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Investigation of Equipment Maintenance Strategies for Maximizing Machine Availability using SAP PM
Subject area: Science,Engineering and Technology · Area of research: Mechanical Engineering
DOI: https://doi.org/10.64388/IREV9I10-1716730
Abstract
In this study, “Evaluating Equipment Maintenance Strategies for Maximizing Machine Availability Using SAP PM in Manufacturing Plants” was carried out to address the problem of frequent machine downtime and low equipment availability caused by inefficient maintenance practices. Many plants rely heavily on corrective maintenance, which increases cost and reduces machine uptime. The main objective was to determine how each strategy affects machine availability, downtime, and cost. Five key goals included assessing the role of PM, impact of PdM, efficiency of CM, SAP PM implementation challenges, and how different strategies affect performance outcomes. The results are useful for maintenance planners, plant managers, and researchers, offering real values to guide decisions. It is recommended that future work integrate optimization tools and machine learning to refine hybrid strategies for better system reliability and cost.
How to cite this paper
@article{1716730,
author = {Ibisiki, Tamunoiduabia, ZOR-OL, Collins Burabari},
title = {Investigation of Equipment Maintenance Strategies for Maximizing Machine Availability using SAP PM},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {10},
pages = {4245-4251},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1716730.pdf},
abstract = {In this study, “Evaluating Equipment Maintenance Strategies for Maximizing Machine Availability Using SAP PM in Manufacturing Plants” was carried out to address the problem of frequent machine downtime and low equipment availability caused by inefficient maintenance practices. Many plants rely heavily on corrective maintenance, which increases cost and reduces machine uptime. The main objective was to determine how each strategy affects machine availability, downtime, and cost. Five key goals included assessing the role of PM, impact of PdM, efficiency of CM, SAP PM implementation challenges, and how different strategies affect performance outcomes. The results are useful for maintenance planners, plant managers, and researchers, offering real values to guide decisions. It is recommended that future work integrate optimization tools and machine learning to refine hybrid strategies for better system reliability and cost.},
month = {April},
doi = {https://doi.org/10.64388/IREV9I10-1716730}
}