| Article | |
| Title | Life Cycle Management and Reliability Analysis of Controls Hardware Using Operational Data From EAM |
| Author(s) | Fortescue, Eve (CERN) ; Kozsar, Ioan (CERN) ; Schramm, Volker (Stuttgart U.) |
| Publication | 2023 |
| Number of pages | 4 |
| In: | JACoW ICALEPCS 2023 (2023) TUPDP092 |
| In: | 19th International Conference on Accelerator and Large Experimental Physics Control Systems (ICALEPCS 2023), Cape Town, South Africa, 7 - 13 Oct 2023, pp.TUPDP092 |
| DOI | 10.18429/JACoW-ICALEPCS2023-TUPDP092 |
| Subject category | Computing and Computers |
| Abstract | The use of operational data from Enterprise Asset Management(EAM) systems has become an increasingly popular approach for conducting reliability analysis of industrial equipment. This paper presents a case study of how EAM data was used to analyse the reliability of CERN’s standard controls hardware, deployed and maintained by the Controls Electronics and Mechatronics group. The first part of the study involved the extraction, treatment and analysis of state-transition data to detect failures. The analysis was conducted using statistical methods, including failure-rate analysis and time-to-failure analysis to identify trends in equipment performance and plan for future obsolescence, upgrades and replacement strategies. The results of the analysis are available via a dynamic online dashboard. The second part of the study considers Front-End computers as repairable systems, composed of the previously studied non-repairable modules. The faults were recorded and analysed using the Accelerator Fault Tracking system. The study brought to light the need for high quality data, which led to improvements in the data recording process and refinement of the infrastructure team’s workflow. In the future, reliability analysis will become even more critical for ensuring the cost-effective and efficient operation of controls systems for accelerators. This study demonstrates the potential of EAM operational data to provide valuable insights into equipment reliability and inform decision-making for repairable and non-repairable systems. |
| Copyright/License | CC-BY-4.0 |
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Záznam vytvorený 2024-04-10, zmenený 2024-04-11
