1
Reliability Centered Maintenance (RCM) and Preventive Maintenance (PM) Methods as a Hybrid Maintenance Model: Jordanian Electric Power Generation Company as a Case Study
Issam S. Jalham, Adnan Bashir, Razan Yasser Zarraq • Jordan Journal of Mechanical and Industrial Engineering • 2026 • Scholar alert surfaced 3 Sep 2026
Core SEA pickRCMPower generationMaintenance strategy
The study examines a hybrid approach that combines reliability-centered maintenance thinking with preventive-maintenance methods in a power-generation setting. That makes it directly relevant to engineers deciding which assets deserve fixed-interval tasks and which require consequence- and failure-mode-based maintenance logic.
Practical takeaway: use preventive maintenance as one possible task inside a broader reliability decision process. Asset criticality, functional failure, failure consequences and failure behavior should determine whether a time-based task is justified.
2
Joint scheduling of jobs and preventive maintenance in a flow shop environment to achieve effective maintenance
Subhash P, Tarun Ramesh Gattu, Sohan Singh Thakur, Sachin Karadgi, P. S. Hiremath • Production Engineering • 2026 • Scholar alert surfaced 22 Aug 2026
Core SEA pickMaintenance schedulingProductionOptimization
This work integrates production-job scheduling and preventive-maintenance scheduling rather than treating them as separate planning problems. It uses mathematical and metaheuristic optimization approaches to balance resource utilization with machine reliability.
Practical takeaway: maintenance windows should be planned together with the production plan. A technically correct PPM schedule can still fail operationally if it ignores release windows, production peaks, labor constraints and equipment degradation thresholds.
3
Machine Learning–Based Failure-Risk Profiling and Preventive Maintenance Prioritisation for 11 kV Distribution Feeders Using Operational Data
Kolawole Gideon Ige, Abdulwaheed Musa • Applied Science, Computing, and Energy • 2026 • Published 28 Jul 2026 • Scholar alert surfaced 22 Aug 2026
Core SEA pickElectrical distributionMachine learningRisk prioritization
The paper uses historical operating data and a Random Forest model to estimate feeder failure risk, then converts model outputs into maintenance-priority indicators. The published results describe moderate predictive performance rather than presenting the model as perfect prediction.
Practical takeaway: predictive maintenance becomes useful when model output is translated into an actionable priority. Engineers should keep causal data separation, model validation and false-positive/false-negative consequences visible rather than relying on an opaque risk score.
4
Evaluation of the Effectiveness of a Preventive Maintenance Checklist on Generator Downtime
M. Irwan, S. Suwarni • Jurnal Sains dan Teknik Terapan • 2026 • Scholar alert surfaced 4 Sep 2026
Core SEA pickGeneratorsChecklistsDowntime
The research compares generator downtime before and after implementation of a preventive-maintenance checklist. The central idea is highly practical: a checklist is useful only if it drives consistent inspection and intervention that changes equipment outcomes.
Practical takeaway: evaluate PPM checklists by outcomes such as repeat failures, downtime, defect detection and task effectiveness—not simply by completion percentage. A 100% completed checklist can still be weak if tasks are vague or do not target real failure modes.
5
Reliability-Based Preventive Maintenance Planning of Pressure Regulator Shut-Off Valve Components on CN235 Aircraft
M. Prabowo, A. Anwar • 2026 • Scholar alert surfaced 3 Sep 2026
Core SEA pickReliability-based PMValvesMaintenance intervals
The study applies quantitative reliability analysis to component failure behavior and maintenance-interval recommendations for a pressure-regulator shut-off valve assembly. Although the application is aerospace, the decision logic is transferable to critical valves and components in industrial systems.
Practical takeaway: maintenance intervals should have an evidence trail. Failure history, reliability behavior, safety consequence, inspection detectability and replacement/repair strategy should support the interval instead of inherited calendar frequencies alone.
6
Analysis of Maintenance for The Model 317 Tray Unloader Using The Preventive Maintenance Method at PT. Madukoro Engineering
M. R. Jurdan, A. Sugiyono, M. Aditiya, M. F. Hasan • Technema: Journal of Intelligent Technologies in Engineering • 2026 • Scholar alert surfaced 26 Aug 2026
Core SEA pickIndustrial equipmentPM frequencyMaterial handling
The paper reviews preventive maintenance on a tray-unloading machine and describes a multi-frequency maintenance structure spanning daily, weekly, monthly and annual activities.
Practical takeaway: multi-frequency PM should be built around what actually changes at each time scale. Daily operator checks, technician inspections, periodic measurements and annual intrusive work should not simply repeat the same checklist at different frequencies.
7
Assessment of latent fatigue damage in RC slabs for preventive maintenance
Y. Takahashi, H. E. Joo • 2026 • Scholar alert surfaced 27 Aug 2026
Adjacent researchStructural assetsFatigueCondition-based intervention
This research considers indicators for deciding the timing and scope of preventive intervention based on latent fatigue damage in reinforced-concrete slabs.
Practical takeaway: the broader reliability lesson is to connect maintenance timing to measurable degradation indicators where possible. Condition thresholds can be more defensible than arbitrary calendar intervals when degradation can be monitored reliably.
8
Performance Analysis of a Two-Unit Cold Standby Redundant System with Priority in Operation, Degradation and Preventive Maintenance
R. Rani • 2026 • Scholar alert surfaced 4 Sep 2026
Adjacent researchRedundancyDegradationStandby systems
The paper models a two-unit system where one unit operates and another remains in cold standby, incorporating degradation, inspections and preventive maintenance into the reliability analysis.
Practical takeaway: standby capacity is not automatically reliable capacity. Standby units need proof-testing, changeover verification, preservation controls and maintenance assumptions that reflect how long equipment remains idle.
9
Statistical Analysis of Medical Equipment Failure Patterns and Preventive Maintenance Planning Based on Hospital Operational Data
J. Shimizu, M. Kimura • 2026 • Scholar alert surfaced 22 Aug 2026
Adjacent researchFailure dataStatistical analysisPM planning
This study applies operational failure data to preventive-maintenance planning in medical equipment. The sector differs from industrial plants, but the data-analysis question is familiar: which failure patterns should actually drive maintenance frequency and priority?
Practical takeaway: maintenance history becomes valuable when failure codes, dates, downtime, causes and corrective actions are structured consistently. Poorly coded CMMS data limits both statistical analysis and future AI/ML use.