Maintenance and reliability of a municipal bus fleet – a data-centered assessment

Assessment of Conveyor Machine Maintenance Performance in the Filling Area Using MTTR, MTBF, and Availability Analysis

Efficient machinery maintenance is paramount to ensuring continuous production flows and minimizing unexpected asset disruptions in automated manufacturing environments. This study evaluates the operational reliability and maintenance performance of a critical belt-type conveyor machine within the Lithos filling line at PT. Pertamina Lubricants. Utilizing historical breakdown data extracted from the facility's Computerized Maintenance Management System (CMMS), empirical time-centric metrics were calculated across a representative 18-day continuous production period. Within this temporal window, a total of 60 unscheduled mechanical and electrical failure sequences were documented and analysed. Quantitative processing reveals that the conveyor system exhibited an empirical Mean Time to Repair (MTTR) of 26.28 minutes and a Mean Time Between Failures (MTBF) of 225.72 minutes. These structural parameters yield a cumulative operational availability rate of 89.57%. Although the availability index indicates a reasonable baseline of functional readiness, the high breakdown frequency highlights critical system vulnerabilities that cause downstream bottlenecks and degrade overall plant efficiency. To optimize asset lifecycle performance and mitigate micro-stoppages, implementing a structured Cleaning, Lubrication, and Inspection (CLI) schedule within an autonomous maintenance framework is highly recommended. Empowering shop-floor operators to execute initial inspections will systematically enhance conveyor availability and production throughput.

Statistical Failure Analysis and Reliability Indices Estimation in a Medium-Voltage Distribution System

This paper presents a statistical failure analysis of data obtained from the DISPO system for the purpose of evaluating the reliability and maintainability of a medium-voltage distribution network. Failure occurrences and outage durations are analyzed using statistical methods to model reliability behavior and downtime characteristics. Based on the processed data, key reliability and maintainability indicators are determined. Emphasis is placed on maintainability assessment through the evaluation of repair times and their influence on system availability. Standard distribution system performance indices are calculated, including the System Average Interruption Duration Index (SAIDI), the System Average Interruption Frequency Index (SAIFI), Mean Time Between Failures (MTBF), and Mean Time To Repair (MTTR). These indicators enable the identification of critical components and network sections with the greatest impact on overall system performance. The obtained results support condition-based maintenance planning and targeted reliability improvement measures. The proposed approach demonstrates how historical outage records can be systematically utilized to enhance operational decision-making and improve the reliability performance of distribution systems.

PROBABILISTIC ENHANCEMENT OF AN ISLAND NETWORK USING RELIABILITY-CENTERED MAINTENANCE

The maintenance of electrical island networks presents major reliability and performance challenges. Traditional methods often overlook the probabilistic nature of failures, leading to avoidable outages. This study proposes an enhanced Reliability-Centered Maintenance (RCM) framework using FMEA-AHP methodology for island networks. An existing network was modelled in ETAP using equipment data and maintenance history from the IEEE Std-493 Gold Book and the Dangote Petroleum Refinery and Petrochemical (DPRP) Captive Power Plant. ETAP simulations quantified energy losses and annual failure rates. Critical equipment was identified using the Pareto Principle, and Failure Mode and Effect Analysis (FMEA) determined failure modes. The Analytical Hierarchy Process (AHP) prioritized high-impact failures, guiding task selection. Implementing ETAP-based reliability assessment combined with RCM, FMEA, and AHP resulted in a 56.36% reduction in interruption duration and a 64.87% reduction in failure rate. A structured preventive maintenance framework was developed to optimize strategies, reduce costs, and improve system reliability in island networks.

An Integrated IPMS–MAFMA Framework for Improving the Operational Efficiency of Clean Water Distribution Pump Systems

PT. XYZ is a local government-owned company responsible for providing clean water services to the residents of Surabaya. To ensure reliable water distribution, the company must maintain high operational performance of its distribution pump system. However, operational activities are frequently disrupted by equipment failures and inadequate maintenance practices, resulting in reduced efficiency and service reliability. This study aims to improve operational performance and minimize machine failures by integrating the Integrated Performance Measurement System (IPMS) and Multi-Attribute Failure Mode Analysis (MAFMA) at the Central Distribution Pump House. The IPMS method was employed to identify and prioritize Key Performance Indicators (KPIs) requiring performance improvement based on their relative weights. Subsequently, the MAFMA method was applied to identify potential failure modes, evaluate associated risks, and determine appropriate corrective actions. The results indicate that KPI 9, namely the completion of non-routine maintenance work, obtained the highest priority weight of 0.174, indicating that it should be the primary focus for performance improvement. Furthermore, the MAFMA analysis identified a damaged foot valve as the most critical failure mode, with the highest Risk Priority Number (RPN) of 168. Based on these findings, the proposed improvements include developing contingency plans to manage unexpected priority changes and implementing routine inspection and cleaning of pump components every two days to reduce the likelihood of equipment failure. The integration of IPMS and MAFMA provides a systematic approach for enhancing maintenance performance, improving operational reliability, and supporting sustainable clean water services.

MAINTENANCE SOURCING, FLEET AVAILABILITY AND HUMANITARIAN PREPAREDNESS: A 48-MONTH BRAZILIAN MILITARY CASE

This study examines changes in fleet availability and a recorded unit-cost indicator following the transition of vehicle maintenance from an external contractor to an organic Brazilian Air Force maintenance unit, with particular attention to implications for humanitarian preparedness. The analysis covers a 35-vehicle fleet over 48 months, comprising equal 24-month periods before and after the January 2023 transition. Monthly availability, target attainment, and inflation-adjusted unit-cost data were assessed descriptively and through exploratory segmented regression with Newey–West standard errors; monetary values were converted to December 2024 Brazilian reais using the national IPCA consumer price index. Mean fleet availability increased from 62.4% in 2021–2022 to 81.1% in 2023–2024, while the proportion of months meeting the 70% availability target rose from 37.5% to 79.2%. The mean IPCA-adjusted recorded unit-cost indicator was 20.9% higher in the post-transition period. However, because availability was already improving before the transition, segmented regression identified no statistically significant level or slope change attributable to January 2023. Availability nevertheless averaged 85.9% and remained above the 70% target from May through December 2024, coinciding with a period of major flood-response and recovery activities. These findings should therefore be interpreted as descriptive rather than causal. The absence of a comparison fleet, reliance on aggregated monthly data, potential concurrent organizational changes, limitations in cost comparability, and the lack of utilization and mission-output measures constrain causal inference. The study contributes to sustainment and humanitarian logistics research by showing how maintenance-sourcing decisions can be evaluated through mission criticality, asset substitutability, availability, and accounting comparability, while emphasizing that fleet availability represents only one component of broader operational and humanitarian response capacity.

Definition and Properties of Alternative Bus Service Definition and Properties of Alternative Bus Service Reliability Measures at the Stop Level Reliability Measures at the Stop Level