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1
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.
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Belyaev, Sergey V., Aleksey V. Malafeev, and Evgeniy Ya Omelchenko. "Development of Optimum Repair Schedule of Electrical Network Equipment to Improve the Reliability of its Functioning." Electrotechnical Systems and Complexes, no. 2(43) (June 28, 2019): 4–11. http://dx.doi.org/10.18503/2311-8318-2019-2(43)-4-11.
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To ensure uninterrupted power supply to consumers, maintenance of the electrical networks in a working condition is today carried out through the use of a system of preventive maintenance. In the general case such a system allows building equipment repair schedules based on repair cycles for a long time predetermining the list of necessary material and labor resources in advance. However, in practice, the use of this system is rather difficult and not always effective. This is due to the need to change the repair schedule for emergency or urgent repairs taking into account the seasonality of work performed and the organizational structure of the production department of electrical networks and related departments as well as taking into account the specific features of the operation of specific equipment. Taking into account the current pace of development of electrical networks with a steady increase in the number of consumers (which also leads to a complication of the configuration of electrical networks) this is impossible without the use of appropriate mathematics and software that automates the planning processes for the maintenance and repair of electrical networks with a large number of factors. The minimum equipment downtime was taken as the main criterion for optimality, as a factor that largely determines the reliability of power supply. A planning algorithm has been developed that takes into account the ranking of works in order of importance, the possibility of their shift in time and the likely adjustment of the schedule based on the results of assessing the technical condition of the equipment. A method for minimizing the downtime of repair crews by using them in adjacent areas as well as a technique for identifying a set of equipment that may be under repair in the same period of time are proposed.
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Sarkar, Mitali, and Biswajit Sarkar. "Optimization of Safety Stock under Controllable Production Rate and Energy Consumption in an Automated Smart Production Management." Energies 12, no. 11 (May 29, 2019): 2059. http://dx.doi.org/10.3390/en12112059.
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A smart production system is essential to produce complex products under the consumption of efficient energy. The main ramification of controllable production rate, amount of production size, and safety stocks is simultaneously optimized under proper utilization of energy within a smart production system with a random breakdown of spare parts. Due to the random breakdown, a greater amount of energy may be used. For this purpose, this study is concerned about the optimum safety stock level under the exact amount of energy utilization. For random breakdown, there are three cases as production inventory meets the demand without utilization of the safety stock, with using of the safety stock, and consumed the total safety stock amount and facing shortages. After the random breakdown time, the smart production system may move to an out-of-control state and may produce defective items, where the production rate of defective items is a random variable, which follows an exponential distribution. The total cost is highly nonlinear and cannot be solved by any classical optimization technique. A mathematical optimization tool is utilized to test the model. Numerical study proves that the effect of energy plays an important role for the smart manufacturing system even though random breakdowns are there. it is found that the controllable production rate under the effect of the optimum energy consumption really effects significantly in the minimization cost. It saves cost regarding the corrective and preventive maintenance cost. The amount of safety stock can have more support under the effect of optimum energy utilization. The energy can be replaced by the solar energy.
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Witonohadi, Amal, Tiena Gustina Amran, and Niken Herawati. "USULAN PERAWATAN MESIN SECARA PREVENTIF DENGAN PENDEKATAN MODULARISASI DESAIN PADA PT. BAI." JURNAL TEKNIK INDUSTRI 3, no. 1 (March 1, 2013). http://dx.doi.org/10.25105/jti.v3i1.1581.
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<p>PT. BAI produce polymer filter system components, such as the spin pack, candle filters, leaf<br />discs, gaskets and so forth. Problems that occur in the form of decreased reliability of machine<br />downtime resulting in large engine stalled, causing the production process, the company should have<br />a preventive maintenance schedule in accordance with the conditions of machines on the production<br />floor to reduce machine downtime by using modularity design method approach to reduce<br />maintenance costs. Level of maintenance reliability measured using Overall Equipment Effectiveness<br />(OEE), whereas treatment schedule used to obtain parameter Mean Time to Failure (MTTF) and<br />Mean Time to Repair (MTTR). Maintenance cost calculator is then performed with corrective<br />maintenance, preventive maintenance and preventive maintenance with design modularity. By using<br />modularity design companies can combine several components into a module to do the replacement<br />components simultaneously causing maintenance costs to be as much as 29.1% less than the company<br />doing the corrective maintenance activities.</p>
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Amirian, Y., and A. Khodadadi. "The T Optimal Maintenance Time of Consecutive Linear k-out-of-r-from-n: F System and Consecutive Circular k-out-of-r-from-n: F System." International Journal of Reliability, Quality and Safety Engineering, August 27, 2020, 2150008. http://dx.doi.org/10.1142/s021853932150008x.
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A consecutive linear (circular) [Formula: see text]-out-of-[Formula: see text]-from-[Formula: see text]: [Formula: see text] system consists of [Formula: see text] linear (circular) ordered components such that the system fails if and only if there exist a set of [Formula: see text] consecutive linear (circular) component that contains at least [Formula: see text] failed components. The optimal maintenance of the consecutive [Formula: see text]-out-of-[Formula: see text]-from-[Formula: see text]: [Formula: see text] system to linear and circular states is investigated in this paper. First, an integrated strategy of corrective maintenance and preventive maintenance is introduced. Then, for first time, optimal maintenance has been applied to these systems, and optimum maintenance time has been achieved with this strategy. Also, real-world practical examples for this system have been presented.
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Singh, Sandeep, Jaimal Singh Khamba, and Davinder Singh. "Analysis and directions of OEE and its integration with different strategic tools." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, September 9, 2020, 095440892095262. http://dx.doi.org/10.1177/0954408920952624.
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The manufacturing industries are among the focused industries of any country according to their contribution to nations’ economies. Therefore, the appropriate utilization of all manufacturing/processing equipment is a high priority. The problem is the complexity to keep all the activities, operations, and use of equipment in synchronization with the reduction of all possible losses and defects. Such losses are becoming the real cause of the investment in the maintenance section of the industrial units. The different versions of established concepts define ‘Maintenance’ as ‘repair of the equipment,’ but this concept covers old and limited dimensions. Therefore, this notion relates the maintenance strategies only as a function of preventive maintenance, predictive maintenance and corrective maintenance. At the basic level of OEE implementation, various process industries of the country are yet unaware of the potential benefits of this strategic tool. The quality and performance-enhancing approaches are being developed based on time management and production loss analysis to get the optimum output from available resources. This study is to mark all the critical strategies associated with sustainable performance and to trace all possible drawbacks while measuring effectiveness through OEE (Overall Equipment Effectiveness). OEE is a tool of Total Productive Maintenance (TPM) without whom the effective utilization of resources is a difficult task. OEE supports the entire perspective on effectiveness uniquely and logically but also improves the life span of the machinery through improvements and monitoring in the maintenance operations and activities. This paper aims to identify the role of different strategies associated with OEE for unceasable production and optimum use of resources. This paper arranges the literature in an organized way and assists to find promising decisions to implement OEE with integrated concepts.