Creating a Model for Examining the Human Factors Engineering Adoption Readiness in the Maintenance of Power Plants

Mfundo Nkosi, Kapil Gupta, Madindwa Mashinini

Research output: Contribution to journalArticlepeer-review

Abstract

Considerable efforts have been made to analyze human-system interconnections to address socio-technical system mismatches and human error in aviation, nuclear, and healthcare industries. These endeavors are growing in the production, manufacturing, technology, and logistics sectors. There is a low adoption rate of Human Factors Engineering (HFE) principles in the maintenance of power plants, yet they have also suffered catastrophic failures due to human error. This study aimed to unearth factors that influence the potential adopters' acceptance or decline of HFE programs at the persuasion-decision stage to accelerate the dissemination of HFE in power plants. The HFE adoption readiness model was developed by combining the HFE intervention attributes and organizational planning requirements. The study followed an exploratory, quantitative survey and cross-sectional research focusing on power plants, especially in South Africa. The results revealed that relative advantage, compatibility, cost, and planning are critical to HFE adoption. Of these factors, compatibility was significantly associated with the readiness to adopt (or accept) HFE in maintenance, while cost gave an essential hint. This paper highlighted the study's contributions to research and the use of HFE in the maintenance of power plants.

Original languageEnglish
Pages (from-to)318-332
Number of pages15
JournalJournal of Applied Research on Industrial Engineering
Volume11
Issue number3
DOIs
Publication statusPublished - Sept 2024

Keywords

  • Adoption readiness
  • Human factors engineering
  • Maintenance
  • Power plant
  • Technology adoption
  • Well-being

ASJC Scopus subject areas

  • Information Systems and Management
  • Management Science and Operations Research
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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