ICALEPCS2023 - List of Authors (Kozsar, I.)

Paper	Title	Page
TUPDP092	Life Cycle Management and Reliability Analysis of Controls Hardware Using Operational Data From EAM	758
	E. Fortescue, I. Kozsar, V. Schramm CERN, Meyrin, Switzerland
	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.
	Poster TUPDP092 [40.179 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP092
About •	Received ※ 04 October 2023 — Revised ※ 11 October 2023 — Accepted ※ 05 December 2023 — Issued ※ 12 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TH2BCO04	SAMbuCa: Sensors Acquisition and Motion Control Framework at CERN	1179
	A. Masi, O.Ø. Andreassen, M. Arruat, M. Di Castro, R. Ferraro, I. Kozsar, E.W. Matheson, J.P. Palluel, P. Peronnard, J. Serrano, J. Tagg, F. Vaga, E. Van der Bij CERN, Meyrin, Switzerland S. Danzeca, M. Donzé, S.F. Fargier, M. Gulin, E. Soria European Organization for Nuclear Research (CERN), Geneva, Switzerland
	Motion control systems at CERN often have challenging requirements, such as high precision in extremely radioactive environments with millisecond synchronization. These demanding specifications are particularly relevant for Beam Intercepting Devices (BIDs) such as the collimators of the Large Hadron Collider (LHC). Control electronics must be installed in safe areas, hundreds of meters away from the sensors and actuators while conventional industrial systems only work with cable lengths up to a few tens of meters. To address this, several years of R&D have been committed to developing a high precision motion control system. This has resulted in specialized radiation-hard actuators, new sensors, novel algorithms and actuator control solutions capable of operating in this challenging environment. The current LHC Collimator installation is based on off-the-shelf components from National Instruments. During the Long Shutdown 3 (LS3 2026-2028), the existing systems will be replaced by a new high-performance Sensors Acquisition and Motion Control system (SAMbuCa). SAMbuCa represents a complete, in-house developed, flexible and modular solution, able to cope with the demanding requirements of motion control at CERN, and incorporating the R&D achievements and operational experience of the last 15 years controlling more than 1200 axes at CERN. In this paper, the hardware and software architectures, their building blocks and design are described in detail.
	Slides TH2BCO04 [5.775 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TH2BCO04
About •	Received ※ 05 October 2023 — Revised ※ 12 October 2023 — Accepted ※ 19 December 2023 — Issued ※ 20 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Life Cycle Management and Reliability Analysis of Controls Hardware Using Operational Data From EAM

758

E. Fortescue, I. Kozsar, V. Schramm
CERN, Meyrin, Switzerland

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.

Poster TUPDP092 [40.179 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP092

About •

Received ※ 04 October 2023 — Revised ※ 11 October 2023 — Accepted ※ 05 December 2023 — Issued ※ 12 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TH2BCO04

SAMbuCa: Sensors Acquisition and Motion Control Framework at CERN

1179

A. Masi, O.Ø. Andreassen, M. Arruat, M. Di Castro, R. Ferraro, I. Kozsar, E.W. Matheson, J.P. Palluel, P. Peronnard, J. Serrano, J. Tagg, F. Vaga, E. Van der Bij
CERN, Meyrin, Switzerland
S. Danzeca, M. Donzé, S.F. Fargier, M. Gulin, E. Soria
European Organization for Nuclear Research (CERN), Geneva, Switzerland

Motion control systems at CERN often have challenging requirements, such as high precision in extremely radioactive environments with millisecond synchronization. These demanding specifications are particularly relevant for Beam Intercepting Devices (BIDs) such as the collimators of the Large Hadron Collider (LHC). Control electronics must be installed in safe areas, hundreds of meters away from the sensors and actuators while conventional industrial systems only work with cable lengths up to a few tens of meters. To address this, several years of R&D have been committed to developing a high precision motion control system. This has resulted in specialized radiation-hard actuators, new sensors, novel algorithms and actuator control solutions capable of operating in this challenging environment. The current LHC Collimator installation is based on off-the-shelf components from National Instruments. During the Long Shutdown 3 (LS3 2026-2028), the existing systems will be replaced by a new high-performance Sensors Acquisition and Motion Control system (SAMbuCa). SAMbuCa represents a complete, in-house developed, flexible and modular solution, able to cope with the demanding requirements of motion control at CERN, and incorporating the R&D achievements and operational experience of the last 15 years controlling more than 1200 axes at CERN. In this paper, the hardware and software architectures, their building blocks and design are described in detail.

Slides TH2BCO04 [5.775 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TH2BCO04

About •

Received ※ 05 October 2023 — Revised ※ 12 October 2023 — Accepted ※ 19 December 2023 — Issued ※ 20 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)