Analysis of Curing Machine Maintenance Using Failure Mode and Effects Analysis (FMEA) and Reliability Centered Maintenance (RCM) Methods Case Study of PT. Krismasindo Printing

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FORMOSA NEWS - Karanganyar - Integrated Maintenance Strategy Cuts Downtime in Printing Industry Curing Machines. Industrial researchers at Duta Bangsa University Surakarta have developed a comprehensive maintenance framework combining Failure Mode and Effects Analysis (FMEA) and Reliability Centered Maintenance (RCM) to eliminate costly unscheduled downtime in printing equipment. The study, conducted by researchers Ditya Alif Firmansyah, Febrina Agusti, and Pitoyo Amrih, was published in July 2026 in the Formosa Journal of Applied Sciences. By identifying critical component failure modes and calculating operational reliability metrics, the research offers a structured strategy to improve machine reliability and optimize industrial productivity in commercial printing operations.

Background and Industrial Relevance
In modern manufacturing, industrial printing facilities rely on continuous production cycles to meet strict customer deadlines and quality standards. Within this workflow, curing machines serve as essential operational units that use heating mechanisms to dry and harden ink on printed materials. Unexpected machine breakdowns disrupt entire supply chains, lower production output, and significantly increase maintenance expenditures. Many commercial printing plants, including PT. Krismasindo Printing in Karanganyar Regency, historically relied on reactive or corrective maintenance repairing machinery only after a failure occurs. This approach frequently leads to repeated failures across mechanical, electrical, and heating subsystems. To solve this, researchers applied a proactive maintenance model to transition plant operations from emergency repairs to systematic, data-driven preventive maintenance.

Research Methodology
The quantitative descriptive study analyzed performance and failure records from PT. Krismasindo Printing across 12 distinct curing machine components from April to June 2026. The engineering team gathered primary data through field observations and interviews with plant technicians and operators, alongside secondary operational logbooks tracking breakdown frequencies, downtime duration, and total operating hours. To establish an optimized maintenance framework, the researchers executed a multi-step analytical process:

• Failure Mode and Effects Analysis (FMEA): Evaluated components using Severity (S), Occurrence (O), and Detection (D) ratings to generate a Risk Priority Number (RPN) for each part.
  
• Reliability Centered Maintenance (RCM): Utilized Logic Tree Analysis (LTA), RCM Decision Worksheets, and Task Selection to map tailored maintenance tasks to high-risk components.
  
• Reliability Metrics Calculations: Calculated Mean Time Between Failure (MTBF) to determine operational lifespan between breakdowns, and Mean Time to Repair (MTTR) to quantify maintenance ease.
  
• Fishbone Diagram Root-Cause Analysis: Categorized underlying failure drivers into five primary domains: Man, Machine, Method, Material, and Environment.
  

Key Findings and Critical Components
The investigation identified 12 failing components during the observation window, pinpointing mechanical drive components as the primary source of operational failure.

• Risk Priority Ranking: Bearings recorded the highest Risk Priority Number ($\text{RPN} = 432$), making them the most critical vulnerability, followed by gearboxes ($\text{RPN} = 336$) and electric motors ($\text{RPN} = 252$).
  
• Failure Frequency and MTBF: Bearings experienced the highest breakdown frequency with 7 recorded failure events, resulting in the shortest Mean Time Between Failure of just 80 hours.
  
• Repair Downtime (MTTR): Gearboxes and electric motors recorded the longest average repair time (MTTR) at 150 minutes per failure event, creating severe operational bottlenecks.
  

The RCM Task Selection yielded three distinct maintenance strategies across the machinery's 12 components: Time Directed (TD) preventive maintenance for 5 components, Condition Directed (CD) predictive maintenance for 4 components, and a combined Condition Directed + Time Directed (CD+TD) approach for 3 critical components, including bearings and temperature controllers.

Real-World Impact and Industry Application
The integration of FMEA and RCM methodologies offers clear economic and operational advantages for manufacturing enterprises. By replacing reactive fix-it-when-it-breaks habits with scheduled maintenance intervals based on precise MTBF metrics, manufacturing facilities can significantly decrease unplanned downtime and extend equipment lifespans. Implementing scheduled lubrication, routine thermal inspections, and condition-based monitoring directly targets the root causes highlighted in the study's Fishbone analysis. Beyond printing companies, this structured framework provides a scalable model for industrial sectors reliant on continuous heating or conveyor systems, optimizing maintenance budgets and safeguarding operational productivity.

Author Profil

Ditya Alif Firmansyah holds an academic degree in industrial engineering and is a researcher affiliated with Duta Bangsa University Surakarta. His expertise focuses on industrial maintenance management, reliability engineering, operations research, and system optimization within manufacturing environments.

Source
Ditya Alif Firmansyah, Febrina Agusti, Pitoyo Amrih: Analysis of Curing Machine Maintenance Using Failure Mode and Effects Analysis (FMEA) and Reliability Centered Maintenance (RCM) Methods Case Study of PT. Krismasindo Printing. Formosa Journal of Applied Sciences (FJAS). Vol. 5, No. 7, Hal. 1547–1554
DOI: https://doi.org/10.55927/fjas.v5i7.82
URL: https://journalfjas.my.id/index.php/fjas