Academic literature on the topic 'Corrective maintenance Preventive maintenance Maintenance Schedule optimum time'
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Journal articles on the topic "Corrective maintenance Preventive maintenance Maintenance Schedule optimum time"
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Ettaye, Ghita, Abdellah El Barkany, and Ahmed El Khalfi. "Modeling and Optimization a Production/Maintenance Integrated Planning." International Journal of Engineering Research in Africa 28 (January 2017): 169–81. http://dx.doi.org/10.4028/www.scientific.net/jera.28.169.
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This study is on the integrated planning problem of maintenance and production within the frame work of a system subject to periodic preventive replacements with minimal repairs in case of unplanned failures. A model was developed using the overall cost by considering the interdependence between the maintenance plan and the production schedule. The overall cost contains two parts: the costs of launching a product, production, storage and breaking on the demand and the preventive and corrective maintenance costs for multi-periods and multi-products systems. The purpose of this integration is to find simultaneously the optimal cycle T at which the preventive maintenance takes place and the optimal values of lot-size by adding the setup time constraint. Using the mixed integer linear programming these optimal values minimize the total cost over a finite horizon. The results show that the proposed model performs quite well and opens new research direction for future improvements.
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Abdul Halim, Nurul Nadiah, S. Sarifah Radiah Shariff, and Siti Meriam Zahari. "Single-machine Integrated Production Preventive Maintenance Scheduling: A Simheuristic Approach." MATEMATIKA 36, no. 2 (August 1, 2020): 113–26. http://dx.doi.org/10.11113/matematika.v36.n2.1168.
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Preventive maintenance (PM) planning becomes a crucial issue in the real world of the manufacturing process. It is important in the manufacturing industry to maintain the optimum level of production and minimize its investments. Thus, this paper focuses on multiple jobs with a single production line by considering stochastic machine breakdown time. The aim of this paper is to propose a good integration of production and PM schedule that will minimize total completion time. In this study, a hybrid method, which is a genetic algorithm (GA), is used with the Monte Carlo simulation (MCS) technique to deal with the uncertain behavior of machine breakdown time. A deterministic model is adopted and tested under different levels of complexity. Its performance is evaluated based on the value of average completion time. The result clearly shows that the proposed integrated production with PM schedule can reduce the average completion time by 11.68% compared to the production scheduling with machine breakdown time.
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Atmaji, Fransiskus Tatas Dwi, Anna Annida Noviyanti, and Widia Juliani. "IMPLEMENTATION OF MAINTENANCE SCENARIO FOR CRITICAL SUBSYSTEM IN AIRCRAFT ENGINE Case study: NTP CT7 engine." International Journal of Innovation in Enterprise System 2, no. 01 (January 31, 2018): 50–59. http://dx.doi.org/10.25124/ijies.v2i01.17.
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An aircraft company needs to "secure" their aircraft engine for a good maintenance system to keep the optimum engine's performance during the flight. This paper proposed maintenance analysis and scenario for the CT7, the main engine for aircraft at NTP company. A failure data record from four critical components of the CT7 engine is analyzed using Reliability Centered Maintenance (RCM) and Risk Based Maintenance (RBM) methods to obtain the optimum maintenance interval task for the critical subsystem of the CT7 engine and also seeing the risk of maintenance cost of the engine's failure effect.
The RCM analysis result obtained seven scheduled on condition task, six scheduled discard task, and three scheduled restoration task. The interval of the maintenance schedule of each critical component varies according to the function obtained. And based RBM analysis, the risk from system performance loss is got $ 7.014.841, 90. Meanwhile, the total cost of maintenance interval based on a calculation of optimal time interval got $1.885.612, 82.
Keywords— preventive maintenance, reliability-centered maintenance, risk-based maintenance, risk priority number.
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Kurniawan, Rizki Arga, and Heri Mujayin Kholik. "Usulan Perawatan Mesin Stitching Dengan Metode Reliability Centered Maintenance." Jurnal Teknik Industri 16, no. 2 (May 9, 2017): 83. http://dx.doi.org/10.22219/jtiumm.vol16.no2.83-91.
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Based on industrial competition nowadays, production quality occurs to be the main concern of severals top companies. Method of machine maintenance is a way to incresing their production quality. Nowadays, several companies still using a corrective maintenance to maintain their machine, which is all of machine maintenance only be performed if the machine damaged. This thesis only focus to high frequency stitching machine. This thesis using Reability centered maintenance method to obtain optimum maintenance interval. This method gathers 7 step of data processing, starting from data selection, determinating restricions of the system, descripting the system and function of block diagram, and then FMEA (Failure Mode Effect Analysis) and LTA (Logic Tree Analysis). The result of this method is a correct maintenance action for critical components that included in condition directed and time directed categories. Qulitative analysis for Reliability Centered Maintenance method includes types indectification of maintenance, cause of damage and the occuring failure. Resul of the research contain several maintenance actions for critical components using condition directed method and critical component replace schedule using time directed method. From the suggested system maintenance simulation with RCM method, downtime can be decrease until 47,83%.
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M’halla, Anis. "Static Integration Based on Stochastic P-Time Petri Nets of Maintenance Scheduling for Railway Transport Equipment." Journal of Advanced Transportation 2021 (August 7, 2021): 1–12. http://dx.doi.org/10.1155/2021/7506673.
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In transport systems, all equipment requires maintenance, which directly affects the machine’s availability and consequently the planned transport schedule. The purpose of this paper is to carry out a method for integrating recovery jobs in railway systems. The proposed method allows the insertion of preventive and corrective maintenance operations when the transport equipment is available in order to minimize periods of inactivity, avoid catastrophic scenarios, and maintain stability and safety of the studied networks. A computing algorithm, allowing insertion of the planned recovery tasks in periods of metro availability, without changing the initial scheduling solution, is established. Finally, we illustrate the implementation of the proposed approach on Tunisian Sahel railway transport networks.
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Soenandi, Iwan Aang, and Teuku Emily Budiman. "Optimization of industrial machine maintenance scheduling using ant colony method." MATEC Web of Conferences 204 (2018): 02001. http://dx.doi.org/10.1051/matecconf/201820402001.
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The importance of machine maintenance has been gradually recognized especially with the great attention in industrial sector. A company was named M is a manufacturing company which engaged in the industrial manufacturer of body pail cans. Previously, the process of machine maintenance at company M is to repair the machine when a problem occurs. This causes several machines to break down frequently and disrupt the production process. Furthermore, the purpose of this research is to determine the optimum and well-planned maintenance scheduling that can reduce the risk of-or prevent machine failures that may ruin the production process by doing the preventive maintenance in right time. Ant Colony Optimization (ACO) method was used in this research as maximizing the interval time between preventive maintenance periods before the trouble occurs based on previous breakdown data period as minimizing frequency of the task. In the principle of ACO, the required parameters are α, β, m, e, el. As a result of using ACO with the combination of parameters above, the optimal well-planned maintenance scheduling was obtained by using α=2, β=5, e=0.3, e1=0.96, and a number of ants needed. Finally, the optimizing of schedule maintenance has proposed in daily for next year period.
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Yu, Quanjiang, Michael Patriksson, and Serik Sagitov. "Optimal scheduling of the next preventive maintenance activity for a wind farm." Wind Energy Science 6, no. 3 (June 23, 2021): 949–59. http://dx.doi.org/10.5194/wes-6-949-2021.
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Abstract. A large part of the operational cost for a wind farm is due to the cost of equipment maintenance, especially for offshore wind farms. How to reduce the maintenance cost, and hence increase profitability, is this article's focus. It presents a binary linear optimization model whose solution may inform the wind turbine owners about which components, and when, should undergo the next preventive maintenance (PM) replacements. The suggested short-term scheduling strategy takes into account eventual failure events of the multi-component system – in that after the failed system is repaired, the previously scheduled PM plan should be updated, assuming that the restored components are as good as new. The optimization algorithm of this paper, NextPM, is tested through numerical case studies applied to a four-component model of a wind turbine. The first study addresses the important case of a single component system, used for parameter calibration purposes. The second study analyses the case of seasonal variations of mobilization costs, as compared to the constant mobilization cost setting. Among other things, this analysis reveals a 35 % cost reduction achieved by the NextPM model, as compared to the pure corrective maintenance (CM) strategy. The third case study compares the NextPM model with another optimization model – the preventive maintenance scheduling problem with interval costs (PMSPIC), which was the major source of inspiration for this article. This comparison demonstrates that the NextPM model is accurate and much faster in terms of computational time.
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Shore, Haim. "OPTIMUM SCHEDULE FOR PREVENTIVE MAINTENANCE: A GENERAL SOLUTION FOR A PARTIALLY SPECIFIED TIME-TO-FAILURE DISTRIBUTION." Production and Operations Management 5, no. 2 (January 5, 2009): 148–62. http://dx.doi.org/10.1111/j.1937-5956.1996.tb00391.x.
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Antunes, Mark, Vincent Armant, Kenneth N. Brown, Daniel Desmond, Guillaume Escamocher, Anne-Marie George, Diarmuid Grimes, et al. "Assigning and Scheduling Service Visits in a Mixed Urban/Rural Setting." International Journal on Artificial Intelligence Tools 29, no. 03n04 (June 2020): 2060007. http://dx.doi.org/10.1142/s0218213020600076.
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This papera describes a maintenance scheduling application, which was developed together with an industrial partner. This is a highly combinatorial decision process, to plan and schedule the work of a group of travelling repair technicians, which perform preventive and corrective maintenance tasks at customer locations. Customers are located both in urban areas, where many customers are in close proximity, and in sparsely populated rural areas, where the travel time between customer sites is significant. To balance the workload for the agents, we must consider both the productive working time, as well as the travel between locations. As the monolithic problem formulation is unmanageable, we introduce a problem decomposition into multiple sequential steps, that is compatible with current management practice. We present and compare different models for the solution steps, and discuss results on datasets provided by the industrial partner.
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Sukopriyatno, Adi, Sri Rahayuningsih, and Ana Komari. "PERANCANGAN PENJADWALAN PERAWATAN MESIN BUBUT DENGAN METODE RELIABILITY CENTERED MAINTENANCE (RCM) DI BENGKEL PEMESINAN SMK NEGERI 1 KEDIRI." JURMATIS : Jurnal Ilmiah Mahasiswa Teknik Industri 1, no. 1 (March 21, 2019): 13. http://dx.doi.org/10.30737/jurmatis.v1i1.291.
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So far, the engineering department has not implemented a good maintenance system. Therefore we need a maintenance schedule to meet the need for maintenance. The method for the analysis function is: reliability analysis and maintainability factor analysis. From the application of the reliability centered maintenance system approach, it is concluded that the critical components and the compilation of the failure modes and effect analysis tables. Whereas from the results of the reliability analysis in the form of the rate of damage, the average time between the damage and the maintainability factor analysis, it is concluded that the average corrective maintenance, the average prevention time, the average maintenance time, the average active maintenance time, the maintenance frequency and the time. the average down time of the lathe electrical system components. The results of the calculation of Mean Time Between Maintenance obtained maintenance intervals of lathe electrical system components every 223.1 hours, lathe erosion every 401.6 hours, fixed head of lathe every 502 hours, lathe head off every 669.3 hours and lathe chuck every 1004 hours. Need to get (preventive maintenance), namely daily maintenance, weekly maintenance and monthly maintenance. Pentingnya fungsi pemeliharaan dalam jurusan pemesinan merupakan hal yang tak terbantahkan. Dengan tidak disadari akan berdampak besar terhadap proses pembelajaran jika pemeliharaan tidak dilakukan seperti, operasi mesin yang tidak aman, kemacetan mesin, kerugian daya, berhentinya proses pembelajaran dan berbagai fungsi sarana lain yang tidak diketahui untuk masa yang lama. Jurusan pemesinan selama ini belum menerapkan suatu sistem pemeliharaan yang baik. Dimana saat ini masih menerapkan suatu pemeliharaan yang bersifat darurat atau perawatan yang dilakukan apabila ada kerusakan (corective maintenance). Oleh karena itu dibutuhkan suatu jadwal pemeliharaan dalam memenuhi kebutuhan akan suatu pemeliharaan. Metode yang digunakan dalam pembentukan jadwal tersebut adalah dengan menerapkan pendekatan sistim yaitu reliability centered maintenance. Dan juga menerapkan fungsi analisa yaitu : analisa reliability dan analisa maintainability faktor. Dari penerapan pendekatan sistem reliability centered maintenance disimpulkan komponen kritis dan penyusunan tabel failure modes and effect analisis. Sedangkan dari hasil analisis reliability disimpulkan berupa laju kerusakan, waktu rata – rata diantara kerusakan dan analisa maintainbility faktor disimpulkan berupa rata – rata pemeliharaan korektif, waktu rata – rata pencegahan, waktu rata – rata pemeliharaan, waktu rata – rata pemeliharaan aktif, frekuensi pemeliharaan dan waktu rata – rata down time dari komponen sistem kelistrikan mesin bubut. Dari hasil perhitungan Mean Time Between Maintenance (MTBM) didapatkan interval pemeliharaan atau perawatan untuk komponen sistem kelistrikan mesin bubut setiap 223,1111 jam, eretan mesin bubut setiap 401,6 jam, kepala tetap mesin bubut setiap 502 jam, kepala lepas mesin bubut setiap 669,3333 jam dan chuck mesin bubut setiap 1004 jam. Jika melihat dari interval perawatan dan pemeliharaan diatas maka mesin bubut perlu mendapatkan perawatan berkala atau terencana (preventive maintenance), yaitu perawatan harian, perawatan mingguan dan perawatan bulanan.
Dissertations / Theses on the topic "Corrective maintenance Preventive maintenance Maintenance Schedule optimum time"
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Tabikh, Mohamad, and Ammar Khattab. "Scheduled maintenance policy for minimum cost : a case study." Thesis, Linnéuniversitetet, Institutionen för teknik, TEK, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-13668.
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This report evaluate the maintenance policies that been applied within specific industrial company, Taken into considerations all corrective and preventive maintenance costs ,in addition to optimise best preventive maintenance schedule for minimum cost. Dynamate Intralog AB was the surveyed company that been encountered high maintenance cost compatible with less productivity, therefore obtaining maintenance schedule policy for minimum cost was the best solution for their problem, then by calculating their corrective and preventive maintenance cost the optimum time was acquired. Finally, the maintenance schedule approve that organized maintenance based on optimum time enhance the productivity and minimize the company maintenance cost.
Book chapters on the topic "Corrective maintenance Preventive maintenance Maintenance Schedule optimum time"
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Salonen, Antti, Marcus Bengtsson, and Victoria Fridholm. "The Possibilities of Improving Maintenance Through CMMS Data Analysis." In Advances in Transdisciplinary Engineering. IOS Press, 2020. http://dx.doi.org/10.3233/atde200163.
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Maintenance of production equipment is one of the most critical support actions in manufacturing companies for staying competitive. More recently, with the introduction of Industry 4.0, academia, as well as industry, put a lot of effort into condition monitoring in order to implement predictive maintenance. Most stakeholders agree that maintenance need to be more data-driven. However, in order to draw true advantage of data-driven decisions, it is necessary for manufacturing companies to have implemented basic maintenance to a high standard in order to reduce for example: recurring failures, human errors, unsafe machines, etc. The real-time data can then be used to improve efficiency of maintenance tasks and schedule that adds value to the processes. In manufacturing industry, maintenance actions are commonly administered in a Computerized Maintenance Management System, CMMS, still, rather few companies analyze their maintenance records. Behind these data there is often a treasure of improvement opportunities that could be used to improve basic maintenance. The purpose of this paper is to explore how historical data from a CMMS can be used in order to improve maintenance effectiveness and efficiency of activities. In order to exemplify the possibilities of analyzing CMMS records, a case study has been performed in a plant, manufacturing driveline components for heavy construction vehicles. The study shows that one major obstacle for utilizing the CMMS data is poor description of faults and failures when it comes to work order requests, mostly performed by operators and assemblers, as well as work order reporting, mostly performed by repairmen and maintenance technicians. However, by thorough analysis of well described corrective maintenance, it is possible for industry to understand the nature of the occurring breakdowns and thus, refine the preventive maintenance program in order to further increase the dependability of the production system.
Conference papers on the topic "Corrective maintenance Preventive maintenance Maintenance Schedule optimum time"
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Mirzamoghadam, Alexander V. "Gas Turbine Plant Thermal Performance Degradation Assessment." In ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-50032.
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Knowing the sources behind degradation of gas turbine power and heat rate and the performance of other power plant equipment are critical to equipment manufacturers for guaranteeing their respective performances over the life cycle as well as to utility/plant owners for cost reasons. Many power companies are trying to improve equipment reliability by focusing on Performance Monitoring and the application of advanced diagnostic technologies. The first part of the paper describes a method to monitor gas turbine compressor efficiency, forecast an efficiency decay rate in terms of operating hours, introduce the logic leading to an optimum schedule pertaining on-line/off-line water washing, correct measured real-time gas turbine power and heat rate with respect to the new and clean reference point, and then deduce the respective turbine and compressor power contributions to gas turbine net power degradation. An example is used to aid the planning of a rigorous but effective schedule in compressor washing. The second part focuses on assessing degradation at the plant level (simple or combined cycle). The derived gas turbine degradation methodology is integrated with the overall plant performance degradation, and as a result, the maintenance effectiveness of the most recent outage can be measured. The proposed methodology is applied to a hypothetical combined cycle plant, allowing the identification of possible sources of plant deterioration with recommendations for corrective actions to improve overall power and heat rate.
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Ferreira, Jean Carlos Nunes, Marcos de Freitas, and Fernando Cavalcanti de Albuquerque. "Combined Cycle Power Plant Long Term Preservation Program: The Arauca´ria Power Station Study Case." In ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-50405.
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Arauca´ria Power Station, a 484 MW CCPP, is powered by two NG-fired Siemens 501FD2 Combustion Turbines and one Alstom DKZ2-2N34 Steam Turbine. Located in Southern Brazil, near Curitiba, the capital of the State of Parana´, Arauca´ria PS was tested and accepted in September 2002. Due to commercial issues, the plant remained shut down since its COD until 2006. Along four years, the O&M team developed and implemented a comprehensive plant preservation program aiming to keep the equipment safe from degradation. The purpose of this paper is to describe the program and the activities performed during this period. The OEM recommendations were strictly followed. All the operations, tests and inspections were performed according to the Long Term Standby Procedure. The preventive, predictive and corrective maintenance performed in conformity with the Plant Maintenance Manual. Such activities were controlled by means of the corporative Computer-based Operations Management System and the CMMS and always in compliance of the ES&H regulations. The wooden structured cooling tower was maintained wet, the circulating water system was kept in operation, the demineralised water treatment system was run monthly and water microbiology/chemistry control (including the chemicals dosing and weekly water analysis schedule) was kept in accordance with the program designed by GE Water & Process Technologies. In a totally outdoor plant, corrosion prevention is fundamental. For this reason, a painting program designed by LACTEC, a local institute of technology, was followed. By the Plant Valves Lubrication and Tests schedules, each manual and automatic valve was lubricated and tested. The two Aalborg HRSGs (including condensate and steam piping) were maintained at minimum 0.5 barg dry nitrogen atmosphere. Dehumidifiers and heaters were installed in both HRSGs gas side, so the ambient conditions between the CTGs air inlet and the HRSGs stack inlet were maintained with relative humidity below 40%. Similar system was provided for the Steam Turbine. Both systems were automatically controlled and supervised from the Plant Control Room. When Arauca´ria PS was re-commissioned in mid-2006, this strict program proved its effectiveness once no major problems were found and the plant start-up succeeded in a very short time. The plant was operated since June, 2007 through January, 2008 with an average availability in excess of 98%. The long-term preservation program is presently being reviewed and many improvements shall be implemented in order to achieve faster installation/removal of high performance preservation systems, so they shall be used for short-term shutdown periods as well.