Descriptive modelling of team troubleshooting in nuclear domain

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

Even though modern engineering systems are becoming more reliable, there is evidence that main control room (MCR) operators and maintenance technicians have problems in diagnosing complicated events and multiple simultaneous events in nuclear power plants (NPPs). There is a lot of research on finding faults in complex incident situations, but there is quite little knowledge of the cognitive strategies, states and activities of MCR teams in troubleshooting situations. This knowledge is, however, important in modelling collaborative diagnostic reasoning and in developing training interventions and decision support systems to support reasoning and problem solving in NPPs. The present paper will firstly critically review existing methods to model collaborative cognition. Our results suggest that some modelling tools, such as social network analysis and information network analysis are valuable in analysing information sharing and team situation awareness in collaborative troubleshooting, but they do not provide detailed information about the sequential evolution of a team’s knowledge state throughout the diagnostic process. On the other hand, the tools representing an individual troubleshooter’s successive knowledge states, transformed by information processing activities, are ignorant of the distributed nature of complex troubleshooting. Therefore, these approaches have to be tailored to suit better the analysis of team collaboration and co-operation in incident and accident situations, i.e., we have to better understand the collaborative aspects of cognition and team-level collaboration in fault finding and in diagnosing faults. We propose a modelling approach suitable for analysing collaborative diagnostic reasoning and troubleshooting of a NPP MCR crew which is based on existing methods and tools. The approach describes the progress and evolution of a MCR operator crew’s knowledge states throughout the critical sections of a simulator run.

Original languageEnglish
Title of host publicationMCCSIS 2018 - Multi Conference on Computer Science and Information Systems
Subtitle of host publicationProceedings of the International Conferences on e-Health 2018, ICT, Society, and Human Beings 2018 and Web Based Communities and Social Media 2018
EditorsPiet Kommers, Luis Rodrigues, Mario Macedo
Pages93-102
Number of pages10
Publication statusPublished - 1 Jan 2018
MoE publication typeNot Eligible
Event10th International Conference on e-Health 2018, the 11th International Conference on ICT, Society, and Human Beings 2018 and of the 15th International Conference Web Based Communities and Social Media 2018, part of the Multi Conference on Computer Science and Information Systems 2018, MCCSIS 2018 - Madrid, Spain
Duration: 17 Jul 201819 Jul 2018

Conference

Conference10th International Conference on e-Health 2018, the 11th International Conference on ICT, Society, and Human Beings 2018 and of the 15th International Conference Web Based Communities and Social Media 2018, part of the Multi Conference on Computer Science and Information Systems 2018, MCCSIS 2018
CountrySpain
CityMadrid
Period17/07/1819/07/18

Fingerprint

Nuclear power plants
Electric network analysis
Decision support systems
Systems engineering
Accidents
Simulators

Keywords

  • Collaboration
  • Operator
  • Process control
  • Troubleshooting

Cite this

Laarni, J. (2018). Descriptive modelling of team troubleshooting in nuclear domain. In P. Kommers, L. Rodrigues, & M. Macedo (Eds.), MCCSIS 2018 - Multi Conference on Computer Science and Information Systems: Proceedings of the International Conferences on e-Health 2018, ICT, Society, and Human Beings 2018 and Web Based Communities and Social Media 2018 (pp. 93-102)
Laarni, Jari. / Descriptive modelling of team troubleshooting in nuclear domain. MCCSIS 2018 - Multi Conference on Computer Science and Information Systems: Proceedings of the International Conferences on e-Health 2018, ICT, Society, and Human Beings 2018 and Web Based Communities and Social Media 2018. editor / Piet Kommers ; Luis Rodrigues ; Mario Macedo. 2018. pp. 93-102
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title = "Descriptive modelling of team troubleshooting in nuclear domain",
abstract = "Even though modern engineering systems are becoming more reliable, there is evidence that main control room (MCR) operators and maintenance technicians have problems in diagnosing complicated events and multiple simultaneous events in nuclear power plants (NPPs). There is a lot of research on finding faults in complex incident situations, but there is quite little knowledge of the cognitive strategies, states and activities of MCR teams in troubleshooting situations. This knowledge is, however, important in modelling collaborative diagnostic reasoning and in developing training interventions and decision support systems to support reasoning and problem solving in NPPs. The present paper will firstly critically review existing methods to model collaborative cognition. Our results suggest that some modelling tools, such as social network analysis and information network analysis are valuable in analysing information sharing and team situation awareness in collaborative troubleshooting, but they do not provide detailed information about the sequential evolution of a team’s knowledge state throughout the diagnostic process. On the other hand, the tools representing an individual troubleshooter’s successive knowledge states, transformed by information processing activities, are ignorant of the distributed nature of complex troubleshooting. Therefore, these approaches have to be tailored to suit better the analysis of team collaboration and co-operation in incident and accident situations, i.e., we have to better understand the collaborative aspects of cognition and team-level collaboration in fault finding and in diagnosing faults. We propose a modelling approach suitable for analysing collaborative diagnostic reasoning and troubleshooting of a NPP MCR crew which is based on existing methods and tools. The approach describes the progress and evolution of a MCR operator crew’s knowledge states throughout the critical sections of a simulator run.",
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Laarni, J 2018, Descriptive modelling of team troubleshooting in nuclear domain. in P Kommers, L Rodrigues & M Macedo (eds), MCCSIS 2018 - Multi Conference on Computer Science and Information Systems: Proceedings of the International Conferences on e-Health 2018, ICT, Society, and Human Beings 2018 and Web Based Communities and Social Media 2018. pp. 93-102, 10th International Conference on e-Health 2018, the 11th International Conference on ICT, Society, and Human Beings 2018 and of the 15th International Conference Web Based Communities and Social Media 2018, part of the Multi Conference on Computer Science and Information Systems 2018, MCCSIS 2018, Madrid, Spain, 17/07/18.

Descriptive modelling of team troubleshooting in nuclear domain. / Laarni, Jari.

MCCSIS 2018 - Multi Conference on Computer Science and Information Systems: Proceedings of the International Conferences on e-Health 2018, ICT, Society, and Human Beings 2018 and Web Based Communities and Social Media 2018. ed. / Piet Kommers; Luis Rodrigues; Mario Macedo. 2018. p. 93-102.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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N2 - Even though modern engineering systems are becoming more reliable, there is evidence that main control room (MCR) operators and maintenance technicians have problems in diagnosing complicated events and multiple simultaneous events in nuclear power plants (NPPs). There is a lot of research on finding faults in complex incident situations, but there is quite little knowledge of the cognitive strategies, states and activities of MCR teams in troubleshooting situations. This knowledge is, however, important in modelling collaborative diagnostic reasoning and in developing training interventions and decision support systems to support reasoning and problem solving in NPPs. The present paper will firstly critically review existing methods to model collaborative cognition. Our results suggest that some modelling tools, such as social network analysis and information network analysis are valuable in analysing information sharing and team situation awareness in collaborative troubleshooting, but they do not provide detailed information about the sequential evolution of a team’s knowledge state throughout the diagnostic process. On the other hand, the tools representing an individual troubleshooter’s successive knowledge states, transformed by information processing activities, are ignorant of the distributed nature of complex troubleshooting. Therefore, these approaches have to be tailored to suit better the analysis of team collaboration and co-operation in incident and accident situations, i.e., we have to better understand the collaborative aspects of cognition and team-level collaboration in fault finding and in diagnosing faults. We propose a modelling approach suitable for analysing collaborative diagnostic reasoning and troubleshooting of a NPP MCR crew which is based on existing methods and tools. The approach describes the progress and evolution of a MCR operator crew’s knowledge states throughout the critical sections of a simulator run.

AB - Even though modern engineering systems are becoming more reliable, there is evidence that main control room (MCR) operators and maintenance technicians have problems in diagnosing complicated events and multiple simultaneous events in nuclear power plants (NPPs). There is a lot of research on finding faults in complex incident situations, but there is quite little knowledge of the cognitive strategies, states and activities of MCR teams in troubleshooting situations. This knowledge is, however, important in modelling collaborative diagnostic reasoning and in developing training interventions and decision support systems to support reasoning and problem solving in NPPs. The present paper will firstly critically review existing methods to model collaborative cognition. Our results suggest that some modelling tools, such as social network analysis and information network analysis are valuable in analysing information sharing and team situation awareness in collaborative troubleshooting, but they do not provide detailed information about the sequential evolution of a team’s knowledge state throughout the diagnostic process. On the other hand, the tools representing an individual troubleshooter’s successive knowledge states, transformed by information processing activities, are ignorant of the distributed nature of complex troubleshooting. Therefore, these approaches have to be tailored to suit better the analysis of team collaboration and co-operation in incident and accident situations, i.e., we have to better understand the collaborative aspects of cognition and team-level collaboration in fault finding and in diagnosing faults. We propose a modelling approach suitable for analysing collaborative diagnostic reasoning and troubleshooting of a NPP MCR crew which is based on existing methods and tools. The approach describes the progress and evolution of a MCR operator crew’s knowledge states throughout the critical sections of a simulator run.

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ER -

Laarni J. Descriptive modelling of team troubleshooting in nuclear domain. In Kommers P, Rodrigues L, Macedo M, editors, MCCSIS 2018 - Multi Conference on Computer Science and Information Systems: Proceedings of the International Conferences on e-Health 2018, ICT, Society, and Human Beings 2018 and Web Based Communities and Social Media 2018. 2018. p. 93-102