Journal articles: 'Schedule maintenance'

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Washimkar, P. V., V. S. Deshpande, J. P. Modak, and A. V. Nasery. "Formulation of Preventive Maintenance Schedule for Dragline System." International Journal of Engineering and Technology 3, no. 4 (2011): 396–99. http://dx.doi.org/10.7763/ijet.2011.v3.259.

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Butler, A. W. "The Evolution of Locomotive and Rolling Stock Maintenance Schedules." Proceedings of the Institution of Mechanical Engineers, Part D: Transport Engineering 202, no. 1 (January 1988): 33–43. http://dx.doi.org/10.1243/pime_proc_1988_202_153_02.

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The paper introduces the maintenance schedule as an integral part of the controls for planned maintenance and reviews the historical development of locomotive maintenance schedules and specifications within British Railways (BR). The events which led to the publication of maintenance schedules for locomotives and rolling stock in a variety of formats and content are explained, culminating in the 1985 decision to produce all such future documents to one standard, taking account of simplification of use at BR depots, the new maintenance policy and the benefits of computerization. The purpose of the maintenance schedule and its supporting documents is redefined in relation to the new maintenance strategy of BR and a new rationale introduced. The standard format is confirmed and the mechanisms for ensuring its maintenance explained. Future requirements associated with development of standard job descriptions, decoupling component overhauls from body overhauls assisted by a computerized maintenance schedule and the changes in overhaul specification promoted by BR's developing contract overhaul policy are described in detail.

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Cheng, Hongbo, Yufan Cao, Jiaxin Wang, Wei Zhang, and Han Zeng. "A preventive, opportunistic maintenance strategy for the catenary system of high-speed railways based on reliability." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 234, no. 10 (November 4, 2019): 1149–55. http://dx.doi.org/10.1177/0954409719884215.

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The catenary is a vital component of the electrified railway system. It consists of many parts which are interrelated; the maintenance schedule of the catenary system should consider the influence of the interrelationship. In this study, a preventive, opportunistic maintenance method is proposed to schedule the maintenance process of the catenary system. First, the reliability of the key parts of the catenary is modeled using Weibull distribution. Second, a reliability margin is proposed to expand the maintenance time from point to interval, and the reliability margin is optimized to minimize the maintenance cost. Then, a preventive opportunistic maintenance schedule can be arranged on the basis of the optimal reliability margin. Case study results verify that the proposed preventive opportunistic maintenance method can reduce the number of maintenance schedules and can effectively save the maintenance cost.

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Paprocka, Iwona, Wojciech M. Kempa, Krzysztof Kalinowski, and Cezary Grabowik. "On Pareto Optimal Solution for Production and Maintenance Jobs Scheduling Problem in a Job Shop and Flow Shop with an Immune Algorithm." Advanced Materials Research 1036 (October 2014): 875–80. http://dx.doi.org/10.4028/www.scientific.net/amr.1036.875.

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In the paper a job shop and flow shop scheduling problems with availability time constraint for maintenance are considered. Unavailability time due to maintenance is estimated basing on information about predicted Mean Time To Failure/To First Failure and Mean Time of Repair of a machine. Maintenance actions are introduced into a schedule to keep the machine available in a good operation condition. The efficiency of predictive schedules (PS) is evaluated using criteria: makespan, flow time, total tardiness, idle time. The efficiency of reactive schedules (RSs) is evaluated using criteria: solution and quality robustness. For basic schedule generation Multi Objective Immune Algorithm is applied. For predictive scheduling Minimal Impact of Disturbed Operation on the Schedule is applied. After doing computer simulations for the job shop scheduling problem following question arises: do dominated Pareto optimal basic schedules achieve better PSs? Although a single Pareto-optimal solution is achieved on Pareto-optimal frontier three different schedules have the same quality in the flow shop scheduling problem. The question is: which schedule is the most robust solution?

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Lazarev, A. A., E. M. Grishin, S. A. Galakhov, and G. V. Tarasov. "Algorithms for locomotives maintenance schedule." IFAC-PapersOnLine 52, no. 13 (2019): 951–56. http://dx.doi.org/10.1016/j.ifacol.2019.11.317.

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Semaan, Nabil M., and Nabhan Yehia. "A stochastic detailed scheduling model for periodic maintenance of military rotorcraft." Aircraft Engineering and Aerospace Technology 91, no. 9 (October 7, 2019): 1195–204. http://dx.doi.org/10.1108/aeat-09-2018-0254.

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Purpose The purpose of this paper is to develop a stochastic detailed schedule for a preventive/scheduled/periodic maintenance program of a military aircraft, specifically a rotorcraft or helicopter. Design/methodology/approach The new model, entitled the military “periodic aviation maintenance stochastic schedule” (PAM-SS), develops a stochastic detailed schedule for a PUMA SA 330SM helicopter for the 50-h periodic inspection, using cyclic operation network (CYCLONE) and Monte Carlo simulation (MCS) techniques. The PAM-SS model identifies the different periodic inspection tasks of the maintenance schedule, allocates the resources required for each task, evaluates a stochastic duration of each inspection task, evaluates the probability of occurrence for each breakdown or repair, develops the CYCLONE model of the stochastic schedule and simulates the model using MCS. Findings The 50-h maintenance stochastic duration follows a normal probability distribution and has a mean value of 323 min and a standard deviation of 23.7 min. Also, the stochastic maintenance schedule lies between 299 and 306 min for a 99 per cent confidence level. Furthermore, except the pilot and the electrical team (approximately 90 per cent idle), all other teams are around 40 per cent idle. A sensitivity analysis is also performed and yielded that the PAM-SS model is not sensitive to the number of technicians in each team; however, it is highly sensitive to the probability of occurrence of the breakdowns/repairs. Practical implications The PAM-SS model is specifically developed for military rotorcrafts, to manage the different resources involved in the detailed planning and scheduling of the periodic/scheduled maintenance, mainly the 50-h inspection. It evaluates the resources utilization (idleness and queue), the stochastic maintenance duration and identifies backlogs and bottlenecks. Originality/value The PAM-SS tackles military aircraft planning and scheduling in a stochastic methodology, considering uncertainties in all inspection task durations and breakdown or repair durations. The PAM-SS, although developed for rotorcrafts can be further developed for any other type of military aircraft or any other scheduled maintenance program interval.

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Karima, Halim Qista, and Fauzan Romadlon. "Optimizing the Preventive Maintenance Scheduling Based on Dynamic Deterministic Demand in The Cement Manufacturing." Jurnal Ilmiah Teknik Industri 20, no. 1 (July 2, 2021): 109–18. http://dx.doi.org/10.23917/jiti.v20i1.13894.

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Preventive maintenance is a planned and scheduled maintenance method that is carried out before a machine failure occurs. The maintenance schedule can be determined based on experience, historical data, or recommendations. Selecting the maintenance schedule greatly affects the production system. The Clin machine in cement manufacturing has an important role in the cement production process. During treatment, the client machine cannot produce clinker, so it is necessary to plan a production system to meet the demand. This paper aims to design an optimization model for determining the preventive maintenance schedule for cement manufacturing by considering the production process and inventory control. Mathematical models with binary options are used to model that system. The model supports showing the optimal preventive maintenance schedule for the ciln machines with a binary decision each period. This mathematical model describes the interaction of production planning, inventory control, and scheduling of total maintenance on a kiln machine. The goal of this system is to determine the optimal preventive maintenance schedule with minimum costs. In addition, the system's output is the optimal production and inventory decision rule for each period. Based on the analysis and simulation of the model with the deterministic and dynamic demand, the optimal preventive maintenance schedule is in the 9th and 21st periods. The kiln machines are maintained every July with minimal costs. The model scenario shows the interaction of the variables and the sensitivity of the production capacity and demand to the decision rule of the variable.

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Mohd Tahir, Abdullah, Jamrin Jasmin, Alfero Sualin, Noor Ajian Mohd-Lair, and Abdul Kadir bin Abdul Rahman. "The Preventive Maintenance Schedule: A Case Study at Aman Sales and Services Sdn. Bhd. and Ladang Sabah Palm Oil Mill." Applied Mechanics and Materials 660 (October 2014): 995–99. http://dx.doi.org/10.4028/www.scientific.net/amm.660.995.

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Maintenance is crucial to system performance and reliability of a machine for an industry. Machine maintenance system in small and medium industries in Malaysia usually consists of manual file management system, which records all the conducted maintenance works. However, a maintenance system should be more complex to include the scheduling of maintenance activities. This paper presents the findings of studies on the implementation of preventive maintenance schedule conducted at Aman Sales And Services Sdn. Bhd. and Ladang Sabah Palm Oil Mill both located in Sabah, Malaysia. In this study, data form previous maintenance works or activities were collected from both companies. The data were then analyzed. The analysis indicates that reduction in time can be obtained by combining similar or repetitive tasks guided by recommendation from the machines’ manuals. This analysis provides foundation for developing an improved preventive maintenance schedule for each company. The new preventive maintenance schedules are found to be able to reduce the breakdown time ranging from as low as 25% to as high as 50%. This reduction signifies the efficiency of the proposed maintenance schedule.

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Alhilman, Judi, Fransiskus Tatas Dwi Atmaji, and Valinouski Aulia. "Maintenance System of Universal Goss Printing Machine based on failure data using RCM and RCS method." International Journal of Innovation in Enterprise System 2, no. 02 (July 30, 2018): 57–62. http://dx.doi.org/10.25124/ijies.v2i02.26.

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Over time a machine will get experience a decrease in reliability, causing the engine to be damaged at the time of operation, thus disrupting the production line. To maintain a machine remains reliable then a good maintenance system is required. In this research, we will use Reliability Centered Maintenance (RCM) and Reliability Centered Spare (RCS) analysis on the critical system of Goss Universal printing machine based on engine failure data. The result of RCM analysis obtained the optimal preventive maintenance schedule and the type of treatment, while based on the RCS analysis obtained spare part needs following the maintenance schedule. With the result of this analysis, is expected where the machine will keep good and will continue to operate without a sudden breakdown under the production schedule's need. Based on RCM analysis for each critical subsystem obtained interval preventive maintenance for transfer roller 127.60 hours, Ink fountain roller 24.45 hours, ink form roller 29.23 hours respectively, and the wash-up device is no scheduled maintenance. For spare parts inventory strategies the result using RCS method are: transfer roller104 units, ink fountain roller requires 32 units, ink form roller 36 units and are holding spare policy required, and a wash-up device no holding spare parts. Keywords— Failure data, Maintenance System, RCM, RCS

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Fauzi, Z. A. M., and M. A. Mansor. "Development of Dynamic Programming Algorithm for Maintenance Scheduling Problem: A Conceptual Paper." International Journal of Engineering Technology and Sciences 5, no. 1 (June 6, 2018): 34–43. http://dx.doi.org/10.15282/ijets.v5i1.2823.

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Maintenance is one of the important methods that can be used to ensure the machines and equipment can operate within the best condition. A good scheduling for maintenance will maintain the proper performance since all resources will be utilised effectively as the underused of the resource can be reduced. The schedule created ensures the particular task was done within the time provided. What, when, where and how the certain operation will be done will be stated to make sure the planned activity going smoothly without any delays. However, the uncertainty that happened during the maintenance needs to be taken into account to create the fully optimised schedule. This change will affect the schedule developed and caused delays to the scheduled task. Once the beginning task is delayed, the following work will also be postponed. Thus, a mathematical model for maintenance scheduling for repairable and inspection of the machines and equipment was proposed to deal with the uncertainty that happened. This dynamic model will create the new schedule for the maintenance scheduling and help the manager in the decision-making process on where to assign the maintenance team when the uncertainty happened.

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Kramer, Barry Alan. "A Seasonal Schedule for Maintenance ECT." Journal of ECT 15, no. 3 (September 1999): 226???231. http://dx.doi.org/10.1097/00124509-199909000-00008.

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Németh, István, Ádám Kocsis, Donát Takács, Basheer W. Shaheen, Márton Takács, Angelo Merlo, Amit Eytan, Luisa Bidoggia, and Paolo Olocco. "Maintenance schedule optimisation for manufacturing systems." IFAC-PapersOnLine 53, no. 3 (2020): 319–24. http://dx.doi.org/10.1016/j.ifacol.2020.11.051.

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Andrade, Pedro, Catarina Silva, Bernardete Ribeiro, and Bruno F. Santos. "Aircraft Maintenance Check Scheduling Using Reinforcement Learning." Aerospace 8, no. 4 (April 17, 2021): 113. http://dx.doi.org/10.3390/aerospace8040113.

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This paper presents a Reinforcement Learning (RL) approach to optimize the long-term scheduling of maintenance for an aircraft fleet. The problem considers fleet status, maintenance capacity, and other maintenance constraints to schedule hangar checks for a specified time horizon. The checks are scheduled within an interval, and the goal is to, schedule them as close as possible to their due date. In doing so, the number of checks is reduced, and the fleet availability increases. A Deep Q-learning algorithm is used to optimize the scheduling policy. The model is validated in a real scenario using maintenance data from 45 aircraft. The maintenance plan that is generated with our approach is compared with a previous study, which presented a Dynamic Programming (DP) based approach and airline estimations for the same period. The results show a reduction in the number of checks scheduled, which indicates the potential of RL in solving this problem. The adaptability of RL is also tested by introducing small disturbances in the initial conditions. After training the model with these simulated scenarios, the results show the robustness of the RL approach and its ability to generate efficient maintenance plans in only a few seconds.

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Alhamad, Khaled, Rym M’Hallah, and Cormac Lucas. "A Mathematical Program for Scheduling Preventive Maintenance of Cogeneration Plants with Production." Mathematics 9, no. 14 (July 20, 2021): 1705. http://dx.doi.org/10.3390/math9141705.

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This paper considers the scheduling of preventive maintenance for the boilers, turbines, and distillers of power plants that produce electricity and desalinated water. It models the problem as a mathematical program (MP) that maximizes the sum of the minimal ratios of production to the demand of electricity and water during a planning time horizon. This objective encourages the plants’ production and enhances the chances of meeting consumers’ needs. It reduces the chance of power cuts and water shortages that may be caused by emergency disruptions of equipment on the network. To assess its performance and effectiveness, we test the MP on a real system consisting of 32 units and generate a preventive maintenance schedule for a time horizon of 52 weeks (one year). The generated schedule outperforms the schedule established by experts of the water plant; it induces, respectively, 16% and 12% increases in the surpluses while either matching or surpassing the total production. The sensitivity analysis further indicates that the generated schedule can handle unforeseen longer maintenance periods as well as a 120% increase in demand—a sizable realization in a country that heavily relies on electricity to acclimate to the harsh weather conditions. In addition, it suggests the robustness of the schedules with respect to increased demand. In summary, the MP model yields optimal systematic sustainable schedules.

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Zhang, Chuan Cheng, Cui Hui Yan, Sai Dai, Dan Xu, Yi Zhu, and Wei Dong. "Research and Application of Static Security Check for Monthly Maintenance Schedule." Advanced Materials Research 1070-1072 (December 2014): 1511–15. http://dx.doi.org/10.4028/www.scientific.net/amr.1070-1072.1511.

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Monthly maintenance schedule has an important guiding significance to day ahead maintenance arrangement. However, the current management of monthly maintenance schedule is short of quantitative analysis methods. Consequently it can’t effectively take the security risk that may exist under monthly maintenance schedule. This paper presents a static security checking method for monthly maintenance schedule. First, established the monthly power grid network model based on the realtime model and device state changes, including the commissioning and decommissioning devices and maintenance devices. Next, the month-contract energy was decomposed to every day and every hour, then combined with monthly load forecast and maintenance schedule, the power system typical operation modes were generated automatically. Finally, quantitative assessment of monthly maintenance schedule was completed by power flow calculation, security analysis and evaluation indexes, including load supply adequacy and equivalent generation capacity loss. This method is instructive for monthly maintenance arrangement and its feasibility is proved by practical application.

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Vakulin, E. A., V. A. Ivashkevich, E. I. I. Gnitsak, V. S. Baikin, and S. P. Maslyukov. "Assessment of maintenance schedule uniformity for Belaz dump trucks in Chernogorsky open pit mine." Mining informational and analytical bulletin, S64 (October 20, 2018): 127–33. http://dx.doi.org/10.25018/0236-1493-2018-12-64-127-133.

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Uniform schedule maintenance of mining and haulage machines is one of the key conditions for increasing productive time of maintenance personnel and decreasing monthly average servicing time. Currently, Russian mines infringe regulated maintenance schedule aimed to improve output per shift. The loss of time of maintenance personnel and equipment as a consequence maintenance irregularity is never assessed. This article presents assessment results on maintenance schedule uniformity in terms of dump trucks BelAZ-7513 and BelAZ-7530 at Chernogorsky open pit mine, SUEK-Khakassia. A variant of calculation of time loss owing to inconsistent maintenance schedule for dump trucks is proposed. The loss of time by maintenance personnel and by mining/haulage machines is assessed. The fleet of dump trucks BelAZ-7513 and BelAZ-7530 is analyzed depending on overtime of operation between maintenance periods. It is recommended to improve uniformity of maintenance schedule for mining and haulage equipment.

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Syakhroni, Akhmad, Rizka Fajar Adi Darmawan, and Novi Marlyana. "Machine Maintenance Design using Markov Chain Method to Reduce Maintenance Costs." International Journal of Education, Science, Technology, and Engineering 4, no. 1 (June 23, 2021): 6–25. http://dx.doi.org/10.36079/lamintang.ijeste-0401.224.

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PT. XYZ is a company that focuses on construction with ready mix concrete product (cast). The problem faced by the company is that the schedule is not suitable for machine maintenance activities so that it still results in high maintenance costs incurred by the company. By using the markov chain method can plan maintenance time in order to reduce downtime so as to minimize maintenance costs. The results obtained by the proposal for the company are for proposal I it takes 49.78 hours = 50 hours at a cost of Rp. 16,984,605, the cost savings of Rp. 73,545,395 (81.24%). Schedule for each machine such as wheel loaders every 14,009 hours, batching plant machines every 16,604 hours, truck mixer machines every 19,168 hours. Scheduling the second proposal will take 26.62 hours = 27 hours at a cost of Rp. 9,080,664, the cost savings of Rp. 81,449,336 (89.97%). Schedule for every machine such as wheel loaders every 7,490 hours, batching plant machines every 8,877 hours, mixer truck machines every 10,248 hours. Judging from the results obtained, the recommendation given is

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DODSON, BRYAN. "DETERMINING THE OPTIMUM SCHEDULE FOR PREVENTIVE MAINTENANCE." Quality Engineering 6, no. 4 (January 1994): 667–79. http://dx.doi.org/10.1080/08982119408918757.

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MARMIER, François, Christophe VARNIER, and Noureddine ZERHOUNI. "ROBUSTNESS MEASURE FOR FUZZY MAINTENANCE ACTIVITIES SCHEDULE." IFAC Proceedings Volumes 40, no. 18 (September 2007): 85–90. http://dx.doi.org/10.3182/20070927-4-ro-3905.00016.

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Yan, Shangyao, Fei-Yen Hsiao, Jyunjhih Guo, and Yu-Ching Chen. "Effective aircraft maintenance schedule adjustment following incidents." Transportation Planning and Technology 34, no. 8 (December 2011): 727–45. http://dx.doi.org/10.1080/03081060.2011.613582.

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Liu, Gehui, Shaokuan Chen, Hua Jin, and Shuang Liu. "Optimum opportunistic maintenance schedule incorporating delay time theory with imperfect maintenance." Reliability Engineering & System Safety 213 (September 2021): 107668. http://dx.doi.org/10.1016/j.ress.2021.107668.

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LIM, JAE-HAK, and DONG HO PARK. "OPTIMAL PERIODIC PREVENTIVE MAINTENANCE SCHEDULES WITH IMPROVEMENT FACTORS DEPENDING ON NUMBER OF PREVENTIVE MAINTENANCES." Asia-Pacific Journal of Operational Research 24, no. 01 (February 2007): 111–24. http://dx.doi.org/10.1142/s0217595907001139.

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This paper considers a periodic preventive maintenance policy under which each preventive maintenance (PM) reduces the hazard rate of the repairable system, while keeping the pattern of hazard rate unchanged. For this model, the hazard rate at a given time t is affected by the improvement factor which depends on the number of PMs conducted until t. In addition to the periodic preventive maintenance, the system undergoes the minimal repair at each failure between the preventive maintenances. We derive mathematical formulas to evaluate the expected cost rate per unit time by computing the expected number of failures depending on the hazard rate of the underlying life distribution of the system. Assuming that the system is replaced by a new one at the N-th preventive maintenance, the optimal values of N and the preventive maintenance period, which minimize the expected cost rate, are solved and thus the best schedules for the periodic preventive maintenance policy are established. Explicit solutions for the optimal schedule for the periodic preventive maintenance are presented when the failure times follow the Weibull distribution.

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Dwi Atmaji, Fransiskus Tatas, 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 1, no. 02 (December 29, 2017): 52. http://dx.doi.org/10.25124/ijies.v1i01.85.

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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.

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Hariyanto, Beny, and Romy Romy. "Maintenance Schedule Optimization for Turnaround Hot Gas Path Inspection of Gas Turbine in North Duri Cogeneration Plant Using Impact Method." Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse) 64, no. 1 (March 30, 2020): 25–32. http://dx.doi.org/10.36842/jomase.v64i1.159.

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North Duri Cogeneration Plant (NDC) is once of Chevron asset in IndoAsia Business Unit. The NDC location is in Duri, Province of Riau, Indonesia. The NDC has 3 units gas turbine and each unit has been combined with Heat Recovery Steam Generator (HRSG). An unit gas turbine NDC is produce electricity of 100 MW, and 1 unit of HRSG NDC that is produce steam of 360,000 BCWEPD (Barrel Cool Water Equivalent per Day). Hot gas path inspection (HGPI) is maintenance activities gas turbine, which routine scheduled in NDC every 3 years per unit. Maintenance schedule for turnaround HGPI gas turbine at NDC should be optimizing. By optimized of HGPI maintenance schedule can be maximized work plan, which is comply of 4 Key Performance Indicators there are Safety, Quality, Schedule and Cost through Initiative for Managing PA Cesetter Turnarounds (IMPACT). The result of optimal electricity production was increased by 13,174 MWh and the steam generated from units in NDC of mass total steam of 126,661 Mlbm and 371,827 BSPD.

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Oke, S. A., O. E. Charles-Owaba, and A. E. Oluleye. "Preventive Maintenance Scheduling." International Journal of Operations Research and Information Systems 4, no. 2 (April 2013): 69–94. http://dx.doi.org/10.4018/joris.2013040105.

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In this work, the effectiveness of preventive maintenance scheduling (PMS) decisions was reported based on a techno-economic model that reflects cost objective function for ship maintenance activities. With a potential to impact on both transportation businesses and users of transportation services, the model provides an alternative to the combined classical literature problems of spare-parts inventory management and control, failure prediction and reliability. The PMS model developed incorporates separate and combined functions of indirect, direct and factor maintenance costs. Idleness period for various formulated schedules are evaluated and compared. First, a general form of the preventive maintenance cost function incorporating unit cost of maintaining ships, a set of cost function parameters and variables was developed. The operations research framework for the problem is then applied to obtain test cases in which cost parameter(s) was/were used for scheduling decisions. Monte Carlo simulation is applied to generate additional test problems. Practical data were used to validate the model. For each problem, optimal schedules based on one to four cost parameters were determined. For each schedule, the total maintenance cost, cost of idleness, total ship idle period and total ship operation period were computed under inflation, opportunity and combined opportunity and inflation and compared with the values corresponding to maintenance cost parameter using t-test (p<0.05). Thus, the use of combined data from maintenance, opportunity and inflation for preventive maintenance scheduling of a fleet of ships is more effective than direct maintenance cost approach.

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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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Hsu, Chou-Jung. "Single-Machine Scheduling with Aging Effects and Optional Maintenance Activity Considerations." Mathematical Problems in Engineering 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/634503.

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This paper explores a single-machine scheduling with aging effects and the problem regarding optional maintenance activity assignment. The jobs’ processing time is assumed to follow a power position-dependent aging model. The optional maintenance activity refers to the situation in which the maintenance activity can be scheduled immediately after processing of any job has been completed except for the last job and the duration of maintenance activity can be of any value from zero to a fixed time interval. A recovery function is proposed to reflect the efficiency of the machine or worker which is improved. The objective of this study is to decide whether and when to implement the maintenance activity into the job sequence, how long the duration of maintenance activity is, and how to schedule so as to minimize the makespan. Once the duration of maintenance activity is known, we introduce an efficient solution for this problem. In addition, when the maintenance activity is completely performed, we showed that the optimal policy is to schedule the maintenance activity in the middle of the task sequence and optimally solved it by lower order algorithm. Finally, we extend the problem to the case of multiple maintenance activities which are completely performed. Hence, the problem is regarded as polynomial time solvable.

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Umeda, Shota, Kenji Tamaki, Masahiro Sumiya, and Yoshito Kamaji. "Planned Maintenance Schedule Update Method for Predictive Maintenance of Semiconductor Plasma Etcher." IEEE Transactions on Semiconductor Manufacturing 34, no. 3 (August 2021): 296–300. http://dx.doi.org/10.1109/tsm.2021.3071487.

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Franty, Yeny Krista, and Budhi Handoko. "The Determination of Preventive Maintenance using Simulated Annealing Algorithm Based on Weighted Fitness Function." Jurnal Teknik Industri 20, no. 1 (February 22, 2019): 53. http://dx.doi.org/10.22219/jtiumm.vol20.no1.53-61.

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This study aims to determine the machine maintenance schedule. We use the Simulated Annealing Algorithm. Fitness and reliability functions are functions that are used in the optimization process. Several weighting scenarios are done to see the unity of the function. The results of the scenario produce several alternative schedules. This algorithm is implemented on machines that have more than one sub-machine. This sub-machine is a smaller engine system part. This sub-machine also has one particular function. The results of the study show that the optimal engine maintenance period to use is six periods. There are five scheduling scenarios used in this problem. The resulting schedule can increase the value of reliability and can minimize costs.

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Shao Zhifang, Sun Lu, and Li Fujuan. "Optimization Model Integrated Flight Schedule and Maintenance Plans." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 5, no. 3 (February 15, 2013): 784–90. http://dx.doi.org/10.4156/aiss.vol5.issue3.91.

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Kim, In Kyum, Jun S. Lee, and Il-Yoon Choi. "Maintenance Schedule of Ballasted Track Using TMV Data." Journal of the Korean Society for Railway 21, no. 3 (April 30, 2018): 277–89. http://dx.doi.org/10.7782/jksr.2018.21.3.277.

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Tambe, Pravin P., and Makarand S. Kulkarni. "Selective maintenance optimization under schedule and quality constraints." International Journal of Quality & Reliability Management 33, no. 7 (August 1, 2016): 1030–59. http://dx.doi.org/10.1108/ijqrm-10-2014-0153.

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Purpose – The traditional practice for maintenance, quality control and production scheduling is to plan independently irrespective of an interrelationship exist between them. The purpose of this paper is to develop an approach for integrating maintenance, quality control and production scheduling. The objective is to investigate the benefits of the integrated effect in terms of the expected total cost of system operation of the three functions. Design/methodology/approach – The proposed approach is based on the conditional reliability of the components. Cost model for integrating selective maintenance, quality control using sampling-based procedure and production scheduling is developed using the conditional reliability. An integrated approach is such that, first an optimal schedule for the batches to be processed is obtained independently while the maintenance and quality control decisions are optimized considering the optimal schedule on the machine. The expected total cost of conventional approach, i.e. “No integration” is calculated to compare the effectiveness of integrated approach. Findings – The integrated approach have shown a higher cost saving as compared to the independent planning approach. The approach is practical to implement as the results are obtained in a reasonable computational time. Practical implications – The approach presented in this paper is generic and can be applied at planned as well as unplanned opportunities. The proposed integrated approach is dynamic in nature, as during maintenance opportunities, it is possible to optimize the decision on maintenance, quality control and production scheduling considering the current age of components and production requirement. Originality/value – The originality of the paper is in the approach for integration of the three elements of shop floor operations that are usually treated separately and rarely touched upon by researchers in the literature.

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Kline, Pat. "How Do I Formulate a Pump Maintenance Schedule?" Opflow 34, no. 6 (June 2008): 8–9. http://dx.doi.org/10.1002/j.1551-8701.2008.tb01990.x.

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Mariappan, V., A. Subash Babu, S. Rajasekaran, and K. Ilayaraja. "Collaborative optimal preventive maintenance schedule using goal programming." International Journal of Advanced Operations Management 3, no. 2 (2011): 153. http://dx.doi.org/10.1504/ijaom.2011.042138.

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Garg, R. K., Ankur Bahl, and Anish Sachdeava. "Optimizing Preventive Maintenance Schedule for a Distillery Plant." International Journal of Operational Research 1, no. 1 (2021): 1. http://dx.doi.org/10.1504/ijor.2021.10023879.

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Martynova, Dina, and Ping Zhang. "Optimization of Maintenance Schedule for Safety Instrumented Systems." IFAC-PapersOnLine 50, no. 1 (July 2017): 12484–89. http://dx.doi.org/10.1016/j.ifacol.2017.08.1928.

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Irfan, Irfan, and Muhammad Ikhsan Hamdy. "Simulasi Perbaikan System Maintenance dengan Pendekatan Konsep Lean Maintenance." Jurnal Energi Dan Manufaktur 12, no. 1 (June 7, 2019): 13. http://dx.doi.org/10.24843/jem.2019.v12.i01.p03.

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PT. Perkebunan Nusantara V mengolah kelapa sawit yang menghasilkan Crude Palm Oil (CPO) dengan produksi 60-ton TBS/jam. Proses produksi yang berlangsung di Perusahaan sering mengalami pemberhentian yang diakibatkan oleh tingginya frekuensi kerusakan mesin thresher dikarenakan sistem perawatan yang belum optimal menyebabkan waktu penundaan (Down Time) 2-3 jam untuk proses perbaikan di mesin tersebut. Hal ini dapat dilihat pada data kondisi mesin thresher tahun 2018 yaitu terdapat 18 kali komponen mesin yang harus mengalami perawatan di luar dari perawatan mesin. Permasalahan ini bisa terjadi 4-5 kali dalam 1 bulan berdampak buruk pada perusahaan yaitu menurunkan jumlah rendemen. Maka dari itu pada penelitian ini akan dilakukan penentuan aktifitas perawatan mesin tresher agar kerusakan pada mesin dapat diminimalisir dengan pendekatan Failure Mode Effect Analysis (FMEA) dan Realibility Centered Maintenance (RCM). Dari hasil FMEA terhadap 18 komponen mesin tresher dengan RPN terbesar adalah Gearbox dengan nilai 648 poin. Selanjutnya dari hasil RCM dengan aktifitas perawatan schedule on condition dan schedule on restoration task terdapat 9 komponen. Untuk hasil dari MVSM pada proses penggantian komponen mesin tresher terdapat delay maka dilakukan simulasi arena dan penjadwalan penggantian komponen mesin, maka nilai efisiensi penggantian meningkat untuk komponen Gearbox dari 40% naik menjadi 54,26%. PT. Perkebunan Nusantara V processes oil palm which produces Crude Palm Oil (CPO) with a production of 60 tons of FFB / hour. The production process that takes place at the Company often has a stop caused by the high frequency of damage to the engine thresher because the maintenance system that has not been optimal causes a delay time (Down Time) of 2-3 hours for the repair process on the engine. This can be seen in the data on the condition of the thresher engine in 2018, which is 18 times the engine components that have to be treated outside the engine maintenance. This problem can occur 4-5 times in 1 month which has a negative impact on the company, namely reducing the amount of yield. Therefore, this research will determine the tresher engine maintenance activities so that damage to the engine can be minimized using the Failure Mode Effect Analysis (FMEA) approach and Reliability Centered Maintenance (RCM). From the results of the FMEA on the 18 components of the tresher engine with the largest RPN is Gearbox with a value of 648 points. Furthermore, from the RCM results with maintenance schedule on condition activities and schedule on restoration tasks there are 9 components. For the results of MVSM in the replacement process of tresher engine components there is delay, then an arena simulation and scheduling of engine components are replaced, then the value of replacement efficiency increases for Gearbox components from 40% to 54.26%.

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Ren, Hui, Ran Ran Cui, and Yan Tang. "An Optimization Model for Condition-Based Maintenance Decision Considering Total Risk of Grid Operation." Advanced Materials Research 1055 (November 2014): 383–88. http://dx.doi.org/10.4028/www.scientific.net/amr.1055.383.

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In the background of condition-based maintenance (CBM), the equipment maintenance levels in a certain state have different choices, which has different impacts on the improvement of the equipment state and maintenance costs, which in turn affects the time schedule of equipment maintenance. Therefore, in this paper the equipment maintenance time and maintenance level are viewed as decision variables to make maintenance schedules. This paper presents a risk-based optimization model for system maintenance scheduling problem, considering the state of equipment, correlations of the equipment and the operation of grid. An optimization model minimizing total risk of grid operation by balancing system maintenance risk and failure risk is established, so that both optimal maintenance level and optimal maintenance time could be determined simultaneously. An example is taken to verify the validity of the model.

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Priyatna, Bayu, Topan Trianto, Julifer P. Manurung, Nono Heryana, and Arip Solehudin. "Sistem Preventive Maintenance Berbasis Web dengan Menggunakan Algoritma Priority Scheduling pada PT. Beta Pharmacon." INTERNAL (Information System Journal) 3, no. 2 (January 4, 2021): 41–53. http://dx.doi.org/10.32627/internal.v3i2.112.

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PT. Beta Pharmacon in the actual preparation of Preventive Maintenance (PM) schedules and input of reports or preventive results data still uses Microsoft Excel, and preventive schedules that have been made are sometimes not following the actual because the machine cannot be maintained (the production process has not been completed) so that the schedule has been completed. Determined to change and to confirm whether preventive maintenance can be done every day, still by telephone. Based on the above problems, a web-based Preventive Maintenance System will be created using the priority scheduling algorithm. The web is built using the CodeIgniter framework and database using MySQL. With this system, it can facilitate scheduling of preventive maintenance, data collection of machines and tools in the company, search for data on preventive maintenance results, coordination of the implementation of preventive maintenance, so that it can provide the information needed effectively and efficiently.

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Gubin, Pavel Yu, and Vladislav P. Oboskalov. "The initialization of initial generating equipment maintenance schedules while a heuristic method is used." Vestnik of Samara State Technical University. Technical Sciences Series 29, no. 2 (August 30, 2021): 6–23. http://dx.doi.org/10.14498/tech.2021.2.1.

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Currently, heuristic methods based on iterative changing of feasible solutions set provide a perspective tool for generation equipment maintenance scheduling in power systems. Wherein effectiveness of a heuristic method depends significantly on the initial set of possible schedules or in other words quality of the method initialization. In this case, a widely used methodology of building the initial array of solutions on the basis of pseudorandom uniform generation of control variables seems to be only palliative way to access the problem. This paper proposes alternative initialization procedure drawing on the example of generating units maintenance planning with heuristic differential evolution method. The principle of this method is to get initial set of solutions utilizing normal probability distribution to generate pseudorandom deviations from the suboptimal maintenance schedule which is to be preliminarily formed using directed search method. Following this approach allows to improve probabilistic characteristics of resultant maintenance schedule in particular to decrease median value of an objective function and its coefficient of variation, and to maximize probability to get the combination of units outage moments completely suiting operational constraints.

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Wirdianto, Eri, Irfan Nugraha Putra Mukhti, Alexie Herryandie Bronto Adi, and Milana Milana. "Model Penjadwalan Pemeliharaan Preventif Mesin-Mesin Produksi untuk Meminimasi Total Tardiness." INVOTEK: Jurnal Inovasi Vokasional dan Teknologi 20, no. 1 (February 10, 2020): 123–36. http://dx.doi.org/10.24036/invotek.v20i1.629.

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Preventive maintenance is considered as a method to avoid unexpected failure in production machines. Unfortunately, conducting such maintenance is limited by resources availability thus likely causes tardiness. This research aims to minimize total tardiness of preventive maintenance on production machines by developing a scheduling model. This scheduling model takes the availability of time and labor into account to get an optimal scheduling model that can minimize the tardiness. The model of preventive maintenance schedule is developed by using the Integer Linear Programming method. This method provides output in the form of preventive maintenance schedule through a purpose function which considers the specified constraints on the company. As the result, the developed model could propose a preventive maintenance schedule which reduces the total tardiness.

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Claudia, Angeline. "Analysis of Repairing Maintenance Schedule and Maintenance Management Designing in PT Horizon Investment." International Journal of Advanced Trends in Computer Science and Engineering 9, no. 4 (August 25, 2020): 5193–99. http://dx.doi.org/10.30534/ijatcse/2020/146942020.

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HUANG, JIANSHENG, and O. GEOFFREY OKOGBAA. "A HEURISTIC REPLACEMENT SCHEDULING APPROACH FOR MULTI-UNIT SYSTEMS WITH ECONOMIC DEPENDENCY." International Journal of Reliability, Quality and Safety Engineering 03, no. 01 (March 1996): 1–10. http://dx.doi.org/10.1142/s0218539396000028.

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For a multi-unit system with economic dependency, it is difficult to develop an effective joint replacement schedule due to the stochastic complexity of the system failure-repair process. As a result, restrictions have often been introduced in the maintenance policy specification and decision problem formulation. In some cases, these restrictions have resulted in a reduction in the optimality or effectiveness of the proposed schedule. In this paper, we propose a general opportunistic maintenance policy for multi-unit systems with economic dependency. Two cost boundary conditions are developed in order to evaluate the potential cost savings achieved by implementing the opportunistic maintenance policy. A heuristic approach based on the application of the single-unit model is presented for developing the opportunistic maintenance schedule via an example problem. The effectiveness of the resulting schedule is demonstrated through simulation experiments.

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Block, Henry W., Naftali A. Langberg, and Thomas H. Savits. "Maintenance comparisons: block policies." Journal of Applied Probability 27, no. 3 (September 1990): 649–57. http://dx.doi.org/10.2307/3214548.

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Complete repair and minimal repair models with a block maintenance policy are considered. Each of these models gives rise to a counting process, and these processes are compared stochastically. This contrasts with most previous work on maintenance policies where only univariate marginal comparisons were made. Also a more general block schedule is considered than is customary.

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Block, Henry W., Naftali A. Langberg, and Thomas H. Savits. "Maintenance comparisons: block policies." Journal of Applied Probability 27, no. 03 (September 1990): 649–57. http://dx.doi.org/10.1017/s0021900200039188.

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Complete repair and minimal repair models with a block maintenance policy are considered. Each of these models gives rise to a counting process, and these processes are compared stochastically. This contrasts with most previous work on maintenance policies where only univariate marginal comparisons were made. Also a more general block schedule is considered than is customary.

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Tong, Fei, and Yuyang Peng. "A Data-Gathering, Dynamic Duty-Cycling MAC Protocol for Large-Scale Wireless Sensor Networks." Sensors 20, no. 15 (July 22, 2020): 4071. http://dx.doi.org/10.3390/s20154071.

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This paper presents a Data-gathering, Dynamic Duty-cycling (D3) protocol for wireless sensor networks. With a proposed duty-cycling MAC of high energy efficiency in D3, a routing scheme is naturally embedded to reduce protocol overhead. A packet can be forwarded in a pipelined fashion by staggering the sleep-wakeup schedules between two communicating nodes, which can significantly reduce end-to-end delay to meet real-time transmission requirements. To construct and maintain schedules, a grade and schedule establishment mechanism with a lightweight schedule error correction scheme is designed. In addition, based on the intrinsic characteristics of the network, an adaptive schedule maintenance scheme is proposed to dynamically adjust the node duty cycle to the network traffic load. The results based on the extensive OPNET simulations show that D3 can largely improve packet delivery ratio, energy efficiency and throughput, and reduce packet delivery latency.

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Maukar, Anastasia Lidya, Ineu Widaningsih Sosodoro, and Rhiza Adiprabowo. "Scheduling Preventive Maintenance on Auto Rooting Machine at Toys Manufacturer Company." Jurnal Rekayasa Sistem Industri 5, no. 1 (April 29, 2016): 26. http://dx.doi.org/10.26593/jrsi.v5i1.1910.26-30.

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Maintenance cost becomes one of the problems that manufacturing company is facing nowadays due to lack of maintenance system. The main objective of this research is to reduce the maintenance cost on auto rooting machine in toy manufacturer by developing a scheduled preventive maintenance. Data of machine breakdowns and costs related to maintenance, components, and the interval time of failure for each machine were collected. To develop a preventive maintenance system, the interval of component replacement must be determined. The minimum cost model is attained by finding the right interval time. The result of this research shows that by implementing proposed maintenance schedule the machine reliability has 45% increase and maintenance cost decreases by 48%.

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Jo, Hyung-Chul, Rakkyung Ko, and Sung-Kwan Joo. "Generator Maintenance Scheduling Method Using Transformation of Mixed Integer Polynomial Programming in a Power System Incorporating Demand Response." Energies 12, no. 9 (April 30, 2019): 1646. http://dx.doi.org/10.3390/en12091646.

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Periodic preventive maintenance of generators is required to maintain the reliable operation of a power system. However, generators under maintenance cannot supply electrical energy to the power system; therefore, it is important to determine an optimal generator maintenance schedule to facilitate efficient supply. The schedule should consider various constraints of the reliability-based demand response program, power system security, and restoration. Determining the optimal generator maintenance schedule is generally formulated as a non-linear optimization problem, which leads to difficulties in obtaining the optimal solution when the various power system constraints are considered. This study proposes a generator maintenance scheduling (GMS) method using transformation of mixed integer polynomial programming in a power system incorporating demand response. The GMS method is designed to deal with various system requirements and characteristics of demand response within a power system. A case study is conducted using data from the Korean power system to demonstrate the effectiveness of the proposed method for determining the optimal maintenance schedule. The results show that the proposed GMS method can be used to facilitate the efficient and reliable operation of a power system, by considering the applicable system constraints.

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Bensana, E. "Remora - A Planning Approach to Schedule Maintenance and Revision." IFAC Proceedings Volumes 26, no. 2 (July 1993): 265–68. http://dx.doi.org/10.1016/s1474-6670(17)48468-0.

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Suliman, Saad M. A., and Sayed Husain Jawad. "Optimization of preventive maintenance schedule and production lot size." International Journal of Production Economics 137, no. 1 (May 2012): 19–28. http://dx.doi.org/10.1016/j.ijpe.2012.01.006.

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Journal articles on the topic 'Schedule maintenance'

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