Factors Affecting Adoption of Industry 4.0 Predictive Maintenance by Manufacturing Industries: Tanzania Food and Beverage Manufacturing Industries
DOI:
https://doi.org/10.52339/tjet.v44i1.1038Keywords:
Industry 4.0, Predictive Maintenance , Manufacturing Industries, Adoption of PdM 4.0, Tanzania, Structural Equation Modeling (SEM), Factor AnalysisAbstract
The fourth industrial revolution has attracted much academic attention in these past few years. However, research on systematic and extensive factors affecting adoption of Industry 4.0 predictive maintenance (PdM 4.0) by manufacturing industries in developing countries, especially in East African countries, has been unavailable. This study aims to explore the impact of factors that influence the actual adoption of Industry 4.0 predictive maintenance by food and beverage manufacturing industries (MI) in Tanzania. Mixed-method research was utilized in this study including in-depth interviews of 10 participants and quantitative research of 90 respondents who are representative of MI by both online and via paper surveys. The SPSS and Smart PLS 4 software were employed to help analyze the collected data. The results indicate that strategic decisions, Equipment data, organizational culture, perceived ease of use, perceived benefit, resource availability, external pressure, risk perception and adoption intention, all have a positive significant effect on actual adoption of Industry 4.0 predictive maintenance. The results seem to suggest that managerial efforts aimed at increasing the factors’ perceptions of adoption of Industry 4.0 PdM and personal relevance of the technology will contribute to implementation success, where success is defined as actual usage of the industry 4.0 predictive maintenance.
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