles and their optimal mission configuration have received little attention. To assure their added value, taking a typical AGV transport system as an example, the capability to evaluate reliability issues in AGVs are investigated in this paper. Following a failure modes effects and criticality analysis (FMECA), the reliability of the AGV system is analysed via fault tree analysis (FTA) and the vehicles mission reliability is evaluated using the Petri net (PN) method. By performing the analysis, the acceptability of failure of the mission can be analysed, and hence the service capability and potential profit of the AGV system can be reviewed and the mission altered where performance is unacceptable. The PN method could easily be extended to have the capability to deal with fleet AGV mission reliability assessment.

• Journal Article Type: Article
• Acceptance Date: Feb 16, 2017
• Online Publication Date: Mar 21, 2017
• Publication Date: 2017-09
• Deposit Date: Jul 5, 2023
• Publicly Available Date: Jul 6, 2023
• Journal: The International Journal of Advanced Manufacturing Technology
• Print ISSN: 0268-3768
• Electronic ISSN: 1433-3015
• Peer Reviewed: Peer Reviewed
• Volume: 92
• Pages: 1825-1837
• DOI: https://doi.org/10.1007/s00170-017-0175-7
• Public URL: https://nottingham-repository.worktribe.com/output/22455175
• Publisher URL: https://link.springer.com/article/10.1007/s00170-017-0175-7