Effect Of Preventive Maintenance Research Articles

Preventive Maintenance on CNC Machines Using the OEE Method to Reduce Downtime at PT. MTAT

This study examines the performance of CNC machines at PT MTAT Indonesia from January to March 2023. Monthly production data, machine uptime, defect rates, and non-productive periods were collected to assess Overall Equipment Effectiveness (OEE). This study aims to analyze the effectiveness of preventive maintenance of CNC machines at PT MTAT Indonesia using the Overall Equipment Effectiveness (OEE) method to reduce downtime. This study uses monthly data from January to March 2023, including production uptime, defect rates, and non-productive periods, to calculate OEE. The analysis showed that the CNC machines achieved an average OEE of 86.52%, surpassing the global standard of 85%, indicating high efficiency and quality. The study used Pareto analysis to identify the main causes of downtime, finding technical and maintenance issues as the main contributors. By addressing these factors, PT MTAT Indonesia can further improve machine efficiency and productivity. This study contributes to this field by providing a comprehensive analysis of CNC machine maintenance and proposing strategies for continuous improvement.

Preventive maintenance decision model of electric vehicle charging pile based on mutation operator and life cycle optimization

AbstractThis paper proposes a preventive maintenance decision model for electric vehicle charging stations based on mutation operators and lifecycle optimization to address the impact of potential faults on maintenance effectiveness. By introducing the particle swarm optimization algorithm with mutation operator, a comprehensive analysis of opportunity service age factor and safety failure probability factor was conducted to establish an indicator system for the operation status of charging piles, and a potential fault identification model was constructed. By optimizing the life cycle, the balance problem between optimal maintenance life and optimal opportunity maintenance life has been solved, thus completing preventive maintenance decisions. The experimental results show that the accuracy of this method in preventive maintenance decision‐making for electric vehicle charging piles can reach 98%, with an average preventive maintenance decision‐making time of 1.6 s for load piles. At the same time, the risk probability value and load loss value are effectively controlled. This study has good application prospects in improving the preventive maintenance effect of electric vehicle charging piles.

Energy-based availability warranty policy with considering preventive maintenance and learning-forgetting effect

Ensuring reliable operation and maximum the output is crucial for energy production systems. Traditional time-based availability (TBA) warranty policies often overlook some factors, such as energy loss and the experience gained during the maintenance activities. In this paper, an innovative warranty policy which focuses on the energy-based availability (EBA) is proposed, where imperfect preventive maintenance (IPM) and minimal repair (MR) are taken into account, and hybrid hazard rate model is adopted to describe the effect of preventive maintenance. In addition, the learning-forgetting effect during the maintenance is considered. On this basis, six types of single-objective and multi-objective models are established, and they are solved by genetic algorithm (GA) and non-dominated sorting genetic algorithm-II (NSGA-II), respectively. To illustrate the effectiveness of the proposed warranty policy, a numerical case of wind turbine gearbox is conducted. The results show that the proposed EBA warranty policy can gain around 0.29% energy more than TBA policy. Compared to single-objective models, multi-objective models can provide more selectable maintenance options. Additionally, sensitivity analysis indicates that by considering the learning-forgetting effect, the gearbox can achieve higher EBA and lower warranty cost.

Group Maintenance for Numerical Control Machine Tools: A Case Study

The high-reliability requirement of numerical control (NC) machine tools emphasizes the effectiveness of preventive maintenance (PM). However, most existing PM decisions are made by treating them as single-component systems, resulting in the problems of “excessive maintenance” or “insufficient maintenance.” Moreover, real failure data has rarely been utilized for maintenance decision-making, which leads to idealized policies far from practice. This article presents a framework to derive the optimal group maintenance (GM) policy from real failure histories for an NC machine tool comprised of heterogeneous components. Criticality analysis is first conducted to identify high-risk and low-risk components. The lifetime of each high-risk component is characterized by a two-parameter Weibull model or by a Weibull competing-risk model according to whether its failures are independent of the other components. High-risk components with strictly increasing or bathtub-shaped failure rates are selected for PM decision-making. This article introduces a multilevel PM decision-making approach: 1) a repair-replacement model is developed at the component level to derive the optimal PM interval and the maximum number of PM actions; and 2) at the system level, a GM procedure is presented to obtain the optimal PM interval of the system. The failure histories of an NC machine tool with 13 components are used to illustrate the effectiveness of the proposed approach. A maintenance plan is finally made based on optimization results to guide maintenance implementation.

Statistical Modeling of the Effectiveness of Preventive Maintenance for Repairable Systems

Preventive maintenance (PM) is commonly adopted in practice to improve a system’s health condition and reduce the risk of unexpected failures. When a PM action is poorly performed, however, it is likely to have adverse effects on system reliability. We observe this phenomenon when evaluating the effectiveness of a PM program for a fleet of service vehicles based on their four-year operating data. This phenomenon is also commonly reported in the maintenance of vehicles and aircraft. Motivated by this observation, we propose a statistical model for repairable systems by taking potential PM adverse effects into account. In the formulation, the baseline failure process without PM effects is modeled by a nonhomogeneous Poisson process. When a PM action is performed, its effect on the failure process is modeled as a multiplicative random effect on the system rate of occurrence of failures. Statistical inference under the proposed model is discussed, and we further develop goodness-of-fit test procedures to validate the adequacy of this model. The above-mentioned service vehicle operating data are used to demonstrate the proposed methods.

Planned maintenance vs Unplanned maintenance and facility costs

Planned maintenance, preventive, predictive, or reliability-based, are assumed to minimize costs and ensure facility sustainment and provide for high customer satisfaction. Good facility management supports sustainability and occupant satisfaction. Planned maintenance is the most efficient means to serve a facility while unplanned maintenance, reactive response to service failures and interruptions, is costly. Customer survey results can be used to measure the effectiveness of preventive maintenance and identify alternative approaches. This research looks at maintenance records from several North American universities, focusing on planned and unplanned maintenance activities and occupant surveys. The ultimate goal is to find the appropriate mix of planning and unplanned maintenance and achieve occupant satisfaction.

THE EFFECT OF PREVENTIVE MAINTENANCE, TRAFFIC MANAGEMENT, TECHNOLOGY AND COMMUNICATION SUPPORT AND OPERATOR CARE ON OSH PERFORMANCE TRANSPORTATION OF TRUCK UNITS IN THE MINING SERVICE COMPANY PT. XYZ

This study aims: To determine the direction and strength of the effect of preventive maintenance on the performance of K3 transportation at Mining Service Company PT. To determine the direction and strength of the influence of traffic management on the performance of K3 transportation at the PT. To determine the direction and strength of the influence of technology and communication on the performance of K3 transportation at the PT XYZ Mining Service Company. This research is descriptive quantitative. The population in this study were 2145 workers and staff working in the construction service company PT. The sampling technique in this study is the saturated sampling technique, the samples taken are 145 workers and staff who work in the construction service company PT. The results of this study indicate that: There is an effect of preventive maintenance on the performance of K3 transportation. There is an effect of traffic management on the performance of K3 transportation. There is an effect of technology and communication support on the performance of K3 transportation. There is an effect of operator concern on the performance of K3 transportation

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.

A novel discrete elephant herding optimization for energy-saving flexible job shop scheduling problem with preventive maintenance

Recently, energy-saving scheduling issues have attracted more and more attention in the manufacturing field. Meanwhile, in practical production, maintenance planning is viewed as a vital task in the workshop. However, the existing literature about energy-saving scheduling problems rarely consider the effect of preventive maintenance. Therefore, this paper investigates an energy-saving flexible job shop scheduling problem with preventive maintenance. A mathematical model is proposed considering the minimization of total energy consumption. To solve the problem, a novel discrete elephant herding optimization algorithm (NDEHO) is proposed according to the problem’s characteristics. To test the NDEHO’s performance, the Taguchi design of experiment approach is adopted to get the best combination of parameters in the algorithm. Numerical experiments are conducted based on twenty-four instances, including four benchmark instances and twenty randomly generated instances. Computational data indicate that NDEHO outperforms other compared algorithms for solving the considered problem.

Dynamic Preventive Maintenance Optimization of Subway Vehicle Traction System Considering Stages

The current maintenance mode of the subway vehicle traction system does not consider the change of failure rate in the operation of components, and there is an unreasonable maintenance interval and high maintenance cost. To solve this problem, a dynamic preventive maintenance strategy for subway vehicle traction systems considering stages is proposed. Service age decreasing factor and failure rate increasing factor are introduced to build a new dynamic reliability model considering the effect of preventive maintenance on component failure rate. Non-preventive failure maintenance, preventive maintenance, preventive update maintenance and opportunistic maintenance are adopted. For the components in degradation or random failure stages, a preventive maintenance optimization model with the least maintenance cost, constrained by reliability, is established. The maintenance strategy is optimized and solved based on the enumeration method to obtain single-component irregular preventive maintenance intervals and multi-component group preventive maintenance times. The results show that the proposed maintenance models are reasonable and feasible. On the premise of ensuring the system reliability, the number of vehicle outages for maintenance and the maintenance cost are reduced. Feasible and effective maintenance models and methods are provided. They can ensure the reliability of subway vehicles and reduce maintenance costs. The effectiveness and economy of maintenance work is increased.

Periodic maintenance optimization considering the difference of preventive maintenance effect based on generalized Polya process

Previous studies seldom consider the difference of preventive maintenance effect on different failure processes when establishing the preventive maintenance model. Meanwhile, preventive maintenance models usually assume that minimal repair is performed for each failure, but this assumption is not applicable in some systems. Once this assumption is made for the inapplicable system, the maintenance strategy obtained by the established preventive maintenance model will not be optimal. In order to get a better maintenance policy to reduce maintenance cost, this paper divides the system failure processes into two types: wear-out type and damage-type. The model assumes that preventive maintenance can reduce the probability of damage-type failure, but it has no effect on wear-out type failure. At the same time, for the system studied in this paper, it is assumed that after corrective maintenance, the overall state of the system is worse than the moment just prior to the failure. Then, an extended preventive maintenance optimization model based on generalized Polya process is established. Finally, a practical algorithm is designed to solve the model. The analysis of numerical examples shows the potential value of the proposed method, which may provide maintenance guidance for enterprises and save maintenance costs.

Analysis of Preventive Maintenance and Breakdown Maintenance on Production Achievement in the Food Seasoning Industry

The machine is a facility that is necessary for the company in production. The machine can reduce the failure rate of the product and reach the target time according to the customer's request. Therefore the machine needs to be cared for and maintained. Maintenance and care is a way to prevent the machine from being damaged. This study aims to determine and analyze the effect of preventive maintenance and breakdown maintenance on production achievement. The research was conducted in the Food Seasoning Industry. The research population is maintenance employees and production employees. The sample used was 25 respondents based on employees who are experts in their fields. The analytical method used in this research is the descriptive analysis method with a quantitative approach with linear regression analysis. Data processing using the help of IBM Statistics 21.00 software. The results showed that preventive maintenance partially had a significant effect on production achievement. Breakdown maintenance partially has no significant effect on the achievement of production. Simultaneously preventive maintenance and breakdown maintenance have a significant effect on the achievement of production. Linear regression analysis resulted in the model formula Y= 9.004 + 0.561 (X1) + 0.042 (X2)

Effect of Preventive Maintenance on Machine Reliability in a Beverage Packaging Plant

This paper investigates the effect of preventive maintenance on the reliabilities of devices in a bottling plant. Six months of real-time maintenance data were analyzed quantitatively. Based on the breakdown events obtained for each machine, mean time between failure (MTBF), mean time to repair (MTTR), and failure rate (λ) values for individual equipment are calculated. The bottle packer, empty bottle inspector (EBI), and palletizer are identified as the plant's critical machines. A breakdown analysis (BDA) is then performed on the bottle packer and from the failure mode of all the reoccurring problems affecting this machine as a result of ineffective PM. An autonomous maintenance (AM) team is set up as part of establishing an effective PM program to improve the reliabilities of the critical machines that were continually falling. A significant reduction in machine breakdowns is observed after two months of rolling out the AM program. As a result, the reliability of bottle packer increased from 55.30% to 70.80%, while EBI and palletizer increased from 89.20% and 87.20% to 92% and 90.50%, respectively.

Research on Application of MMA Super-solid Seal in Preventive Maintenance of Bridge Deck

In order to solve the problems of minor cracks, insufficient slip resistance, and lightening of the asphalt concrete bridge deck, the self-developed MMA super-solid seal is used to preventive maintenance of Yulong River Bridge and Baisha Viaduct of G65 Yangshuo to Pingle and G65 Guilin to Yangshuo expressways. The road performance of the MMA super-solid seal was evaluated. Engineering application results show MMA super-solid seal has a good preventive maintenance effect. The various road performance indicators (water permeability coefficient, bonding strength, sliding resistance, structural depth, etc.) meet the design requirements. MMA super-solid seal has a short maintenance time and excellent road performance, which is conducive to the sustainable development of road engineering. It can not only guarantee the service quality of the bridge deck, but also prolong the life of the bridge deck.

Stochastic Analysis of a Priority Standby System under Preventive Maintenance

In this paper, we propose a system of two dissimilar units: one unit prioritizes operation (priority unit), and the other unit is kept as a cold standby (ordinary unit). In this system, we assume that the failures, repairs, and preventive maintenance (PM) times follow arbitrary distributions for both units, except for the fact that the repair time of the ordinary unit follows an exponential distribution. The priority unit has normal, partial failure or total failure modes, while the ordinary unit has normal or total failure modes. The PM of the system can be started after time t when (i) the priority unit is in the normal or partial failure modes up to time t and (ii) the standby unit is available up to time t. PM can be achieved in two types: the costlier type with probability p and the cheaper type with probability (1−p). Under these assumptions, we investigate the reliability measures of the system using the regenerative point technique. Finally, we show a numerical example to illustrate the theoretical findings and show the effect of preventive maintenance in the reliability measures of the proposed system.

Risk factors associated with the development of post-ablation atrial fibrillation

The article presents the main clinical, instrumental, and electrophysiological risk factors of atrial fibrillation (AF) occurence in patients with typical atrial flutter (TAF) who underwent radio frequency catheter ablation (RFA) of the cavotricuspidal isthmus (CTI). The term “post-ablation AF” is defined. The role of such a factor as endocardial provocation test in predicting post-ablation AF in patients with TAF is indicated. Studies evaluating the effectiveness of preventive maintenance of RFA AF in patients undergoing RFA CTI are also represented. Mathematical models for predicting AF in the general population and in patients with TAF are discussed.

Hybrid Approach to Incorporate Preventive Maintenance Effectiveness into Probabilistic Pavement Performance Models

AbstractVarious methodologies are being developed to build and improve probabilistic pavement performance models that have high prediction capabilities. However, the effectiveness of preventive mai...

A discrete MMAP for analysing the behaviour of a multi-state complex dynamic system subject to multiple events

A complex multi-state system subject to different types of failures, repairable and/or non-repairable, external shocks and preventive maintenance is modelled by considering a discrete Markovian arrival process with marked arrivals (D-MMAP). The internal performance of the system is composed of several degradation states partitioned into minor and major damage states according to the risk of failure. Random external events can produce failures throughout the system. If an external shock occurs, there may be an aggravation of the internal degradation, cumulative external damage or extreme external failure. The internal performance and the cumulative external damage are observed by random inspection. If major degradation is observed, the unit goes to the repair facility for preventive maintenance. If a repairable failure occurs then the system goes to corrective repair with different time distributions depending on the failure state. Time distributions for corrective repair and preventive maintenance depend on the failure state. Rewards and costs depending on the state at which the device failed or was inspected are introduced. The system is modelled and several measures of interest are built into transient and stationary regimes. A preventive maintenance policy is shown to determine the effectiveness of preventive maintenance and the optimum state of internal and cumulative external damage at which preventive maintenance should be taken into account. A numerical example is presented, revealing the efficacy of the model. Correlations between the numbers of different events over time and in non-overlapping intervals are calculated. The results are expressed in algorithmic-matrix form and are implemented computationally with Matlab.

Stochastic behavior of parallel system with expert repair and maintenance

This paper examines the effect of preventive maintenance and repair done by different repairpersons on the system performance. By means of semi-Markov process and regenerative point technique, the researcher has developed a stochastic model of two unit parallel system. Both units are identical in nature. A usual repairperson visits the system to conduct preventive maintenance at the completion of maximum operation time and repair at the failure stage of the unit. At the elapse of the pre-definite time (called maximum repair time), the usual repairperson inspects the failed unit to examine the feasibility of further repair by the expert repairperson; otherwise that unit will be replaced by a new one with some replacement time. The unit may work as good as new after getting maintenance, repair and replacement as well. The switch devices are considered as perfect. Various measures of system usefulness such as MTSF, availability and profit have been derived to depict the usefulness of expert repair facility.

Stochastic Analysis of Two Non-identical Unit Parallel System Incorporating Waiting Time and Preventive Maintenance

The reliability of two non-identical unit’s parallel system with two kinds of failures common cause failure and partial failures is inspected. Moreover, the preventive maintenance and waiting time to repair, a significant aspect of reliability analysis, has also been incorporated. The proposed system is assumed to a function properly if at least one of the unit is in operate mode. The system goes for preventive maintenance at random apaches. Supplementary variable technique and Laplace transform have used for solution. Our results are compared with the previous results to observe the effect of preventive maintenance and failure rates on system performance.