Enhancing FMEA-Based Risk Prioritization Through the Economic Risk Priority Number (ERPN): A System-Level Analysis of Heavy Industrial Vehicle Failures

Heavy industrial vehicles operating in aluminum smelters are exposed to severe thermal, mechanical, and environmental stresses, which increase the likelihood of failure and unplanned downtime. This study proposes an Economic Risk Priority Number (ERPN) framework to address the limitations of the conventional Risk Priority Number (RPN) used in Failure Mode and Effects Analysis (FMEA). A five-year maintenance dataset (2019–2024), comprising 2303 corrective work orders from 58 heavy equipment units, was analyzed. The classical RPN approach prioritized failure modes mainly according to occurrence and detectability, identifying the wheel and hydraulic subsystems as the most critical. In contrast, the proposed ERPN framework integrates economic impact through maintenance cost, manpower cost, and production loss, resulting in the engine subsystem being ranked as the most critical. The most severe engine failure caused an estimated financial loss of approximately USD 1.92 million due to extended downtime and repair costs. Root cause analysis identified coolant loss, low oil pressure, and excessive vibration as the main contributors to catastrophic engine failure, supported by diagnostic evidence and repeated alarm patterns. Statistical validation performed using the Kruskal–Wallis test confirmed significant differences among subsystem risk distributions for both RPN (χ2 = 846.07, df = 4, p < 0.0001) and ERPN (χ2 = 131.69, df = 4, p < 0.0001). The findings demonstrate that ERPN provides a more economically meaningful framework for maintenance prioritization and offers a practical decision-support tool for reducing operational risk in aluminum smelter fleets.

Authors

Institutions

Publication Details

Journal
Machines
Published
2026-04-27
DOI
https://doi.org/10.3390/machines14050491
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

Enhancing FMEA-Based Risk Prioritization Through the Economic Risk Priority Number (ERPN): A System-Level Analysis of Heavy Industrial Vehicle Failures

Rahizar Ramli, Sudhir Chitrapady Vishweshwara, Ahmed Al Saadi, Ahmad Saifizul
Machines
Reliability and Maintenance Optimization
article

Enhancing FMEA-Based Risk Prioritization Through the Economic Risk Priority Number (ERPN): A System-Level Analysis of Heavy Industrial Vehicle Failures

Rahizar Ramli, Sudhir Chitrapady Vishweshwara, Ahmed Al Saadi, Ahmad Saifizul
article en

Abstract

Heavy industrial vehicles operating in aluminum smelters are exposed to severe thermal, mechanical, and environmental stresses, which increase the likelihood of failure and unplanned downtime. This study proposes an Economic Risk Priority Number (ERPN) framework to address the limitations of the conventional Risk Priority Number (RPN) used in Failure Mode and Effects Analysis (FMEA). A five-year maintenance dataset (2019–2024), comprising 2303 corrective work orders from 58 heavy equipment units, was analyzed. The classical RPN approach prioritized failure modes mainly according to occurrence and detectability, identifying the wheel and hydraulic subsystems as the most critical. In contrast, the proposed ERPN framework integrates economic impact through maintenance cost, manpower cost, and production loss, resulting in the engine subsystem being ranked as the most critical. The most severe engine failure caused an estimated financial loss of approximately USD 1.92 million due to extended downtime and repair costs. Root cause analysis identified coolant loss, low oil pressure, and excessive vibration as the main contributors to catastrophic engine failure, supported by diagnostic evidence and repeated alarm patterns. Statistical validation performed using the Kruskal–Wallis test confirmed significant differences among subsystem risk distributions for both RPN (χ2 = 846.07, df = 4, p < 0.0001) and ERPN (χ2 = 131.69, df = 4, p < 0.0001). The findings demonstrate that ERPN provides a more economically meaningful framework for maintenance prioritization and offers a practical decision-support tool for reducing operational risk in aluminum smelter fleets.

MachinesVol. 14(5)
University Malaya Medical Centre (MY), National University of Science and Technology (ZW), University of Malaya (MY)
Openalex Percentile: Top 4%
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.