ICALEPCS2023 - List of Authors (Blanco Vinuela, E.)

Paper	Title	Page
MO3AO06	Energy Consumption Optimisation by Using Advanced Control Algorithms	145
	F. Ghawash, E. Blanco Viñuela, B. Schofield CERN, Meyrin, Switzerland
	Large industries operate energy-intensive equipment and energy efficiency is an important objective when trying to optimize the final energy consumption. CERN utilizes a large amount of electrical energy to run its accelerators, detectors and test facilities, with a total yearly consumption of 1.3 TWh and peaks of about 200 MW. Final energy consumption reduction can be achieved by dedicated technical solutions and advanced automation technologies, especially those based on optimization algorithms, have revealed a crucial role not only in keeping the processes within required safety and operational conditions but also in incorporating financial factors. MBPC (Model-Based Predictive Control) is a feedback control algorithm which can naturally integrate the capability of achieving reduced energy consumption when including economic factors in the optimization formulation. This paper reports on the experience gathered when applying non-linear MBPC to some of the contributors to the electricity bill at CERN: the cooling and ventilation plants (i.e. cooling towers, chillers, and air handling units). Simulation results with cooling towers showed significant performance improvements and energy savings close to 20% over conventional heuristic solutions. The control problem formulation, the control strategy validation using a digital twin and the initial results in a real industrial plant are reported together with the experience gained implementing the algorithm in industrial controllers.
	Slides MO3AO06 [3.101 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-MO3AO06
About •	Received ※ 04 October 2023 — Revised ※ 09 October 2023 — Accepted ※ 14 November 2023 — Issued ※ 29 November 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TU2BCO02	Protection Layers Design for the High Luminosity LHC Full Remote Alignment System	285
	B. Fernández Adiego, E. Blanco Viñuela, A. Germinario, H. Mainaud Durand, M. Sosin CERN, Meyrin, Switzerland
	The Full Remote Alignment System (FRAS) is a complex measurement, alignment and control system designed to remotely align components of the Large Hadron Collider (LHC) following its High Luminosity upgrade. The purpose of FRAS is to guarantee optimal alignment of the strong focusing magnets and associated components near the experimental interaction points, while at the same time limiting the radiation dose to which surveyors in the LHC tunnel are subjected. A failure in the FRAS control system, or an operator mistake, could provoke a non desired displacement of a component that could lead to damage of neighbouring equipment. Such an incident would incur a considerable repair cost both in terms of money and time. To mitigate this possibility, an exhaustive risk analysis of FRAS has been performed, with the design of protection layers according to the IEC 61511 standard proposed. This paper presents the different functional safety techniques applied to FRAS, reports on the current project status, and introduces the future activities to complete the safety life cycle.
	Slides TU2BCO02 [2.757 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TU2BCO02
About •	Received ※ 03 October 2023 — Accepted ※ 14 December 2023 — Issued ※ 19 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUMBCMO39	Enhanced Maintenance and Availability of Handling Equipment using IIoT Technologies	462
	E. Blanco Viñuela, A.G. Garcia Fernandez, D. Lafarge, G. Thomas, J-C. Tournier CERN, Meyrin, Switzerland
	CERN currently houses 6000 handling equipment units categorized into 40 different families, such as electric overhead travelling cranes (EOT), hoists, trucks, and forklifts. These assets are spread throughout the CERN campus, on the surface (indoor and outdoor), as well as in underground tunnels and experimental caverns. Partial access to some areas, a large area to cover, thousands of units, radiation, and diverse needs among handling equipment makes maintenance a cumbersome task. Without automatic monitoring solutions, the handling engineering team must conduct periodic on-site inspections to identify equipment in need of regulatory maintenance, leading to unnecessary inspections in hard-to-reach environments for underused equipment but also reliability risks for overused equipment between two technical visits. To overcome these challenges, a remote monitoring solution was introduced to extend the equipment lifetime and perform optimal maintenance. This paper describes the implementation of a remote monitoring solution integrating IIoT (Industrial Internet of Things) technologies with the existing CERN control infrastructure and frameworks for control systems (UNICOS and WinCC OA). At the present time, over 600 handling equipment units are being monitored successfully and this number will grow thanks to the scalability this solution offers.
	Slides TUMBCMO39 [0.560 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUMBCMO39
About •	Received ※ 03 October 2023 — Accepted ※ 28 November 2023 — Issued ※ 19 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

TUPDP001	Working Together for Safer Systems: A Collaboration Model for Verification of PLC Code	467
	I.D. Lopez-Miguel IAP TUW, Wien, Austria C. Betz, M. Salinas GSI, Darmstadt, Germany E. Blanco Viñuela, B. Fernández Adiego CERN, Meyrin, Switzerland
	Formal verification techniques are widely used in critical industries to minimize software flaws. However, despite the benefits and recommendations of the functional safety standards, such as IEC 61508 and IEC 61511, formal verification is not yet a common practice in the process industry and large scientific installations. This is mainly due to its complexity and the need for formal methods experts. At CERN, the PLCverif tool was developed to verify PLC programs formally. Although PLCverif hides most of the complexity of using formal methods and removes barriers to formally verifying PLC programs, engineers trying to verify their developments still encounter different obstacles. These challenges include the formalization of program specifications or the creation of formal models. This paper discusses how to overcome these obstacles by proposing a collaboration model that effectively allows the verification of critical PLC programs and promotes knowledge transfer between organizations. By providing a simpler and more accessible way to carry out formal verification, tools like PLCverif can play a crucial role in achieving this goal. The collaboration model splits the specification, development, and verification tasks between organizations. This approach is illustrated through a case study between GSI and CERN.
	Poster TUPDP001 [0.744 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP001
About •	Received ※ 03 October 2023 — Accepted ※ 20 November 2023 — Issued ※ 19 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THPDP059	Towards Automatic Generation of Fail-Safe PLC Code Compliant with Functional Safety Standards	1449
	A. Germinario, E. Blanco Viñuela, B. Fernández Adiego CERN, Meyrin, Switzerland
	In agreement with the IEC 61511 functional safety standard, fail-safe application programs should be written using a Limited Variability Language (LVL), that has a limited number of operations and data types, such as LD (Ladder Diagrams) or FBD (Function Block Diagrams) for safety PLC (Programmable Logic Controller) languages. The specification of safety instrumented systems, as part of the Safety Requirements Specification document, shall unambiguously define the logic of the program, creating a one-to-one relationship between code and specification. Hence, coding becomes a translation from a specification language to PLC code. This process is repetitive and error-prone when performed by a human. In this paper we describe the process of fully generating Siemens TIA portal LD programs for safety applications from a formal specification. The process starts by generating an intermediate model that represents a generic LD program based on a predefined meta-model. This intermediate model is then automatically translated into code. The idea can be expanded to other equivalent LVL languages from other PLC manufacturers. In addition, the intermediate model can be generated from different specification formalisms having the same level of expressiveness as the one presented in this paper: a Cause-Effect Matrix. Our medium-term vision is to automatically generate fail-safe programs from diverse formal specification methods and using different LVLs.
	Poster THPDP059 [1.935 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THPDP059
About •	Received ※ 03 October 2023 — Revised ※ 26 October 2023 — Accepted ※ 08 December 2023 — Issued ※ 09 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Energy Consumption Optimisation by Using Advanced Control Algorithms

145

F. Ghawash, E. Blanco Viñuela, B. Schofield
CERN, Meyrin, Switzerland

Large industries operate energy-intensive equipment and energy efficiency is an important objective when trying to optimize the final energy consumption. CERN utilizes a large amount of electrical energy to run its accelerators, detectors and test facilities, with a total yearly consumption of 1.3 TWh and peaks of about 200 MW. Final energy consumption reduction can be achieved by dedicated technical solutions and advanced automation technologies, especially those based on optimization algorithms, have revealed a crucial role not only in keeping the processes within required safety and operational conditions but also in incorporating financial factors. MBPC (Model-Based Predictive Control) is a feedback control algorithm which can naturally integrate the capability of achieving reduced energy consumption when including economic factors in the optimization formulation. This paper reports on the experience gathered when applying non-linear MBPC to some of the contributors to the electricity bill at CERN: the cooling and ventilation plants (i.e. cooling towers, chillers, and air handling units). Simulation results with cooling towers showed significant performance improvements and energy savings close to 20% over conventional heuristic solutions. The control problem formulation, the control strategy validation using a digital twin and the initial results in a real industrial plant are reported together with the experience gained implementing the algorithm in industrial controllers.

Slides MO3AO06 [3.101 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-MO3AO06

About •

Received ※ 04 October 2023 — Revised ※ 09 October 2023 — Accepted ※ 14 November 2023 — Issued ※ 29 November 2023

Cite •

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

TU2BCO02

Protection Layers Design for the High Luminosity LHC Full Remote Alignment System

285

B. Fernández Adiego, E. Blanco Viñuela, A. Germinario, H. Mainaud Durand, M. Sosin
CERN, Meyrin, Switzerland

The Full Remote Alignment System (FRAS) is a complex measurement, alignment and control system designed to remotely align components of the Large Hadron Collider (LHC) following its High Luminosity upgrade. The purpose of FRAS is to guarantee optimal alignment of the strong focusing magnets and associated components near the experimental interaction points, while at the same time limiting the radiation dose to which surveyors in the LHC tunnel are subjected. A failure in the FRAS control system, or an operator mistake, could provoke a non desired displacement of a component that could lead to damage of neighbouring equipment. Such an incident would incur a considerable repair cost both in terms of money and time. To mitigate this possibility, an exhaustive risk analysis of FRAS has been performed, with the design of protection layers according to the IEC 61511 standard proposed. This paper presents the different functional safety techniques applied to FRAS, reports on the current project status, and introduces the future activities to complete the safety life cycle.

Slides TU2BCO02 [2.757 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TU2BCO02

About •

Received ※ 03 October 2023 — Accepted ※ 14 December 2023 — Issued ※ 19 December 2023

Cite •

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

TUMBCMO39

Enhanced Maintenance and Availability of Handling Equipment using IIoT Technologies

462

E. Blanco Viñuela, A.G. Garcia Fernandez, D. Lafarge, G. Thomas, J-C. Tournier
CERN, Meyrin, Switzerland

CERN currently houses 6000 handling equipment units categorized into 40 different families, such as electric overhead travelling cranes (EOT), hoists, trucks, and forklifts. These assets are spread throughout the CERN campus, on the surface (indoor and outdoor), as well as in underground tunnels and experimental caverns. Partial access to some areas, a large area to cover, thousands of units, radiation, and diverse needs among handling equipment makes maintenance a cumbersome task. Without automatic monitoring solutions, the handling engineering team must conduct periodic on-site inspections to identify equipment in need of regulatory maintenance, leading to unnecessary inspections in hard-to-reach environments for underused equipment but also reliability risks for overused equipment between two technical visits. To overcome these challenges, a remote monitoring solution was introduced to extend the equipment lifetime and perform optimal maintenance. This paper describes the implementation of a remote monitoring solution integrating IIoT (Industrial Internet of Things) technologies with the existing CERN control infrastructure and frameworks for control systems (UNICOS and WinCC OA). At the present time, over 600 handling equipment units are being monitored successfully and this number will grow thanks to the scalability this solution offers.

Slides TUMBCMO39 [0.560 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUMBCMO39

About •

Received ※ 03 October 2023 — Accepted ※ 28 November 2023 — Issued ※ 19 December 2023

Cite •

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

TUPDP001

Working Together for Safer Systems: A Collaboration Model for Verification of PLC Code

467

I.D. Lopez-Miguel
IAP TUW, Wien, Austria
C. Betz, M. Salinas
GSI, Darmstadt, Germany
E. Blanco Viñuela, B. Fernández Adiego
CERN, Meyrin, Switzerland

Formal verification techniques are widely used in critical industries to minimize software flaws. However, despite the benefits and recommendations of the functional safety standards, such as IEC 61508 and IEC 61511, formal verification is not yet a common practice in the process industry and large scientific installations. This is mainly due to its complexity and the need for formal methods experts. At CERN, the PLCverif tool was developed to verify PLC programs formally. Although PLCverif hides most of the complexity of using formal methods and removes barriers to formally verifying PLC programs, engineers trying to verify their developments still encounter different obstacles. These challenges include the formalization of program specifications or the creation of formal models. This paper discusses how to overcome these obstacles by proposing a collaboration model that effectively allows the verification of critical PLC programs and promotes knowledge transfer between organizations. By providing a simpler and more accessible way to carry out formal verification, tools like PLCverif can play a crucial role in achieving this goal. The collaboration model splits the specification, development, and verification tasks between organizations. This approach is illustrated through a case study between GSI and CERN.

Poster TUPDP001 [0.744 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-TUPDP001

About •

Received ※ 03 October 2023 — Accepted ※ 20 November 2023 — Issued ※ 19 December 2023

Cite •

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

THPDP059

Towards Automatic Generation of Fail-Safe PLC Code Compliant with Functional Safety Standards

1449

A. Germinario, E. Blanco Viñuela, B. Fernández Adiego
CERN, Meyrin, Switzerland

In agreement with the IEC 61511 functional safety standard, fail-safe application programs should be written using a Limited Variability Language (LVL), that has a limited number of operations and data types, such as LD (Ladder Diagrams) or FBD (Function Block Diagrams) for safety PLC (Programmable Logic Controller) languages. The specification of safety instrumented systems, as part of the Safety Requirements Specification document, shall unambiguously define the logic of the program, creating a one-to-one relationship between code and specification. Hence, coding becomes a translation from a specification language to PLC code. This process is repetitive and error-prone when performed by a human. In this paper we describe the process of fully generating Siemens TIA portal LD programs for safety applications from a formal specification. The process starts by generating an intermediate model that represents a generic LD program based on a predefined meta-model. This intermediate model is then automatically translated into code. The idea can be expanded to other equivalent LVL languages from other PLC manufacturers. In addition, the intermediate model can be generated from different specification formalisms having the same level of expressiveness as the one presented in this paper: a Cause-Effect Matrix. Our medium-term vision is to automatically generate fail-safe programs from diverse formal specification methods and using different LVLs.

Poster THPDP059 [1.935 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THPDP059

About •

Received ※ 03 October 2023 — Revised ※ 26 October 2023 — Accepted ※ 08 December 2023 — Issued ※ 09 December 2023

Cite •

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