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All Journal Jurnal Teknik Desimal: Jurnal Matematika
Joseph Andrew Leo
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Social Sciences

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Analysis of Preventive Maintenance on Heavy Dump Suspension Using Reliability-Centered Maintenance Method Puspa, Sofia Debi; Tono Sukarnoto; Dany Nugraha Tantra; Christina Eni Pujiastuti; Joseph Andrew Leo
Jurnal Teknik Vol 23 No 1 (2025): Jurnal Teknik
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37031/jt.v23i1.512

Abstract

The suspension system on Heavy Dump (HD) vehicles is crucial in maintaining stability, comfort, and reliability when used in harsh environments. HD vehicles have a hydraulic-pneumatic suspension that uses nitrogen gas and oil to overcome the load and vibrations from the road. The suspension maintains vehicle components and protects the load, especially when crossing damaged or bumpy roads at high speed. This study aims to optimize preventive maintenance planning using the Reliability-Centered Maintenance (RCM) method and determine the suspension system's preventive activities to reduce breakdowns. In designing effective preventive maintenance, the RCM approach and related methods, such as FMEA, are used to identify critical machines as the focus of analysis. In addition, a statistical distribution approach is used to determine the optimal maintenance activity interval. Based on the analysis results, it was obtained that the data follows a lognormal distribution where the optimization of preventive maintenance on the suspension component is every 370-hour time interval for each machine working. Changing the time interval increased the reliability value from 34.09% to 93.60% before and after preventive maintenance. Preventive maintenance activities with a time interval of 370 hours to reduce unscheduled breakdowns in the form of adjusting suspension components
Evaluation of Lock Cover and STEM Dimensional Variations on Separation Force Using Multiple Regression and Statistical Process Control Puspa, Sofia Debi; Joko Riyono; Christina Eni Pujiastuti; Sentot Novianto; Larasati Rizky Putri; Ghiffari Awliya Muhammad Ashfania; Joseph Andrew Leo
Desimal: Jurnal Matematika Vol. 9 No. 1 (2026): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v9i1.30842

Abstract

This study addresses a critical limitation in conventional manufacturing analysis by demonstrating that dimensional variation in injection-molded press-fit systems should be interpreted as an interaction-driven phenomenon rather than independent geometric effects. The research focuses on lock stem and cover dimensions produced in a multi-cavity injection molding system, where geometric dependency leads to strong multicollinearity among variables. A quantitative approach was applied using actual production data, including dimensional measurements and separation force testing. Multiple linear regression was employed to model the relationship between geometric parameters and mechanical performance, supported by classical assumption testing and multicollinearity diagnostics. The results indicate a very high coefficient of determination, showing that dimensional variation collectively explains most of the separation force variability. However, severe multicollinearity limits the reliability of individual parameter interpretation and highlights the need for system-level analysis. Statistical Process Control confirms that the process operates within stable limits, while process capability analysis shows compliance with specification requirements. Despite this, variation in separation force persists, indicating high sensitivity to small geometric deviations. These findings emphasize that process stability alone is insufficient to ensure consistent performance. This study introduces an integrated framework combining regression, SPC, and capability analysis, providing both theoretical insight and practical guidance for improving dimensional control in precision manufacturing.
Co-Authors Christina Eni Pujiastuti Dany Nugraha Tantra Ghiffari Awliya Muhammad Ashfania Joko Riyono Larasati Rizky Putri Puspa, Sofia Debi Sentot Novianto Tono Sukarnoto