Abstract
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.
Highlights
Performance in the maintenance of power plant facilities often poses significant risks
Personnel performance is closely related to energy management performance, and is a factor in energy consumption and human errors [5,6], further investigation is required to determine the interaction between personnel, energy management, and the critical success factors (CSFs) associated with thermal and gas power plant maintenance [7]
The previous literature dealing with the interaction between personnel performance and energy management performance in maintaining power plants is analyzed in an attempt to answer three specific research questions: (RQ1) What are the current challenges facing the improvement of performance in the maintenance of power plants? (RQ2) What are the CSFs for integrating an intelligent performance improvement framework? (RQ3) Is it possible to develop an intelligent framework that can improve performance? This study provides a new vision for improving performance based on Industry 4.0 and Artificial intelligence (AI), clarifying the integration of personal performance with energy management performance in gas and thermal power plants within an intelligent framework
Summary
Performance in the maintenance of power plant facilities often poses significant risks. Industry 4.0 is intended to integrate performance within power plants, reducing human errors and ensuring high energy. Lack of intelligent integration of performance and poor automation in the maintenance of power plants causes losses that are roughly 2.5 times higher than those attributed to hardware failure [4]. Personnel performance is closely related to energy management performance, and is a factor in energy consumption and human errors [5,6], further investigation is required to determine the interaction between personnel, energy management, and the critical success factors (CSFs) associated with thermal and gas power plant maintenance [7]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
