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The problem faced is the decline in the performance of a 650 liter/minute centrifugal pump due to wear on components, especially the impeller, rolling bearings, and mechanical seals in supplying process water and clean water in industrial production systems. The planning objective is to obtain a maintenance schedule for a 650 liter/minute centrifugal pump for the operational period of 2026 and the ratio between maintenance costs and profits generated by the machine. The maintenance planning method includes collecting maintenance data from previous maintenance periods, reviewing centrifugal pump specifications, applying the inspection, replace, repair, and overhaul (IRRO) approach, estimating the age and price of components that are expected to be damaged, estimating the cost and duration of dismantling and installing components that have been repaired in accordance with the provisions of the requirements for usable components or replacement parts, scheduling maintenance and repairs, estimating maintenance and repair costs for the 2026 period, and determining the ratio of maintenance costs to profits. The planning results are in the form of a maintenance schedule for the 2026 period worth IDR 4,290,000,-, a maintenance cost to profit ratio of 7.44% and the implications indicate that the machine is still suitable for use and prospective for operations in the next few years.  

Corrective maintenance is one of the maintenance strategies performed after system failures or malfunctions occur, particularly in diesel power plants (PLTD) that play a crucial role in supplying electricity to remote areas such as Jayapura. This study aims to identify the types of failures occurring in diesel engines at the Jayapura PLTD and to evaluate the corrective maintenance actions implemented. Data were collected through direct observation during an internship program, interviews with technicians, and analysis of historical maintenance and failure records. The results indicate that the most common failures occurred in the lubrication system, fuel system, and cooling system. Corrective actions included component repairs, spare part replacements, and system adjustments. The application of timely and appropriate corrective maintenance significantly reduced machine downtime and improved the reliability of the power generation system. This study recommends integrating corrective and preventive maintenance strategies to maximize operational efficiency of the PLTD.

The problem with the coconut grater machine is that the machine has decreased performance after being used for several years, especially in the mechanical components (electric motor, V belt, Pulley, grater knife, hopper) and its electricity. The purpose of maintenance and repair planning is to obtain costs, maintenance and repair schedules for the period 2026, and the ratio of maintenance costs to profit. The maintenance and repair planning method includes collecting previous maintenance data, applying the inspection-replace-repair-overhaul (IRRO) method, evaluating component conditions, predicting component lifespan, predicting labor costs, predicting supporting equipment that will be used in maintenance, predicting the time to replace spare parts or reinstall repaired components, estimating maintenance and repair costs for the 2026 period, and calculating the maintenance cost to profit ratio. The results of maintenance and repair planning obtained maintenance costs for the 2026 period were IDR 957,000 with an estimated coconut grater machine rental rate of IDR 10,000/hour which has the potential to be rented for 900 hours/year, and the maintenance cost to profit ratio was 10.6% which implies that the coconut grater machine with a capacity of 15 kg/hour is still prospective and feasible to use for the next few years.

This study analyzes the maintenance process of the Roll Bending machine used in the wind tower production line at PT Kenertec Power System, Cilegon, Indonesia. The Roll Bending machine plays a crucial role in shaping steel plates into cylindrical shell components, which are later assembled into wind tower sections. The objective of this research is to identify maintenance patterns, types of failures, and improvement strategies to ensure machine reliability and operational efficiency. The research employed observation, interviews with maintenance personnel, and documentation review to collect relevant data. The findings show that the machine experienced multiple failures, mostly related to hydraulic system leaks, PLC programming errors, and component wear such as cylinders, seals, and gear pumps. A significant increase in corrective maintenance activities occurred between August 2023 and April 2024, particularly in February 2024, indicating the need for a more consistent predictive maintenance strategy. The implications of this study highlight that optimized maintenance scheduling and monitoring are essential to reduce downtime, avoid production delays, and maintain product quality. This research is expected to support maintenance decision-making and contribute to the improvement of industrial machine reliability in wind tower manufacturing operations.

The problem with the sugarcane press machine is a decrease in performance in sugarcane pressing because it has been used since 2020 with an initial price of IDR 3,000,000, which is predicted to be IDR 5,500,000 in 2025 which occurs in the main components of the roler mill, V-belt, and bearings. The purpose of scheduling replacements and repairs is to obtain a schedule, estimated maintenance costs, and the ratio of replacement and repair costs to the profit of renting a sugarcane press for the period 2026. The scheduling method includes collecting data on the use of the sugarcane press machine, a list of replacements for 5 components for roler mills, V-belts, bearings, gasoline motor tanks, and engine frames from 34 components, component prices, estimated labor costs, equipment costs, supporting material costs, application of the inspection, replace, repair, and overhaul (IRRO) method, scheduling replacements and repairs, and calculating the ratio of replacement costs to profits. The results of the replacement and repair scheduling are in the form of maintenance costs of IDR 958,000, with a rate of IDR 10,000/hour for 588 hours/year, resulting in a profit of IDR 5,880,000, and a ratio of maintenance and repair costs to profit of 0.16%.

Technological advancements in manufacturing have greatly improved production efficiency, particularly through the use of advanced machinery. As key components of industrial operations, machines must operate optimally to meet production targets, often requiring continuous use. To maintain performance and reliability, regular maintenance in accordance with Standard Operating Procedures (SOPs) is essential. This study analyzes the maintenance management system at PT. XYZ, focusing on the Komatsu OBS-25T Power Press machine. The research evaluates the Preventive Maintenance strategy using Mean Time Between Failure (MTBF) and Mean Time To Repair (MTTR) as key performance indicators. The results show that the monthly maintenance schedule is effective. Between January 1 and April 1, 2024, several component failures occurred, including lamp, roll feeder, hand sensor, oil flow, memory slide, alarm No. 11, conveyor belt, and uncoiler malfunctions. The total MTBF was 171.387 minutes (average 13.183 minutes), and the total MTTR was 1.950 minutes (average 150 minutes). The machine of availability rate reached 99%, demonstrating high operational efficiency and effective maintenance management.

The Field Work Practice (PKN) carried out at PT MK Prima Indonesia focused on the implementation of periodic maintenance practices for the premoulding hydraulic press machine as an effort to maintain machine performance and operational lifespan. The main activities included identifying critical components such as the hydraulic system, valves, pressure hoses, and oil filters; conducting direct observation of common disruptions; and performing daily maintenance checklists that covered pressure monitoring, operating temperature, leakage detection, machine cleanliness, and lubrication conditions. Comprehensive cleaning procedures, condition-based filter replacement, and functional testing were also conducted to ensure reliability and safety in the production process. The implementation methods involved participatory observation, interviews with technicians regarding common failure patterns, visual and functional inspections, as well as the use of structured checklists supported by inspection documentation. The results indicate a significant decrease in the frequency of disturbances caused by leaks and oil contamination, improved compliance with routine inspection procedures, and enhanced machine readiness during operations. The introduction of structured documentation and simple technical training further improved technicians’ ability to detect early signs of abnormalities in the hydraulic system. As a recommendation, the company is advised to strengthen the use of digital recording systems, adjust filter replacement intervals based on actual machine conditions, and implement regular training programs focusing on contamination control and predictive maintenance.

The Field Work Practice (PKN) carried out at PT MK Prima Indonesia focused on the implementation of periodic maintenance practices for the premoulding hydraulic press machine as an effort to maintain machine performance and operational lifespan. The main activities included identifying critical components such as the hydraulic system, valves, pressure hoses, and oil filters; conducting direct observation of common disruptions; and performing daily maintenance checklists that covered pressure monitoring, operating temperature, leakage detection, machine cleanliness, and lubrication conditions. Comprehensive cleaning procedures, condition-based filter replacement, and functional testing were also conducted to ensure reliability and safety in the production process. The implementation methods involved participatory observation, interviews with technicians regarding common failure patterns, visual and functional inspections, as well as the use of structured checklists supported by inspection documentation. The results indicate a significant decrease in the frequency of disturbances caused by leaks and oil contamination, improved compliance with routine inspection procedures, and enhanced machine readiness during operations. The introduction of structured documentation and simple technical training further improved technicians’ ability to detect early signs of abnormalities in the hydraulic system. As a recommendation, the company is advised to strengthen the use of digital recording systems, adjust filter replacement intervals based on actual machine conditions, and implement regular training programs focusing on contamination control and predictive maintenance.

This study analyzes failures in the bending machine at PT. XYZ and determines maintenance priorities to reduce downtime and improve production efficiency. The company often faces repeated breakdowns, especially in hydraulic and control components, which negatively impact productivity. To address these issues, the research applies Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis (FTA). The study employs a descriptive qualitative approach using downtime and repair data from September 2024 to February 2025. FMEA was conducted to identify failure modes, effects, and causes, and to calculate the Risk Priority Number (RPN) as a basis for prioritization. FTA was then applied to trace root causes by mapping logical relationships among contributing factors leading to the top event. Recommendations were formulated with the 5W+1H method to propose preventive maintenance actions. The results indicate that the hydraulic valve is the most critical component, with an RPN value of 504 due to oil contamination. The main causes include damaged filters, improper oil usage, and lack of a cooling system. The hydraulic cylinder seal and back gauge were also found to contribute significantly to machine failures. FTA analysis revealed root causes such as inadequate maintenance procedures, unsuitable materials, and insufficient inspections. The proposed improvements involve regular replacement of oil filters, structured lubrication schedules, installation of oil coolers, and technician training to strengthen compliance with standard procedures. Overall, the integration of FMEA and FTA provides a systematic approach to identify critical components and root causes, enabling PT. XYZ to implement preventive strategies that minimize failures, reduce downtime, and improve bending machine performance sustainably.

PT. YGI, an automotive manufacturing company, uses the Press Injection GB-36 machine in its production process. However, this machine frequently experiences failures, causing high downtime and reduced production efficiency. This study aims to identify the types of failures, determine the most critical components, and propose a maintenance system using the Reliability Centered Maintenance (RCM) approach. The method used is descriptive qualitative, involving FMEA (Failure Mode and Effect Analysis), Logic Tree Analysis (LTA), and maintenance action selection. Data were collected through observations, historical failure documentation, and interviews. The analysis results indicate that components such as the injection nozzle, heating, and clamping are the most critical, contributing over 80% of total failures based on Pareto analysis and the highest RPN values in FMEA. Proposed maintenance actions include Condition Directed and Time Directed approaches. Additionally, the maintenance system is supplemented with standard operating procedures (SOP) and routine inspection schedules to improve machine reliability and reduce production downtime. This study is expected to enhance the efficiency and productivity of the Press Injection GB-36 machine at PT. YGI through the appropriate implementation of RCM.

Maintenance and repair work in a building or structure is not only in low places, but also in high places which require assistive devices. The assistive device in question is scaffolding. The design of this scaffolding begins with a literature study followed by data collection in the Mechanical Engineering Department of the Semarang State Polytechnic to obtain data on the need for height assistive devices which are used as a reference for making electric scaffolding. The purpose of this study is to design an electric scaffolding with a capacity of 300 kg and to perform the performance of the electric scaffolding made. After the design of the electric scaffolding, the dimensions of the equipment were obtained, namely 1000 mm x 1500 mm x 2000 mm and specifications that can lift goods with a maximum height of 5 m, a minimum height of 0.35 m, a maximum load of 300 kg and an AC 220 V electric hoist drive. Based on the results of the performance test, in this case the test data was taken from the weight of the load that the machine can lift based on the travel time when the machine moves up and down. The load weight of 300 kg with electric scaffolding was covered in 27.44 seconds when going up and 21.02 seconds when moving down.

This research aims to identify potential hazards and assess the level of fire risk in a textile company located in Sukoharjo Regency using the Hazard Identification, Risk Assessment, and Risk Control (HIRARC) method. The research background is based on the high fire hazard potential in the textile industry due to the use of flammable chemicals, high operating temperatures, and the accumulation of combustible fibers and textile dust. A descriptive research approach was applied through field observations, interviews with workers and the OHS team, and technical document analysis. The results showed that the highest risk levels were found in the dyeing process, electrical panel room, and machine maintenance activities (welding/repair), with risk scores reaching 20 (high category). The main contributing factors included non-standard electrical installations, poor ventilation, and unsafe work behavior. Risk control strategies are recommended through technical, administrative, and behavioral approaches, including smoke detection systems, routine evacuation training, and the reinforcement of safety culture. The implementation of these measures is expected to improve the effectiveness of occupational health and safety management systems and reduce the potential for fire incidents in the textile industry.

Amphibian Cessna 172 SP is an aircraft designed to operate in aquatic environments and is frequently exposed to seawater, which is highly corrosive. Such exposure poses a serious issue of corrosion affecting both the structure and components of the aircraft, particularly the floats, lower fuselage, and propeller. Corrosion not only reduces the quality and integrity of the material but also potentially compromises flight safety and increases maintenance costs. This study aims to analyze the causes of corrosion on the Seaplane Amphibian Cessna 172 SP using the fishbone diagram to identify the main contributing factors, including material, method, environment, manpower, and machine. In addition, the 5W+1H approach is employed to examine the problem in greater detail and develop preventive strategies. The results of the analysis indicate that the dominant factors causing corrosion are the high intensity of direct contact with seawater, suboptimal cleaning processes due to limited manpower, and the use of cleaning agents not fully compatible with aircraft materials. Mitigation efforts include implementing more effective cleaning procedures, applying anti-corrosion chemicals such as AeroShell Fluid 41, Bonderite Turco S.S.2, Ardrox AV-15, CorrosionX, Toolmates Dry Film Lubricant 6075, and Ultra Tef-Gel, as well as conducting scheduled inspections at specific intervals. This research is expected to provide more appropriate preventive strategies to extend the service life of the aircraft structure while maintaining both operational safety and efficiency.

The purpose of this research is to use the six sigma approach to assess the quality of cracker manufacturing at UD. Palapa in Nganjuk Regency. This technology was chosen because it allows for quantitative measurement and analysis of product defect levels, as well as the identification of defect-causing variables. The study was carried out using the DMAIC (Define, Measure, Analyze, Improve, Control) steps and statistical methods such as Pareto diagrams, fishbone diagrams, and C-chart control charts. According to the research, the cracker manufacturing process at UD. Palapa has an average sigma value of 2.74, which is still below the six sigma (6σ) threshold.  This figure implies that the product fault rate remains fairly high.  The most common forms of faults are irregular shape and uneven thickness, which are mostly produced by machine, human, process, and raw material problems. C-chart analysis reveals that most processes are still under control, while there are a few spots beyond the control boundaries that indicate unique variances. Based on these data, it is possible to infer that UD. Palapa's quality control system is still reactive and has to be improved in order to be more proactive. Routine equipment maintenance, operator training, the introduction of standard operating procedures (SOP), and more stringent raw material selection are all possible efforts. Six Sigma deployment has been shown to provide a full view of production quality conditions, as well as a foundation for future continuous improvement programs.

This study aims to analyze the effect of transformer oil purification on oil breakdown voltage and evaluate its benefits in maintaining transformer performance and reliability. Oil purification is a crucial preventive maintenance step to preserve insulation quality and prevent operational failures caused by reduced dielectric properties. The study was conducted through several stages, including data collection, oil purification, measurement of breakdown voltage before and after purification, and evaluation of results. Data collection involved measuring the oil’s electrical properties according to SPLN 49-1:1982 and observing results using a Break Down Voltage (BDV) test. Purification of a Trafindo 400 kVA transformer was performed through visual inspection, connecting the inlet and outlet hoses to the purification machine, and circulating the oil until the breakdown voltage met the required standards. Results indicated that the oil breakdown voltage before purification was below standard due to reduced insulation quality caused by water contamination, charcoal particles, thermal degradation, and dissolved gases that weakened dielectric properties. Additional factors such as electrical stress, mechanical stress, and excessive loading also contributed to insulation deterioration. After purification, the oil breakdown voltage increased significantly to meet the standard of >30 kV/2.5 mm, demonstrating that purification effectively restores the oil’s insulating capacity and supports optimal transformer performance. Analysis confirms that the transformer oil remains suitable for use, and routine annual purification is recommended to maintain reliability, efficiency, and operational performance. This study highlights oil purification as an effective preventive measure for transformer stability, extending operational life, and reducing the risk of insulation failure. The findings provide valuable guidance for transformer maintenance in the electricity industry, ensuring safe and optimal long-term operation.

Electronic Medical Records (EMR) are medical records compiled and stored through an electronic system used to support the provision of healthcare services. The implementation of EMR facilitates faster, more practical, and integrated patient data recording. Electronic Medical Records (EMR) are designed to improve the efficiency, accessibility, and accuracy of patient information within healthcare institutions. This study used a qualitative descriptive approach with a case study design through interviews to assess the readiness of EMR implementation in terms of the 5M management aspects (Man, Money, Material, Machine, Method) at Muhammadiyah General Hospital, Ponorogo Regency. The study sample consisted of 27 healthcare workers selected using a purposive sampling technique. The case study design allowed researchers to capture in-depth insights from healthcare workers directly involved in EMR implementation. The results showed that from the Man element, most healthcare workers were ready to use EMR, as indicated by their comfort and skills in operating the application. In the Money element, there is a system maintenance budget and support for EMR development in the inpatient unit and the Emergency Room. The Material element indicates the availability of adequate software, while the Machine element includes computer devices, internet connections, and a stable server to support users. These technological resources ensure a user-friendly and reliable system. The final element, Method, is demonstrated by the existence of clear SOPs and workflows, enabling healthcare workers to understand and effectively follow the EMR implementation process. Overall, the findings indicate that the hospital is institutionally prepared for EMR adoption.    

PT Sinar Semesta is a company engaged in the metal casting industry. In its production process, defects were still found during the period from March 2023 to February 2024. Out of a total production of 4,950 units, there were 1,004 defective units, consisting of 534 units with flow error defects and 470 units with porosity defects. To address this issue, quality control methods such as Statistical Quality Control (SQC) and Fault Tree Analysis (FTA) are necessary to minimize product defects, improve quality, and maintain high standards. Based on the Pareto diagram, the most dominant defect percentages are flow error defects at 53.19% and porosity defects at 46.81%. The control chart shows points beyond the upper control limit (UCL) occurring in April with 148 units, May with 145 units, and October with 149 units, and below the lower control limit (LCL) occurring in August with 35 units, January with 36 units, and February with 32 units. Based on the fault tree analysis, five main factors causing defects were identified: human, machine, raw material, method, and environment. Proposed improvements include operator training, routine machine maintenance, accurate raw material measurement, use of high-quality raw materials, pre-pouring temperature checks, increased supervision, and environmental improvements.

The Paiton Steam Power Plant (PLTU) is one of the main sources of electrical energy in East Java, which plays a vital role in maintaining a sustainable electricity supply. The reliability of generator units is a key element in maintaining stable energy distribution. However, the high frequency of sudden generator failures poses serious challenges, such as increased downtime and increased maintenance costs. To address these challenges, this study aims to design a generator maintenance prediction model based on the Naive Bayes algorithm with a predictive maintenance approach. This study uses historical maintenance data and key sensor parameters such as temperature, oil pressure, and vibration as input. The data is analyzed through several stages, namely data preprocessing, selection of relevant features, and labeling generator conditions into three categories: Normal, Warning, and Critical. The Naive Bayes model is trained to classify the data probabilistically to generate predictions of future generator conditions. Model evaluation using accuracy metrics and a confusion matrix shows that the model successfully achieved an accuracy rate of 89% and was able to provide early warnings of potential failures up to 3 days before failure occurs. The implementation of this system is expected to support the shift in maintenance strategies from reactive and scheduled systems to data-driven predictive systems. Implementing failure predictions allows the technical team at the Paiton PLTU to conduct planned maintenance, avoid sudden disruptions, and extend equipment lifespan. Thus, this model has the potential to reduce operational downtime by up to 25%, while providing significant savings in operational and logistics costs. This research also shows that integrating machine learning technology into energy facility management can improve the efficiency and resilience of the overall electric power system.

This study aims to analyze the effectiveness of preventive maintenance on the Simplex machine at PT. XYZ by applying the Overall Equipment Effectiveness (OEE) method and identifying the primary causes of production losses through the Six Big Losses framework. Preventive maintenance is an important strategy to ensure machine reliability, reduce downtime, and improve production efficiency. OEE is a widely recognized performance measurement tool consisting of three key indicators: Availability, Performance, and Quality. These indicators collectively reflect the overall effectiveness of equipment in supporting the production process. The results of this study indicate that the OEE value of the Simplex machine is 79%, which remains below the world-class benchmark of 85% as recommended by the Japan Institute of Plant Maintenance (JIPM). This finding suggests that the machine’s performance has not yet reached the optimal standard and requires improvement efforts. Further analysis using the Six Big Losses approach reveals that the most significant contributors to reduced machine effectiveness are equipment failure and idling or minor stoppages. These two categories account for the majority of productivity losses, thereby affecting both machine utilization and production output. To further explore the underlying issues, a root cause analysis was conducted using a fishbone diagram, which enabled the identification of several critical factors related to human resources, methods, machines, materials, environment, and measurement systems. Based on this analysis, improvement proposals were developed through the 5W+1H method, providing a systematic strategy to enhance preventive maintenance practices. The recommended actions include scheduling more frequent inspections, improving operator training, upgrading spare parts management, and implementing stricter monitoring of machine performance. In conclusion, this study highlights the importance of continuous preventive maintenance to optimize machine productivity and reduce unplanned downtime. By adopting the proposed improvement strategies, PT. XYZ can increase the effectiveness of its Simplex machine, moving

The continuous operation of airlock machines in wheat milling facilities plays a critical role in the material handling system, especially in the transfer of grain from ships to silo storage. At PT XYZ, the airlock machine has been identified as the equipment with the highest frequency of downtime over a three-month observation period, leading to significant disruptions in production flow and increased corrective maintenance costs. This study aims to analyze the failure modes of the airlock machine using the Failure Mode and Effect Analysis (FMEA) method and to develop preventive maintenance recommendations based on the highest Risk Priority Number (RPN) values. The research adopts a quantitative descriptive approach, involving field observations, interviews with maintenance personnel, historical breakdown analysis, and machine technical documentation review. The FMEA results indicate that the seal, gear, and bearing are the most critical components, with RPN values of 224, 210, and 192, respectively. These components are prioritized for preventive actions such as regular seal replacement, scheduled lubrication, gear inspections, and motor monitoring. Simulation of the proposed maintenance strategy demonstrates a 66.7% reduction in downtime, from 18 hours to 6 hours per month, and a 43.7% reduction in total maintenance costs, from Rp 9,034,500 to Rp 5,087,500 monthly. These results validate the effectiveness of the FMEA method in identifying risk-prone components and optimizing maintenance planning. It is recommended that PT XYZ institutionalize periodic FMEA updates and establish a cross-functional analysis team to continuously monitor and improve equipment reliability.