Publication: Reliability concerns of programmable logic controllers: Trends and methodologies from 2010-2023
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Issued Date
2024-01-01
Resource Type
eISSN
25953982
Scopus ID
2-s2.0-85201806480
Journal Title
Multidisciplinary Reviews
Volume
7
Issue
12
Rights Holder(s)
SCOPUS
Bibliographic Citation
Multidisciplinary Reviews Vol.7 No.12 (2024)
Suggested Citation
Obele A.F., Aikhuele D.O., Herold N.U., Sorooshian S., Ahadi N., Virutamasen P. Reliability concerns of programmable logic controllers: Trends and methodologies from 2010-2023. Multidisciplinary Reviews Vol.7 No.12 (2024). doi:10.31893/multirev.2024270 Retrieved from: https://hdl.handle.net/20.500.14740/20154
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Abstract
The manufacturing, chemical, and process industries frequently employ programmable logic controllers (PLCs) in industrial automation systems because they are very effective and dependable in applications requiring sequential control and the synchronization of processes and auxiliary parts. Despite their robustness, idealism, and tolerance to adverse operational conditions such as unclean air, humidity, vibration, and electrical noise, PLC-based control systems can nevertheless malfunction, leading to a substantial amount of downtime. To determine the methods that have been most frequently employed to increase the dependability of systems or components from 2010 to 2023, this study will offer trends in the reliability analysis of systems. To review articles released within the past 14 years, this study used a systematic literature review process. The reliability analysis was divided into categories. The findings indicated that although the use of combinatorial and hybrid models is on the rise, combinatorial modeling, which is the process of creating a mathematical model to solve a problem, can be used to explain this growing tendency. Hybrid models, which use both combinatorial and state-space-based solutions, are commonly regarded as the most cutting-edge methods for evaluating reliability. For dependability analysis, state space models have been increasingly frequently utilized. This study will help other researchers discover the gaps in reliability analysis that need to be filled to choose the best course of action for new research.