Abstract
Machine efficiency can be enhanced by adapting maintenance practices. Organisations have adapted a proactive approach to maintenance by incorporating predictive maintenance and condition monitoring techniques. Machinery and equipment are required to operate non-stop for organisations to achieve maximum capabilities. Recent advanced analytical instrumentation for the maintenance of machinery has become more compact and portable and has been developed to maintain the harsh continuous cycling of machinery. This research explores if one of these latest and sophisticated analytical instruments developed, namely, a portable Fourier Transform Infrared (FTIR) oil analysis instrument, can be successfully incorporated into a predictive maintenance program. The research examines if maintenance personnel can use the results from such analysis to successfully identify maintenance actions within a maintenance program. A case study on how maintenance personnel perform when analyzing used engine oils was carried out. Post training interviews established that experienced maintenance personnel struggled to identify a maintenance action from the results of the portable instrument. Hence, further training was created and performed to overcome these difficulties. Therefore, this research has shown there is a deficiency in maintenance training regimes.
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Acknowledgments
The author wishes to express gratitude to the Industry partners that assisted the research by providing used oil samples for testing and to the ACORN research Centre for providing analytical instrumentation for the research. The author also wishes to express gratitude to the Limerick Institute of Technology for funding this research through its Graduate Office Bursary (GRO) bursary.
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Chaplin, A., Hardiman, F., Naughton, D. (2016). Identifying Maintenance Actions Using Portable Lubrication Analytical Instrumentation for Maintenance Application. In: Ao, Si., Yang, GC., Gelman, L. (eds) Transactions on Engineering Technologies. Springer, Singapore. https://doi.org/10.1007/978-981-10-1088-0_23
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DOI: https://doi.org/10.1007/978-981-10-1088-0_23
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