Breakdown Maintenance Research Articles

Analysis of disruption factors at PT PLN Indonesia Power PLTU Banten 2 Labuan PGU using a grounded theory approach and pareto analysis of lean kaizen

The reliable and efficient availability of electricity is a crucial factor in economic and social development. PT PLN (Persero), through its subsidiary PT PLN Indonesia Power, is responsible for providing electricity, including operating the 2x300 MW Banten 2 Labuan coal-fired power plant. However, in 2022, the Banten 2 Labuan plant experienced 28 disruptions, leading to a decrease in production capacity from 4,838.4 GWH to 4,259.716 GWH per year. This study aimed to identify the factors causing these disruptions and the decline in electricity production capacity. A qualitative approach using the Grounded Theory method was employed, involving in-depth interviews with the Assistant Manager of Operation Planning and Control, the Assistant Manager of Maintenance Planning and Control, and the Assistant Manager of Public Relations and CSR of the Banten 2 Labuan plant, as well as field observations and document studies. Through open coding, axial coding, and selective coding, three themes emerged as causes of disruption: internal factors (frequency 14), external factors (frequency 9), and force majeure (frequency 4). Pareto analysis revealed internal factors as the most dominant, contributing to 51.9% of the disruptions, with equipment failure (frequency 11) being the most significant internal factor, contributing 40.7% to the total disruptions. Consequently, optimization of maintenance strategies, improvement of human resource competencies, and the application of Lean Manufacturing principles, including Predictive Maintenance, Preventive Maintenance, Corrective Maintenance, and Breakdown Maintenance within the framework of Reliability Engineering and Maintenance Management, are necessary to enhance the operational reliability of the Banten 2 Labuan power plant.

Analysis of Overall Equipment Effectiveness (OEE) as an Effort to Increase The Productivity Filling Line of Lithos Packaging Lubricant

This research was conducted at a company engaged in the lubricants business. This study examines the filling station lithos packaging. The lithos packaging filling station consists of 6 filling lines (FL), namely FL-1, FL-2, FL-3, FL-4, FL-5, and FL-6. From each filling, the line will be observed and analyzed in the format of the automation machine program. Based on the observations and analysis, it was found that FL-4 has an availability rate, performance rate, and quality rate below standard, so it is necessary to identify the cause of the low Overall Equipment Effectiveness (OEE) value of FL-4. This study analyzes the factors causing the low Overall Equipment Effectiveness (OEE) score on FL-4 using Six Big Losses and Fishbone diagrams. From the research results, it was found that several factors caused the less productive FL-4, namely breakdown losses with a value of 48%, setup and adjustment losses with a value of 3%, idling and minor stoppages with a value of 7%, reduced speed losses with a value of 41%, and defect losses with a value of 1%. An analysis was carried out using a fishbone diagram to determine the root cause of the high value of breakdown losses, reduced speed losses followed by idle and minor stoppage losses, and setup and adjustment losses. Based on the fishbone diagram, it was found that the factors causing the FL-4's unproductivity in terms of machine factors, method factors, human factors, material factors, and environmental factors. The causes of unproductive FL-4 are damage to the machine, downtime, the operator's less responsiveness to machine problems, operator expertise, decreased work ethic, defective materials, late material stocks, and hot room temperatures. Based on this, the proposed improvements given are to schedule machine maintenance at a specified time (preventive maintenance), not by the factor of damage (breakdown maintenance), make data guide for product change for each machine and attach it to each machine in full so that This downtime can be reduced, placing technical operators who focus on each filling line at least one technical operator, to speed up downtime and not disrupt the production process, add fans to speed up air circulation to reduce heat in the area and change material suppliers to get better quality.

RCM based optimization of maintenance strategies for marine diesel engine using genetic algorithms

In the modern world the availability of the machinery for any industry is of utmost importance. It is the right maintenance at right time which keeps these machineries available for their jobs. The primary goal of maintenance is to avoid or mitigate consequences of failure of equipment. There are various types of maintenance schemes available such as breakdown maintenance, preventive maintenance, condition based maintenance etc. Out of all these schemes Reliability Centred Maintenance (RCM) is most recent one and the application of which will enhance the productivity and availability. RCM ensures better system uptime along with understanding of risk involved. RCM has been used in various industries, however, it is very less explored and utilized in marine operations.Hence in the present study maintenance schemes of a marine diesel engine has been considered for optimization using RCM.Failure Modes and Effects Analysis and Fault Tree Analysis (FTA)are some of the basic steps involved in RCM. Due to the scarcity of reliability data particularly in the marine environment some of the components data had to be estimated based on the operating experience. As FTA is based on binary state perspective, assuming the system exist in either functioning or failed state, some of the components (whose performance varies with time and degrades) cannot be modeled using FTA. Hence, in this paper reliability modeling of performance degraded components is dealt with Markov models and the required data is evaluated from condition monitoring techniques. After obtaining the availability of the marine diesel engine, based on the importance ranking, critical components have been obtained for optimizing the maintenance schedules. In this paper genetic algorithm approach has been used for optimization. The results obtained have been compared and new maintenance scheme has been proposed.

Market segmentation using predictive technology and shared-service contracts

‘Shared-service contracts’ provided by Original Equipment Manufacturers (OEMs) are a standard feature of capital-intensive, long-life products. In such contracts, OEMs assume a predetermined portion of the products’ long-term failure opportunity costs by conducting routine and breakdown maintenance tasks for their customers. Recently, OEMs have been utilizing predictive technology to improve service productivity. It enables OEMs to reduce failure opportunity costs mentioned while using the data generated to develop products at lower costs. We extend the adverse selection framework to model the market segmentation of products offered with shared-service contracts and predictive technology. Our model includes: (i) the cost of product development and operation, (ii) the failure opportunity cost driven by long-term product failures, (iii) the cost of designing product reliability, and (iv) the cost of incorporating predictive technology, which reduces the first two cost components. Here, the OEM targets a basic and a premium offering at their respective customer types. We find that using predictive technology improves the quality and price of OEM products, thereby increasing their profitability. However, predictive technology enables the OEM to design a product line with lower reliability. In addition, the OEM is more likely to choose a ‘premium-only’ strategy when predictive technology is present.

TECHNICAL AND ECONOMICAL BENEFITS OF AVIATION CBM IN MAINTENANCE, REPAIR & OVERHAUL (MRO) - REVIEW

Maintenance along with its technical and management activities during repair periods has impact on a product or an asset’s economic factors. Maintenance plans have been divided into several categories, including condition based maintenance - CBM, preventative maintenance, and breakdown maintenance. While preventative maintenance frequently inspects a product at predetermined intervals to avoid abnormalities, breakdown maintenance is performed once certain issues, such as product breakdowns, are discovered. All these require higher cost values and passive in avoiding defects ahead. The contents of this paper are concerning CBM in technical systems. It has also been shown that the traditional maintenance techniques, corrective and preventive, are very costly. With CBM one utilizes predictive maintenance, i.e. perform maintenance based upon need. One assesses the condition of the assets and makes judgments whether or not maintenance should be performed. This indicates that the maintenance intervals will be decided dynamically. Vibrations, temperature, oil, acoustic analysis etc. are some of the basic parameters that will reveal the condition. There are also just a few areas in the industry where CBM (or possibly even just condition monitoring) have gained acceptance.

Comparison Study On Pinch-Hitting Vibration Signal Analysis for Automotive Bearing: I-KazTM and I-Kaz 3D

Rotating machines are now an essential part of the automotive industry. Meanwhile, a bearing is playing the most important component of rotating machinery. To sustain the system's smooth running, maintenance methods such as preventive maintenance, breakdown maintenance, and predictive maintenance are used. Under preventive maintenance, vibration analysis is used to diagnose machines bearing faults. The main objective is to recognize bearing defects in a mechanical device by acquiring signals from the bearing using data acquisition hardware. This analysis is conducted under various load torque conditions, speeds, and defect types. A modular hardware configuration consisting of an accelerometer acquires the vibration signal. The signals are analyzed by using I-kazTM and I-kaz 3D signal analysis and its main objective is to observe the degree of dispersion data from its mean point. This analysis resolves the issues associated with time domain analysis. This pinch-hitting analysis research was conducted in two stages. The first stage is an experimental process that uses 3 types of bearings, the healthy (BL), inner race fault (IRF), and defect at outer race (ORF) bearing on the Machine Fault Simulator and forces with a different type of speed (1000, 1500 and 2500 rpm) and load variation (0.0564, 0.564 and 1.1298 N-m). In the second stage, computing the coefficient value and plots of signal’s I-kazTM and I-kaz 3D based on the bearings type were done accordingly. As a result, the analysis for detecting inner race fault, the deviation percentage averages calculation obtained the I-kazTM coefficient shows a better result with 96.86% by comparing to the I-kaz 3D that achieves 94.20%. Similarly, for the outer race defect, I-kazTM lead with 65.40% compared to I-kaz 3D with only 54.82%.

Hydrogen defect acoustic emission recognition by deep learning neural network

Hydrogen attack is the major failure cause of hydrogen equipment breakdown maintenance. Especially, common problems like cracks frequently occur but are challenging to find while operating, presenting an issue for safety and production. In the process of hydrogen damage evolution, a method for defect state recognition is proposed in this paper. Acoustic emission (AE) technology is used for inspecting the entire hydrogen charging process. The characteristic parameters including the counts and duration of the AE signals are first preprocessed, and the current damage states such as the dislocation propagation, and the occurrence of cracks are identified. Then, a deep learning convolutional neural network is used to create a hydrogen defect recognition (HDR) model with the input of a short-time Fourier transform for the feature vector extraction of various damage status AE signals. Finally, the hydrogen defect recognition experiment revealed that HDR is better in classification accuracy at 98.37% due to dislocation propagation and cracks identification. The study can provide an online damage recognition approach for damage state early warning and evaluation to guarantee hydrogen equipment safety operation.

Total Productive Maintenance Strategy to Increase Overall Equipment Effectiveness of Integrated Filling Machine N2 Vaccine Production Pt. Xyz

In the midst of production process to fulfilling the needs of n2 vaccine, several problems occur and cause the production process to be hampered. The high frequency of breakdowns that occurred became problems that results in longer production process and some products become rejected and cannot be absorbed as a whole to meet the production needs. Preventive maintenance that have been conducted so far are considered not optimal because there are more breakdown maintenance than preventive maintenance. History of the breakdown shows that 35% of the total number of production batches experiences failure of the machine in the production process experiences failure of the production process. The results of the study using quantitative analysis show that the OEE of the integrated Filling Machine is only 55%, far below the ideal OEE standard of 95%. A qualitative analysis also conducted to further explores the cause of the bottlenecks in the production process which involves the production and maintenance unit. Study and analyses are conducted to find the root cause of high disturbances that results in losses and obstacle to production process. By using current reality tree, found that the main cause of the bottleneck in the production process on the high number of the breakdown in the Integrated Filling Machine is lack in maintenance activity which the preventive maintenance that conducted doesn’t have clear procedure then coupled with the maintenance team’s habit that prefer to work in breakdown maintenance than preventive maintenance. To solve the problem three alternative solutions are prepared to be choose. The alternative solutions are Autonomous Maintenance, Planned Maintenance, and Principal’s service agreement. All of the alternative solution is selected with consideration of production needs with their respected advantages and disadvantages. Of the three alternative solutions provided, Analytical Hierarchy process will be conducted to determine which alternative is more likely to be implemented. Planned maintenance was chosen as the best solution that meet the needs of each stakeholder with the most mitigable risks and has advantages that can solve the problems that occur.

Research Progress and Development Trend of Prognostics and Health Management Key Technologies for Equipment Diesel Engine

The diesel engine, as the main power source of equipment, faces practical problems in the maintenance process, such as difficulty in fault location and a lack of preventive maintenance techniques. Currently, breakdown maintenance and cyclical preventive maintenance are the main means of maintenance support after a diesel engine failure, but these methods require professional maintenance personnel to carry out manual fault diagnosis, which is time-consuming. Prognostics and health management (PHM), as a new technology in the field of equipment maintenance support, has significant advantages in improving equipment reliability and safety, enhancing equipment maintenance support capability, and reducing maintenance support costs. In view of this, when introducing PHM into diesel engine maintenance support, the research progress and development trend of the key technologies of PHM for diesel engines are carried out with the objective of achieving precise maintenance and scientific management of diesel engines, and the key technologies demand traction. Firstly, the development history of PHM technology is reviewed, and its basic concept and main functions are introduced. Secondly, the system architecture of PHM for diesel engines is constructed, and its key technologies are summarized. Then, the research progress in the field of PHM for diesel engines is reviewed from four aspects: data acquisition, data processing, fault diagnosis, and health status assessment. Finally, the challenges faced by diesel engine PHM in engineering applications are analyzed, effective solutions to address these challenges are explored, and the future development trend is foreseen.

Effect of Carbide Orientation on Wear Characteristics of High-Alloy Wear-Resistant Cast Irons

Both erosive and abrasive wear are common in mechanical systems and moving components in industrial production. Once they occur in machine parts, the task of breakdown maintenance should be carried out, leading to high production costs. Previous research has shown that high-chromium cast iron (HCCI), a commonly used wear-resistant material, experiences repeated particle impacts that break up the chromium carbides (M7C3) on its surface, resulting in the formation of fine fracture carbides. It has been reported that erosion wear occurs progressively due to the shedding of protrusions caused by the plastic deformation of the material’s matrix. Thus, the erosion wear characteristics of a material are strongly affected by carbides, which come in various shapes and can affect resistance. This research examined the orientation of carbides on the microstructure and their effects on erosion and abrasion properties. The wear tests showed that 27 wt.% chromium content high-alloy cast irons showed the best wear resistance properties due to the coarse strips of M7C3 carbides that effectively suppressed wear propagation. Additionally, the M2C carbides crystallized around the M7C3 carbides which support the M7C3 carbide to reduce plastic deformation and carbide peel-out. Consequently, the wear resistance properties of this material are significantly improved.

Machine Maintenance Type and Quality of Output: Evidence from Ghanaian Manufacturing Firms

The need to manage machine maintenance effectively has gained more importance due to the high rate of changing operational technologies, changing market demands, increased emphasis on employee safety, and new environmental legislation. To demonstrate the purpose of maintenance in the manufacturing value chain, the study sought to investigate the relationship between machine maintenance type and quality of output as well as to establish whether machine maintenance contributes to quality of output among Ghanaian manufacturing firms. Data was collected from 150 manufacturing firms in Tema and Accra Metropolis by using questionnaire and analyzed with SPSS and SmartPLS software. The findings showed significantly direct relationship between all the maintenance types, except corrective maintenance, and quality of output. Therefore, if a company minimizes breakdown maintenance, quality defects are also minimized. Hence, adopting preventive maintenance help reduce cost of repairs and unplanned stoppages in the production process.

Reliability, availability, and condition monitoring of inverters of grid‐connected solar photovoltaic systems

AbstractReliability, Availability and Condition Monitoring (RACM) evaluation has become a critical area of interest for researchers as the output power quality of a Photo‐Voltaic (PV) system depend on the reliability of its components. In this paper, the RACM of grid‐connected PV systems is presented. For this, the Reliability Block Diagram (RBD) technique along with the exponential probability distribution function is used. The main objective of this work is to identify the weakest subsystem of a system in order to enhance system reliability. The condition monitoring system will be helpful in avoiding the sudden breakdown and unexpected maintenance of the system. An elaborate analysis is presented for PV system beginning from the sub‐assemblies to the subsystems and then to the overall system. In addition, the subsystems are ranked based on their impact on the overall availability of the system. This is decided based on the availability importance measures. It is observed that the inverter forms the weakest subsystem in the solar system. The novelty of the proposed RACM method is that one can monitor the health status or useful life of the system regularly which is not yet explored in the literature. Most of the papers have considered that the components of PV systems are non‐repairable but in this paper, the redundancy concept is explored which helps in increasing the reliability and availability of the system. When the proposed method and the results obtained are compared to existing methods, it is discovered that the proposed work outperforms them.

Methods of mining machine components reconditioning and hardening by means of concentrated energy fluxes

Introduction. The value of resources is becoming increasingly important to mining proprietors, since the maintenance of mining equipment is quite expensive. Increased scope and cost of repairs are largely determined by the quality of mining machines and equipment operation in production environment, as well as by their reliability and maintainability. The costs of preventive maintenance are over the limit by 40–50%, in most instances, due to equipment shutdowns caused by subsystem failures. Components with hidden defects as well as the methods of components reconditioning that do not ensure long-term operation cause a significant overrun of costs for breakdown maintenance. The quality of mining equipment maintenance is in direct relationship with the effective methods of components reconditioning, including the methods of components hardening both during their manufacture at machinebuilding plants and during their repairs at repair works that carry out complex, mainly major repairs of mining equipment. Adherence to the flow process of reconditioning/hardening of the component surface in contact with another component is of great importance. Therefore, to preserve fixed assets, in particular, mining and transport equipment, it is essential to find that reconditioning methods which allow to preserve consumer properties and operability of equipment for a sufficiently long time. Subject matter. The article provides an overview of methods of mining machine components reconditioning/hardening involving concentrated energy fluxes. In the authors’ opinion, these are the most effective methods to increase the resource and reliability of mining machine components by 2–3 times. The choice of components reconditioning/hardening method depends entirely on the service centre capacities, necessary technological equipment availability, personnel qualifications and, most importantly, economic feasibility of using a particular method of reconditioning/hardening. Research objective is to consider the most effective methods of mining machine components reconditioning/hardening. Methods of research include the interpretation of a number of experiments conducted at mining enterprises to obtain comparative characteristics of the most effective methods of mining machine components reconditioning/hardening. Research results. The most effective methods of components reconditioning/hardening are identified and recommended practices are provided. Conclusions. It has been established that the application of a particular components reconditioning/hardening method should be based on the data from tribological maps, as well as necessary equipment availability and economic feasibility.

Application of Multicriteria Decision-Making Methods to Determine the Appropriate Policy for Maintenance of Buildings in Karaj City, Iran

Maintenance operations embrace all parts of the building, such as structural and architectural parts, mechanical and electrical installations, and how they are serviced, including the most detailed to the most sensitive components in the building. This research uses the Delphi method and prepares a questionnaire with the construction industry experts’ opinions to determine the main criteria. The purpose of this article is to identify and prioritize the effective indicators for the building maintenance system and determine the most appropriate strategy for this system using multicriteria decision making methods. The proposed method first calculates the weight of the indicators and then prioritizes the indicators based on fuzzy and nonfuzzy multicriteria decision-making methods. Finally, the final rankings of the indices were calculated using the mean rank and final ranking methods. According to the review of all methods, it was found that safety, health and accessibility indices are the first to third priorities, respectively. Finally, by examining the results obtained from a case study (Karaj City, Iran) and examining the experts’ opinions, it was found that the obtained results are different and the corrective maintenance (CM) and breakdown maintenance (BM) strategies are the most appropriate.

Five-year trends in bacterial contamination of dialysis equipment.

Bedside dialysis monitoring equipment for hemodialysis are located in the bioburden section upstream of the endotoxin-retentive filter for dialysis fluid sterilization. We observed 26 equipment at our institution for bacterial contamination at least once every 4 weeks for 5 years with another ultrafiltration membrane upstream to prevent bacterial contamination. Bacterial contamination levels were highest and most diverse at the time of the first flush. During subsequent initial cleanng, the contamination level decreased, and bacterial species converged almost exclusively to one genus, namely Methylobacterium spp. During clinical use, the equipment were cleaned and disinfected daily after dialysis, and daily operations and maintenance were performed using aseptic techniques. Although the frequency of bacterial detection decreased annually, the same bacterial genotypes observed at the first flush were isolated even after long time periods and were thought to persist in the equipment possibly by forming biofilm. Pseudomonas aeruginosa was newly detected after the replacement of parts during breakdown maintenance, indicating the need to sterilize replacement parts. Thus, the bioburden should be assessed regularly as part of the management of in-house-produced dialysis fluid.

Application of Industrial Internet for Equipment Asset Management in Social Digitalization Platform Based on System Engineering Using Fuzzy DEMATEL-TOPSIS

In any industry, Equipment Asset Management (EAM) is at the core of the production activities. With the rapid development of Industrial Internet technologies and platforms, the EAM based on the Industrial Internet has become an important development trend. Meanwhile, the paradigm of EAM is changing, from a single machine to integrated systems, from the phase of using them to the end of their lifecycle, from breakdown maintenance to predictive maintenance, and from local decision-making to collaborative optimization. However, because of the lack of a unified understanding of the Industrial Internet platforms (IIPs) and the lack of a comprehensive reference architecture and detailed implementation framework, the implementation of EAM projects will face greater risks according to special needs in different industries. Based on the method of system engineering, this study proposes a general reference model and a reference architecture of implementation for the Industrial Internet Solution for Industrial Equipment Asset Management (I3EAM). Further, to help enterprise to evaluate and select their best-fit I3EAM scheme and platform partner, we proposed a set of performance indicators of I3EAM schemes and a quantitative decision-making method based on fuzzy DEMATEL-TOPSIS. Finally, a case study for an I3EAM in automated container terminals was conducted. In the multi-criteria decision environment with complex uncertainty, the project group identified the I3EAM metrics priorities and social digitalization platforms that were more in line with the actual needs of the automated container terminal and firms. The complexity and time of the decision-making process were dramatically reduced. In terms of feasibility and validity, the decision result was positively verified by the feedback from the enterprise implementation. The given model, architecture, and method in this study can create a certain reference value for various industrial enterprises to carry out the analysis and top-level planning of their I3EAM needs and choose the partner for co-implementation. In addition, the research results of this study have the potential to support the construction of standard systems and the planning and optimization of the cross-domain social platform, etc.

Vibration Analysis of a Roller Bearing Condition Used in a Tangential Threshing Drum of a Combine Harvester for the Smooth and Continuous Performance of Agricultural Crop Harvesting

Testing the reliability of the threshing unit is difficult and thus often neglected before the harvesting season, which can result in breakdown maintenance during peak harvesting time in difficult-to-access areas for sensor mounting. In this paper, the vibration analysis of the threshing condition of the combine harvester was performed by introducing the bracket for inaccessible locations. The Adash A4900 Vibrio M analyzer (Adash spol. s.r.o., Ostrava, Czech Republic) was used for a vibration signal measurement and the DDS Adash software was used for signal processing. The demodulated fast Fourier transform (FFT) root mean square (RMS) (500 Hz–16 kHz) method was used to evaluate the bearing condition and DDS Adash Fault Source Identification Tool (FASIT) technology was used to evaluate other mechanical conditions such as the looseness, misalignment, and unbalance of the threshing unit of the Massey Ferguson series of combine harvesters. Modal and random vibration analyses were performed on the bracket and components and compared to prevent the resonance phenomenon using the Ansys Software (Ansys, Inc., Canonsburg, PA, USA). The constrained modal analysis of the threshing drum was performed to observe the deformation. Decent results were obtained from the method used. The method was again validated by the tangential threshing test bench and successfully determined the bearing fault condition. The method used is an uncomplicated and effective way of performing the bearing analysis of the tangential unit of the combine harvester.

Pengaruh Preventive Maintance dan Breakdown Maintance Terhadap Kelancaran Proses Produksi

This study aims to determine the simultaneous and partial effect of preventive maintenance and breakdown maintenance on the smooth production process (a case study at the Marrivosa Rubber Sandal Cigantang Company, Tasikmalaya City. The research method used is survey and quantitative methods. The sample used is random sampling. The data used are primary data in the form of preventive maintenance cost data, damage maintenance cost data, and production target data for the last 5 years, namely in the 2017-2021 period. The analytical tool used in this study is multiple regression using SPSS 16. The results of the study shows that simultaneously preventive maintenance and breakdown maintenance have a significant effect on the smoothness of the production process Partially, preventive maintenance and breakdown maintenance have a significant effect on the smoothness of the production process.

Prioritization of Effective Lean Tools for Reliability Analysis & Maintenance Strategy

Asset or equipment reliability and availability have occupied extensive attention because of an emerging competitive environment and the overall operating and production cost. The main focus of this manuscript is to prioritize the lean tool and select an appropriate maintenance strategy for the repairable assets in the maintenance shop of the SIMGA1 shipyard. Five (5) assets of that maintenance shop such as an air compressor machine, 500-ton press machine, overhead crane machine, VDF lathe machine, and Roller machine were under breakdown maintenance. Due to the continuous degradation of those assets, attempts should be taken to enhance the reliability parameters by predicting upcoming failure events for each equipment or asset. QFD-AHP is a rapid tool in which quality function deployment is integrated with AHP to make an optimal selection. Firstly, the integrated QFD-AHP method is employed to prioritize the lean tools for that maintenance shop. 5S and KPI are the best fit for that shop among ten lean tools. Non Homogenous Poisson Process (NHPP) is a model which represents the no. of failure experienced up to time (t). NHPP and Weibull analysis are utilized to predict future failure events and analyzed the nature of the failure accordingly. From the results of the Weibull analysis and NHPP analysis, it is shown that the slope (β) of the failure rate is greater than 1 for all assets. Overhead crane m/c and 500-ton press m/c are the most critical m/c according to equipment criticality analysis. Finally, a decision diagram is utilized to extract the most congruent maintenance strategies based on the reliability parameter of five (5) assets. The approach employed in this study helps maintenance practitioners to achieve lean maintenance.

Collaborating product development and maintenance service: quality incentive with inspection and warranty strategies

ABSTRACT Service-oriented manufacturing has been a prevalent trend in integrating product collaborative development with maintenance service, whereas the final products are frequently trapped into severe quality defects lacking appropriate contracting incentives. This paper establishes a tractable framework investigating the alignment of inspection and warranty strategies to manage product quality throughout the R&D, manufacturing and usage processes. Specifically, the manufacturing effort is motivated by a cost-sharing contract provided by the researcher, who performs quality inspection upon receiving the final product. Subsequent maintenance service is predesignated for warranty period coverage that the cost is partially claimed for compensation from the manufacturer. Under both breakdown and preventive maintenance strategies, we elaborate and compare the optimal incentive intensities solving the equilibrium effort decisions and inspection accuracy. The results suggest that both R&D and manufacturing effort levels under preventive maintenance are slightly higher than that under breakdown maintenance scenario, while inspection accuracy contradicts conversely. The breakdown maintenance strategy is associated with a lower proportion of warranty costs borne by the manufacturer. For a sufficient long warranty period, the researcher is better off to conduct preventive maintenance periodically. Our study contributes to providing explicit implications to manage product development quality with adequate inspection and warranty strategies.