Crawler Crane Failure Cause Analysis Using Fishbone Diagram, ParetoPrinciple, and Failure Mode Effect Analysis: A Comprehensive Approach toMinimize Downtime and Improve Operational Reliability

Crawler cranes are critical heavy equipment in the construction industry, but they often experience failures that cause downtime and increased costs. This article comprehensively analyses crawler crane failures using three main methods: Fishbone Diagram, Pareto Principle, and Failure Mode and Effect Analysis (FMEA). Failure data for the past two years (January 2022 – September 2024) is analyzed to identify root causes and determine repair priorities. A Fishbone Diagram is used to identify the main causes of failure, which are grouped into four categories: Mechanical, Electrical, Environmental, and Human Error. From this analysis, it is found that mechanical failure is the most dominant cause. This analysis found that mechanical failure is the most dominant cause, mechanical failures account for most failures (60%), followed by electrical failures (33%), with failures in the gearbox and engine overheating being the most significant causes. Furthermore, FMEA evaluates potential failure modes, determines their impacts, and sets mitigation priorities based on the Risk Priority Number (RPN). The results of this study provide a strategic approach to minimize downtime by focusing maintenance efforts on the root causes of failure. This article also offers a new contribution by combining three comprehensive analysis methods not systematically applied to crawler crane maintenance. This research is expected to help improve operational reliability and reduce repair costs in the construction industry.

Authors

Institutions

Publication Details

Journal
Journal of Innovation and Technology
Published
2025-03-01
DOI
https://doi.org/10.61453/joit.v2025no04
Citations
1
Primary Topic
Mechanical Failure Analysis and Simulation
Type
article
Field-Weighted Citation Impact
0.71
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Crawler Crane Failure Cause Analysis Using Fishbone Diagram, ParetoPrinciple, and Failure Mode Effect Analysis: A Comprehensive Approach toMinimize Downtime and Improve Operational Reliability

Saifullah Arief, Yassyir Maulana, Ice Trianiza, Faisal Rahman et al.
1 citations
Journal of Innovation and Technology
Mechanical Failure Analysis and Simulation
0.71
article

Crawler Crane Failure Cause Analysis Using Fishbone Diagram, ParetoPrinciple, and Failure Mode Effect Analysis: A Comprehensive Approach toMinimize Downtime and Improve Operational Reliability

Saifullah Arief, Yassyir Maulana, Ice Trianiza, Faisal Rahman, Firda Herlina
article en
1 citations

Abstract

Crawler cranes are critical heavy equipment in the construction industry, but they often experience failures that cause downtime and increased costs. This article comprehensively analyses crawler crane failures using three main methods: Fishbone Diagram, Pareto Principle, and Failure Mode and Effect Analysis (FMEA). Failure data for the past two years (January 2022 – September 2024) is analyzed to identify root causes and determine repair priorities. A Fishbone Diagram is used to identify the main causes of failure, which are grouped into four categories: Mechanical, Electrical, Environmental, and Human Error. From this analysis, it is found that mechanical failure is the most dominant cause. This analysis found that mechanical failure is the most dominant cause, mechanical failures account for most failures (60%), followed by electrical failures (33%), with failures in the gearbox and engine overheating being the most significant causes. Furthermore, FMEA evaluates potential failure modes, determines their impacts, and sets mitigation priorities based on the Risk Priority Number (RPN). The results of this study provide a strategic approach to minimize downtime by focusing maintenance efforts on the root causes of failure. This article also offers a new contribution by combining three comprehensive analysis methods not systematically applied to crawler crane maintenance. This research is expected to help improve operational reliability and reduce repair costs in the construction industry.

Journal of Innovation and TechnologyVol. 2025(1)
Universitas Islam Kalimantan Muhammad Arsyad Al Banjary (ID)
Openalex Percentile: Top 35%
Mechanical Failure Analysis and Simulation
0.71
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.