Production risk caused by human factors: a multiple case study of thermal power plants

Diao, Huiyue; Ghorbani, Majid

doi:10.1186/s11782-018-0035-9

Cited by 13 publications

(3 citation statements)

References 61 publications

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“…Meta-analysis of human factors could help improve employee performance in power plants [10]. Similarly, human factors have been analyzed in terms of the risks faced by thermal power plants' maintenance staff [11]. This analysis showed that, to minimize such errors, understanding human behavior is imperative.…”

Section: Human Factorsmentioning

confidence: 99%

Intelligent Integrated Model for Improving Performance in Power Plants

Ajmi¹,

Mahmood²,

Jamaludin³

et al. 2022

Computers, Materials &Amp; Continua

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Industry 4.0 is expected to play a crucial role in improving energy management and personnel performance in power plants. Poor performance problem in maintaining power plants is the result of both human errors, human factors and the poor implementation of automation in energy management. This problem can potentially be solved using artificial intelligence (AI) and an integrated management system (IMS). This article investigates the current challenges to improving personnel and energy management performance in power plants, identifies the critical success factors (CSFs) for an integrated intelligent framework, and develops an intelligent framework that enables power plants to improve performance. The theoretical basis is founded on a systematic literature review to locate 110 out of 3108 papers studied carefully to examine the performance architecture that best enables effective maintenance. The findings from this literature review are combined with expert judgment and the big data advantages of AI applications to develop an intelligent model. Data are collected from a power plant in Iraq. To ensure the reliability of the proposed model, various hypotheses are tested using structural equation modeling. The results confirm that the measurement model is acceptable, and that the hypotheses are supported and significant. A case study demonstrates the strong relationship and significance between big data of performance and the CSFs. It is hoped that this model will be adopted to enable performance improvement in power plants.

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Section: Human Factorsmentioning

confidence: 99%

Intelligent Integrated Model for Improving Performance in Power Plants

Ajmi¹,

Mahmood²,

Jamaludin³

et al. 2022

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

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“…Poor performance in the industrial sector, especially in the electricity sector, negatively affects the power plant and contributes to the increase in human errors and the weakness of human factors [5]. The literature confirms the need to conduct more studies and investigations related to the performance shaping factors, including the human performance, human factors, and human error in maintaining thermal and gas power plants [6][7][8][9][10][11][12]. Additionally, further investigation regarding the CSFs of energy management is required [13][14][15].…”

Section: Introductionmentioning

confidence: 97%

Novel Approach to Energy Management via Performance Shaping Factors in燩ower Plants

Ajmi¹,

Mahmood²,

Jamaludin³

et al. 2022

Computers, Materials &Amp; Continua

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The literature that a lack of integration between the performance shaping factors (PSFs) and the energy management performance (EMP) is one of the critical problems that prevent performance improvement and reduces the power plant's efficiency. To solve this problem, this article aims to achieve two main objectives: (1) Systematically investigate and identify the critical success factors (CSFs) for integration with PSFs and EMP; (2) Develop a novel modelling approach to predict the performance of power plants based on innovative integrated strategies. The research methodology is grounded on the theoretical and practical approach to improving performance. The Newcastle Ottawa Scale (NOS) was used to assess the quality of the literature that met the criteria. To ensure the reliability and accuracy of the proposed model, the researchers developed a hypothesis and evaluated the CSFs via a case study in the Iraqi power plants. The findings of this study succeeded in developing a novel modeling approach to predict the performance by integrating the CSFs of both the PSFs and EMP to increase the positive interaction and energy efficiency of power plants. The results confirmed the validity of the selected hypotheses and verified the positive and important relationship with the success and improvement of the performance in power plants. However, the lack of consistency and balance in the current studies indicates that the performance strategy in power plants did not receive sufficient attention and needs further investigations.

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“…Accordingly, PSFs, especially human factors, can improve the personnel's behavior performance toward EMP in power plants [ 7 ]. The poor performance of PSFs in power plants has resulted in increased human errors, which can have long-term negative effects [ [8] , [9] , [10] , [11] , [12] , [13] ]. Furthermore, unlike nuclear power generation systems that require high levels of automation, thermal power plants typically operate with lower levels of automation.…”

Section: Introductionmentioning

confidence: 99%