PREDICTIVE MAINTENANACE AND ITS ROLE IN ENERGY EFFICIENCY IN THE HOSPITALITY INDUSTRY
Energy efficiency has emerged as a critical priority in the hospitality industry, driven by the need for sustainable operations and long-term cost optimization. Predictive Maintenance (PdM), an innovative strategy that integrates advanced analytics, machine learning, and real-time monitoring, offer...
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| Format: | Article |
| Language: | English |
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Kwara State University, Malete Nigeria
2025-06-01
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| Series: | Malete Journal of Accounting and Finance |
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| Online Access: | https://majaf.com.ng/index.php/majaf/article/view/249 |
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| author | F. B. Adeleke A. S Odetoye, E. E. Akerele O. S. Folorunso A. A. Bashiru |
| author_facet | F. B. Adeleke A. S Odetoye, E. E. Akerele O. S. Folorunso A. A. Bashiru |
| author_sort | F. B. Adeleke |
| collection | DOAJ |
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Energy efficiency has emerged as a critical priority in the hospitality industry, driven by the need for sustainable operations and long-term cost optimization. Predictive Maintenance (PdM), an innovative strategy that integrates advanced analytics, machine learning, and real-time monitoring, offers a proactive approach to equipment management. Despite its potential, many hospitality establishments remain reliant on reactive maintenance models, resulting in frequent equipment failures, excessive energy consumption, and shortened asset lifespans. This study examines the application of PdM in enhancing energy efficiency across hospitality facilities and seeks to establish a framework for anticipating equipment failure, reducing operational disruptions, and promoting sustainable resource use. Using a desk research approach, the study draws insights from a comprehensive review of contemporary literature on smart sensor technologies, machine learning applications, and energy-efficient practices in facility management in Nigeria. The findings underscore PdM’s capacity to extend equipment lifespan, curtail energy waste, and reduce operating costs. However, barriers such as high implementation expenses, insufficient technical expertise, and algorithmic biases continue to impede widespread adoption. Small- and medium-sized enterprises (SMEs), in particular, face significant challenges due to limited financial and human capital, often defaulting to reactive or minimal preventive maintenance approaches. To overcome these constraints, the study advocates for a strategic blend of ethical AI deployment and workforce upskilling. By addressing structural and skill-related gaps, the hospitality sector can unlock the full potential of predictive maintenance, positioning it as a transformative pathway toward greater operational resilience, energy efficiency, and sustainable growth.
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| format | Article |
| id | doaj-art-0579704563f14a57a1c003b8da2dffcd |
| institution | Kabale University |
| issn | 2735-9603 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Kwara State University, Malete Nigeria |
| record_format | Article |
| series | Malete Journal of Accounting and Finance |
| spelling | doaj-art-0579704563f14a57a1c003b8da2dffcd2025-08-26T01:31:05ZengKwara State University, Malete NigeriaMalete Journal of Accounting and Finance2735-96032025-06-0152PREDICTIVE MAINTENANACE AND ITS ROLE IN ENERGY EFFICIENCY IN THE HOSPITALITY INDUSTRYF. B. Adeleke0A. S Odetoye,1E. E. Akerele2O. S. Folorunso3A. A. Bashiru4Kwara State University, MaleteLadoke Akintola University, Ogbomoso, NigeriaKwara State University, MaleteKwara State University, MaleteKwara State University, Malete Energy efficiency has emerged as a critical priority in the hospitality industry, driven by the need for sustainable operations and long-term cost optimization. Predictive Maintenance (PdM), an innovative strategy that integrates advanced analytics, machine learning, and real-time monitoring, offers a proactive approach to equipment management. Despite its potential, many hospitality establishments remain reliant on reactive maintenance models, resulting in frequent equipment failures, excessive energy consumption, and shortened asset lifespans. This study examines the application of PdM in enhancing energy efficiency across hospitality facilities and seeks to establish a framework for anticipating equipment failure, reducing operational disruptions, and promoting sustainable resource use. Using a desk research approach, the study draws insights from a comprehensive review of contemporary literature on smart sensor technologies, machine learning applications, and energy-efficient practices in facility management in Nigeria. The findings underscore PdM’s capacity to extend equipment lifespan, curtail energy waste, and reduce operating costs. However, barriers such as high implementation expenses, insufficient technical expertise, and algorithmic biases continue to impede widespread adoption. Small- and medium-sized enterprises (SMEs), in particular, face significant challenges due to limited financial and human capital, often defaulting to reactive or minimal preventive maintenance approaches. To overcome these constraints, the study advocates for a strategic blend of ethical AI deployment and workforce upskilling. By addressing structural and skill-related gaps, the hospitality sector can unlock the full potential of predictive maintenance, positioning it as a transformative pathway toward greater operational resilience, energy efficiency, and sustainable growth. https://majaf.com.ng/index.php/majaf/article/view/249Predictive maintenanceEnergy efficiencyEquipment reliabilityMachine learningSmart sensorsAssets performance |
| spellingShingle | F. B. Adeleke A. S Odetoye, E. E. Akerele O. S. Folorunso A. A. Bashiru PREDICTIVE MAINTENANACE AND ITS ROLE IN ENERGY EFFICIENCY IN THE HOSPITALITY INDUSTRY Malete Journal of Accounting and Finance Predictive maintenance Energy efficiency Equipment reliability Machine learning Smart sensors Assets performance |
| title | PREDICTIVE MAINTENANACE AND ITS ROLE IN ENERGY EFFICIENCY IN THE HOSPITALITY INDUSTRY |
| title_full | PREDICTIVE MAINTENANACE AND ITS ROLE IN ENERGY EFFICIENCY IN THE HOSPITALITY INDUSTRY |
| title_fullStr | PREDICTIVE MAINTENANACE AND ITS ROLE IN ENERGY EFFICIENCY IN THE HOSPITALITY INDUSTRY |
| title_full_unstemmed | PREDICTIVE MAINTENANACE AND ITS ROLE IN ENERGY EFFICIENCY IN THE HOSPITALITY INDUSTRY |
| title_short | PREDICTIVE MAINTENANACE AND ITS ROLE IN ENERGY EFFICIENCY IN THE HOSPITALITY INDUSTRY |
| title_sort | predictive maintenanace and its role in energy efficiency in the hospitality industry |
| topic | Predictive maintenance Energy efficiency Equipment reliability Machine learning Smart sensors Assets performance |
| url | https://majaf.com.ng/index.php/majaf/article/view/249 |
| work_keys_str_mv | AT fbadeleke predictivemaintenanaceanditsroleinenergyefficiencyinthehospitalityindustry AT asodetoye predictivemaintenanaceanditsroleinenergyefficiencyinthehospitalityindustry AT eeakerele predictivemaintenanaceanditsroleinenergyefficiencyinthehospitalityindustry AT osfolorunso predictivemaintenanaceanditsroleinenergyefficiencyinthehospitalityindustry AT aabashiru predictivemaintenanaceanditsroleinenergyefficiencyinthehospitalityindustry |