A Systematic Approach for Developing Decision Aids: From Cognitive Work Analysis to Prototype Design and Development

Dhukaram, Anandhi Vivekanandan; Baber, Chris

doi:10.1002/sys.21320

Cited by 13 publications

(3 citation statements)

References 65 publications

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“…This process is realized through decomposing the interactions obtained from the decision wheel to events and information clues. By comparing the results of task network characteristics analysis under different levels of automation, the feasibility of CWA to quantitative analysis was verified, which was proposed by many studies that showed that the results of human factors engineering analysis should be combined with the quantitative analysis path [50][51][52]. At the same time, this paper is an attempt to extend the application of a formative method.…”

Section: Discussionmentioning

confidence: 86%

A Task Complexity Analysis Method to Study the Emergency Situation under Automated Metro System

Niu

Liu

Zhang

et al. 2023

IJERPH

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System upgrades and team members interactions lead to changes in task structure. Therefore, in order to handle emergencies efficiently and safely, a comprehensive method of the traffic dispatching team task complexity (TDTTC) is proposed based on team cognitive work analysis (Team-CWA) and network feature analysis. The method comes from the perspective of the socio-technical system. Two stages were included in this method. In the first stage, four phases of Team-CWA, i.e., team work domain analysis, team control task analysis, team strategies analysis, and team worker competencies analysis, were applied in the qualitative analysis of TDTTC. Then in the second stage, a mapping process was established based on events and information cues. After the team task network was established, the characteristic indexes of node degree/average degree, average shortest path length, agglomeration coefficient, and overall network performance for TDTTC were extracted to analyze TDTTC quantitatively. The cases of tasks for screen door fault under grade of automation GOA1–GOA4 were compared. The results revealed that the more nodes and communication between nodes, the larger the network scale was, which would lead to the TDTTC being more complicated no matter what level of automation system it was under. This method is not only the exploration of cognitive engineering theory in the field of task complexity, but also the innovation of team task complexity in the development of automatic metro operation.

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Section: Discussionmentioning

confidence: 86%

A Task Complexity Analysis Method to Study the Emergency Situation under Automated Metro System

Niu

Liu

Zhang

et al. 2023

IJERPH

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“…The root cause method (RCM) follows the problem to its source [37,38]. RCM assumes that systems and events are dependent and may be related.…”

Section: The Root Cause Methodsmentioning

confidence: 99%

Intelligent Monitoring of Data Center Physical Infrastructure

Matko

Brezovec²,

Milanovič

2019

Applied Sciences

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This paper presents a new intelligent monitoring and event management method for data center physical infrastructure based on multilayer node event processing. The priorities of highly classified data centers are not only the maintenance of the highest level of reliability and availability of the operation, but also fast, specific event identification and energy consumption monitoring, which altogether improve the level of energy efficiency. The new method, using a tree node for each device, improves information about the events in a specific node. Its major advantage is that in the case of a large number of nodes, it considerably reduces the number of identified events (alarms/alerts) that might be the main cause. Fast event processing lowers data center physical infrastructure operating costs, improving at the same time the level of energy efficiency. The experimental results show that the use of tree nodes significantly reduces the number of unexpected events, the time needed for the main event identification, and the maintenance response time to events. By using event entities processing, multilayer nodes have a significant impact on the efficient operation of data center physical infrastructure.

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“…Root cause methods and analyses track a problem to its source [37]. This technique is used to find an answer to a question as to what triggered a specific event.…”

Section: Root Cause Analysis (Rca)mentioning

confidence: 99%

Improved Data Center Energy Efficiency and Availability with Multilayer Node Event Processing

Matko

Brezovec²

2018

Energies

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This article presents an overview of a new multilayer node event processing (MNEP) method for improved data center energy efficiency and event management monitoring in its physical infrastructure. Event management is essential for the provision and maintenance of the reliability and functionality of the physical infrastructure. For effective maintenance, action preventing any downtime accurate event information as well as appropriate energy support is of outmost importance. The novelty of this approach lies in the enhanced availability and reliability of the physical infrastructure, improved data center infrastructure energy efficiency, as well as lower costs when designing a new physical infrastructure system. The MNEP method presents a data model based on the node tree processing. The experimental results show that the number of all potential unexpected events is reduced significantly as a result of the accurate identification of the alarm root cause. The comparison of time parameters required to evaluate the maintenance factors shows that the time needed to detect, identify, and react to alarm events decreases and has a significant impact on maintaining a defined high level of availability and energy efficiency in a data center physical infrastructure.

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A Systematic Approach for Developing Decision Aids: From Cognitive Work Analysis to Prototype Design and Development

Cited by 13 publications

References 65 publications

A Task Complexity Analysis Method to Study the Emergency Situation under Automated Metro System

A Task Complexity Analysis Method to Study the Emergency Situation under Automated Metro System

Intelligent Monitoring of Data Center Physical Infrastructure

Improved Data Center Energy Efficiency and Availability with Multilayer Node Event Processing

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