Investigation of Equipment Maintenance Strategies for Maximizing Machine Availability using SAP PM

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.

Authors

Publication Details

Journal
Iconic Research and Engineering Journals
Published
2026-05-08
DOI
https://doi.org/10.64388/irev9i10-1716730
Primary Topic
Reliability and Maintenance Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigation of Equipment Maintenance Strategies for Maximizing Machine Availability using SAP PM

Tamunoiduabia Ibisiki, Collins Burabari ZOR-OL
Iconic Research and Engineering Journals
Reliability and Maintenance Optimization
article

Investigation of Equipment Maintenance Strategies for Maximizing Machine Availability using SAP PM

Tamunoiduabia Ibisiki, Collins Burabari ZOR-OL
article en

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.

Iconic Research and Engineering JournalsVol. 9(10)
Industry, innovation and infrastructure
Openalex Percentile: Top 5%
Reliability and Maintenance Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.