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Investigation of the impact of main control room digitalization on operators cognitive reliability in nuclear power plants

Issue title: IEA 2012: 18th World congress on Ergonomics - Designing a sustainable future

Article type: Research Article

Authors: Zhou, Yong | Mu, HaiYing | Jiang, Jianjun | Zhang, Li

Affiliations: Flight Technology college, Civil Aviation Flight University of China, 618307, Guanghan, China | Human Factors Institute, University of South China, 421001, Hengyang, China | Department of Computer Engineering, KangDa Vocational Technical College, 511363, Guangzhou, China

Note: [] Corresponding author. Tel.:+86 15181049689; fax: +86 08385182124; E-mail: [email protected].

Keywords: digital main control room, cognitive reliability, human factors issues, human errors, bayesian network

DOI: 10.3233/WOR-2012-0231-714

Journal: Work, vol. 41, no. Supplement 1, pp. 714-721, 2012

Published: 2012
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Abstract

Currently, there is a trend in nuclear power plants (NPPs) toward introducing digital and computer technologies into main control rooms (MCRs). Safe generation of electric power in NPPs requires reliable performance of cognitive tasks such as fault detection, diagnosis, and response planning. The digitalization of MCRs has dramatically changed the whole operating environment, and the ways operators interact with the plant systems. If the design and implementation of the digital technology is incompatible with operators’ cognitive characteristics, it may have negative effects on operators’ cognitive reliability. Firstly, on the basis of three essential prerequisites for successful cognitive tasks, a causal model is constructed to reveal the typical human performance issues arising from digitalization. The cognitive mechanisms which they impact cognitive reliability are analyzed in detail. Then, Bayesian inference is used to quantify and prioritize the influences of these factors. It suggests that interface management and unbalanced workload distribution have more significant impacts on operators’ cognitive reliability.

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