Optimal track geometry maintenance limits using machine learning: A case study

2020 ◽  
pp. 095440972097009
Author(s):  
Ahmad Kasraei ◽  
Jabbar Ali Zakeri ◽  
Arash Bakhtiary
Keyword(s):  
Clustering Algorithm ◽  
Cost Model ◽  
Maintenance Cost ◽  
Maintenance Costs ◽  
Corrective Maintenance ◽  
Track Geometry ◽  
Penalty Costs ◽  
Optimal Maintenance ◽  
Maintenance Activities ◽  
Maintenance Model

The aim of this study has been to determine the optimal maintenance limits for one of the main railway lines in Iran in such a way that the total maintenance costs are minimized. For this purpose, a cost model has been developed by considering costs related to preventive maintenance activities, corrective maintenance activities, inspection, and a penalty costs associated with exceeding corrective maintenance limit. Standard deviation of longitudinal level was used to measure the quality of track geometry. In order to reduce the level of uncertainty in the maintenance model, K-means clustering algorithm was used to classify track sections with most similarity. Then, a linear function was used for each cluster to model the degradation of track sections. Monte Carlo technique was used to simulate track geometry behavior and determine the optimal maintenance limit which minimizes the total maintenance costs. The results of this paper show that setting an optimal limit can affect total annual maintenance cost about 27 to 57 percent.

scholarly journals Predictive Group Maintenance Model for Networks of Bridges

2020 ◽  
Vol 2674 (4) ◽  
pp. 373-383 ◽  
Author(s):  
Georgios M. Hadjidemetriou ◽  
Xiang Xie ◽  
Ajith K. Parlikad
Keyword(s):  
Predictive Model ◽  
Recent Progress ◽  
Cost Model ◽  
Practical Significance ◽  
Optimal Time ◽  
Setup Cost ◽  
Maintenance Costs ◽  
Deterioration Model ◽  
Scheduling Model ◽  
Maintenance Model

Recent progress in the monitoring and prediction of the condition of infrastructure using sensing technologies has motivated researchers and infrastructure owners to explore the benefits of asset predictive maintenance, as an alternative to reactive maintenance. However, the application of predictive group maintenance for multi-system multi-component networks (MSMCN) has not received much attention in the literature or in practice. The paper presents an approach that prioritizes the maintenance of MSMCN of bridges, using a deterioration model of components with uncertainty, a lifecycle cost model, a predictive model for the optimal time for maintenance based on the latest inspection, a group maintenance model to reduce setup cost, and a scheduling model considering budget constraints. This model has been applied to a network of 15 bridges constituted by multiple heterogeneous components, and, compared with the Structures Investment Toolkit, it showed potential for a substantial decrease in maintenance costs, thus highlighting the practical significance of the presented approach.

scholarly journals Effective time interval for railway track geometry inspection

2020 ◽  
Vol 53 (1) ◽  
pp. 53-65 ◽  
Author(s):  
Ahmad Kasraei ◽  
Jabbar Ali Zakeri
Keyword(s):  
Decision Making ◽  
Railway Track ◽  
Sensitivity Analyses ◽  
Maintenance Cost ◽  
Time Interval ◽  
Maintenance Policy ◽  
Corrective Maintenance ◽  
Track Geometry ◽  
Inspection Interval ◽  
Geometry Inspection

A proper decision-making scheme for track geometry maintenance requires a knowledge of the real condition of track geometry. Therefore, the track must be inspected by measurement cars at different time intervals. The frequency of track geometry inspection plays a crucial role in decision-making and has always been a big concern for infrastructure managers. The inspection interval should be chosen properly, it means that the small period can decrease the capacity of line and affect the operation of network and the big period can result in low quality of track and in some cases derailments and possible loss of human lives. The aim of this paper is to determine the effective inspection interval such that the total maintenance cost is minimized. In the proposed cost model, the costs of inspection, preventive maintenance, corrective maintenance and the penalty for exceeding the corrective maintenance level are considered. A case study is performed on a real dataset collected from a railway line in Iran. The standard deviation of longitudinal level is considered to measure track geometry degradation. A widely applied linear model is used to model track geometry degradation over time. Monte Carlo technique is used to simulate the track geometry behavior under various track geometry inspection intervals. In addition, a set of sensitivity analyses are carried out to assess the effect of various inspection intervals on different terms of maintenance cost. The results indicate that not only can substantial costs be saved by setting effective inspection intervals, but also the time during which the track suffers from bad conditions is dramatically reduced. The result of this study has shown the appropriate inspection interval for the studied case can result in 13.6 percent decrease in maintenance cost in comparison with the current maintenance policy. Besides, it would lead to more reliable railway track by preventing the system exceed the corrective threshold.

scholarly journals Evaluasi Manajemen Perawatan dengan Metode Reliability Centered Maintenance (RCM) II pada Mesin Cane Cutter 1 dan 2 di Stasiun Gilingan PG Meritjan - Kediri

Rekayasa ◽  
2017 ◽  
Vol 10 (2) ◽  
pp. 99
Author(s):  
Cahyo Purnomo Prasetyo
Keyword(s):  
Maintenance Cost ◽  
Repair Cost ◽  
Maintenance Policy ◽  
Work Safety ◽  
Maintenance Costs ◽  
Reliability Centered Maintenance ◽  
Optimal Maintenance ◽  
Critical Components ◽  
Optimal Maintenance Policy ◽  
Production Target

<p>Penelitian ini bertujuan untuk menentukan kebijakan perawatan optimal yang dapat mengurangi biaya perbaikan (repair cost) dan biaya konsekwensi operasional (operational consequence cost). Metode yang diterapkan pada penelitian ini adalah Reliability Centered Maintenance (RCM) II. Penelitian ini difokuskan pada mesin Cane Cutter 1 dan 2 dengan pertimbangan beberapa aspek yaitu : pengaruh kegagalan terhadap pencapaian target produksi, resiko keselamatan kerja dan biaya perawatan yang akan ditimbulkan. Dari hasil penelitian dapat diketahui bahwa komponen kritis pada mesin Cane Cutter 1 dan 2 adalah : Pisau dan Baut Pisau. Perawatan yang dilakukan untuk mengantisipasi dan mengatasi kegagalan yang terjadi pada komponen mesin tersebut adalah proactive task yang meliputi : scheduled restoration task dan scheduled discard task. Rata-rata penurunan biaya perawatan total yang didapatkan dengan mengurangkan ‘biaya total pada interval perawatan awal’ dan ‘biaya total pada interval perawatan optimal’ adalah 14,82 %.</p><p>Kata Kunci: cane cutter, downtime, pabrik gula.</p><p><strong> </strong></p><p><strong>ABSTRACT</strong></p><p><em>This research aims to determine the optimal maintenance policy which could reduce repair cost and operational consequence cost. The methods which applied in this research is Reliability Centered Maintenance (RCM) II. This research focuses on Cane Cutter 1 and 2 machines by considering several aspects, such as and effect of any failure on production target achievement, work safety risk and maintenance cost which might be caused by the critical condition. The result showed that some critical components at the Cane Cutter 1 and 2 machines were : Blade and Blade Bolt. The maintenance which could be done to anticipate and deal with any failure occurring in the machine components was called proactive task comprising : scheduled restoration task and scheduled discard task. The average reduction in total maintenance costs which was obtained by subtracting ‘total costs at initial maintenance interval’ and ‘total costs at optimal maintenance interval’ amounted to 14,82 %.</em></p><p><em>Keywords: cane cutter, downtime, sugar factory</em></p>

Assessing Maintenance Cost for Design or Re-Design of Complex Machinery

2002 ◽  
Author(s):  
Alley Butler ◽  
Dan Baldwin ◽  
Mohit Kashyap
Keyword(s):  
Cost Model ◽  
Open Architecture ◽  
Maintenance Cost ◽  
Preventative Maintenance ◽  
Maintenance Costs ◽  
Time Value Of Money ◽  
Turbine Generators ◽  
System Data ◽  
The Cost

Maintenance costs are often significant for complex machinery, and organizations that are able to accurately assess maintenance costs for complex machinery can design or re-design the machinery to reduce maintenance expenses. This paper provides a review of relevant reliability theory to provide a background for model construction. The maintenance cost model is then developed from a probabilistic perspective, with a hierarchical breakdown of the complex machinery, and with consideration of the time value of money. A framework for the cost model is offered in which the cost of repair and preventative maintenance is considered along with the downtime costs for repair or preventative maintenance. As a proof of concept, maintenance costs for Ship Service Gas Turbine Generators (SSGTG) are developed from the Navy’s OARS (Open Architecture Retrieval System) data. Problems with data quality and heuristic adjustment of the data are discussed, recognizing that work is ongoing to improve the quality of the Navy’s maintenance data. Cognition Corporation’s Cost Advantage software is used for the modeling effort, providing an ability to focus on maintenance cost at any level of detail and to obtain cost roll up, as needed. Conclusions are drawn with respect to the modeling of maintenance costs for complex machinery.

An integrated space-based building maintenance management model using multi-objective optimization

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huthaifa AL-Smadi ◽  
Abobakr Al-Sakkaf ◽  
Tarek Zayed ◽  
Fuzhan Nasiri
Keyword(s):  
Residential Buildings ◽  
Maintenance Cost ◽  
Content Type ◽  
Fund Allocation ◽  
Building Maintenance ◽  
Window System ◽  
Optimal Maintenance ◽  
Building Condition ◽  
Maintenance Model

PurposeThe purpose of this study is to minimize cost and minimize building condition. Weibull distribution approach was employed to generate deterioration curves over time. The third floor of Concordia University’s Engineering And Visual Arts (EV) Complex in Montreal, Canada, served as a case study to test the maintenance model and determine the optimal maintenance activities to be performed.Design/methodology/approachThis research has demonstrated that there is insufficient fund allocation for the maintenance of non-residential buildings. Therefore, this research focused on designing and developing a maintenance optimization model that provides the type of spaces (architectural system) in a building. Sensitivity analysis was used to calculate weights to validate the model. Particle swarm optimization, based explicitly on multiple objectives, was applied for the optimization problem using MATLAB.FindingsFollowing 100 iterations, 13 non-dominant solutions were generated. Not only was the overall maintenance cost minimized, but the condition of the building was also maximized. Moreover, the condition prediction model demonstrated that the window system type has the most rapid deterioration in educational buildings.Originality/valueThe model is flexible and can be modified by facility managers to align with the required codes or standards.

Maintenance cost assessment for heterogeneous multi-component systems incorporating perfect inspections and waiting time to maintenance

2021 ◽  
pp. 1748006X2110388
Author(s):  
Lucía Bautista ◽  
Inma T Castro ◽  
Luis Landesa
Keyword(s):  
Heuristic Algorithms ◽  
Cost Model ◽  
System Level ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Industrial Systems ◽  
Inspection Strategy ◽  
Optimal Maintenance ◽  
Systems Maintenance ◽  
Safety Constraint

Most existing research about complex systems maintenance assumes they consist of the same type of components. However, systems can be assembled with heterogeneous components (for example degrading and non-degrading components) that require different maintenance actions. Since industrial systems become more and more complex, more research about the maintenance of systems with heterogeneous components is needed. For this reason, in this paper, a system consisting of two groups of components: degrading and non-degrading components is analyzed. The main novelty of this paper is the evaluation of a maintenance policy at system-level coordinating condition-based maintenance for the degrading components, delay time to the maintenance and an inspection strategy for this heterogeneous system. To that end, an analytic cost model is built using the semi-regenerative processes theory. Furthermore, a safety constraint related to the reliability of the degrading components is imposed. To find the optimal maintenance strategy, meta-heuristic algorithms are used.

MODEL BIAYA PEMELIHARAAN FASILITAS PADA BANDAR UDARA NGURAH RAI BALI

1970 ◽  
Author(s):  
Reni Dewita ◽  
I G. A. Adnyana Putera ◽  
I G. Putu Suparsa
Keyword(s):  
Linear Regression ◽  
Cost Model ◽  
Regression Equation ◽  
Maintenance Cost ◽  
Quality Level ◽  
Road Maintenance ◽  
Linear Regression Equation ◽  
Maintenance Costs ◽  
Facility Maintenance ◽  
The Cost

Facilities in an airport requires maintenance activity in order to achieve excellent quality level and able to support activities at the airport to avoid negative impacts, which is the declining quality of the facility that can lead to lower levels of the productivity carried out in an airport. Maintenance facilities at Bali's Ngurah Rai airport need the maintenance costs planning. To get proper maintenance actions,  the maintenance costs early stages of planning phase needs to develop a model of facility maintenance costs that can provide the maintenance costs estimates quickly and accurately. To produce a maintenance costs model we should identify the maintenance activities that exist at Ngurah Rai airport. Maintenance costs data used is within the last 5 years (2007-2011). Using the Cost Significant Model methode and the linear regression equation it showed that several of the facility maintenace significantly affect the facility maintenance costs in the Ngurah Rai Airport which is the cost of passenger terminal building maintenance (X6), the cost of runway maintenance (X1), the cost of taxiway maintenance (X2), the cost of air conditioning installation maintenance (X14), the cost of road maintenance (X4), the cost of vehicle parking maintenance (X5), and the cost of navigation and communication equipment maintenance (X10). There is 3  linear regression equation model which is 1) Y = 11873745878,77 + 0,993 X1 + 0,826 X2 + 0,334 X4 + 1,181 X6, 2) Y = -698840481,94 + 1,327 X1 + 1,716 X2 + 5,516 X5+ 3,060 X14, and 3) Y = 82110363478,07 + 1,013 X1 - 17,223X5 + 22,406 X10 - 12,035 X14. After doing the Cost Model Factor (CMF) test to the three linear regression equation, the most accurate equation is linear regression equation Y = 82110363478,07 + 1,013 X1 - 17,223X5 + 22,406 X10 - 12,035 X14 that has the average ratio 0.006% of the actual cost, so it is the best facility maintenance cost model at Bali's Ngurah Rai Airport.

scholarly journals Mass Rapid Transit Operation and Maintenance Cost Calculation Model

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Rahmat Nurcahyo ◽  
F. Farizal ◽  
Bimo M. I. Arifianto ◽  
Muhammad Habiburrahman
Keyword(s):  
Cost Model ◽  
Calculation Model ◽  
Maintenance Cost ◽  
Cost Calculation ◽  
Rapid Transit ◽  
Maintenance Costs ◽  
Operation And Maintenance ◽  
Transit Operation ◽  
The Cost ◽  
Mass Rapid Transit

Mass rapid transit (MRT) is an efficient transportation mode that is urgently needed by a growing city such as Jakarta, Indonesia. However, limited research has attempted to evaluate the system’s current performance through a comprehensive, unit-based calculation of the costs of MRT operation and maintenance. This research aimed to develop a system for calculating and comparing MRT operation and maintenance costs per kilometer per year. The cost model has three components, namely, capital, operation cost, and maintenance cost, which are, respectively, calculated based on their percentage toward total cost. The cost model calculation determined that Jakarta MRT operation and maintenance costs total USD 8.44 million per kilometer per year. This result was compared to other countries’ MRT operations.

Maintenance optimization for marine mechanical systems

2019 ◽  
Vol 234 (2) ◽  
pp. 446-462
Author(s):  
David Kimera ◽  
Fillemon Nduvu Nangolo
Keyword(s):  
Mechanical System ◽  
Expert Knowledge ◽  
Mechanical Systems ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Maintenance Costs ◽  
Cost Rate ◽  
Optimal Maintenance ◽  
Optimal Maintenance Policy ◽  
Marine Vehicle

This article proposes a stochastic technique for determining the optimal maintenance policy for marine mechanical systems. The optimal maintenance policy output includes the average maintenance cost rate, maintenance interval and the performance thresholds for the three marine mechanical system classifications. The purpose of this study is to optimize maintenance, maintenance interval and performance thresholds based on maintenance and reliability data of the marine mechanical systems. Performance threshold and maintenance interval are used as the decision variables to determine the optimal maintenance policy. A stochastic model based on probability analysis is developed to trigger the maintenance action for mechanical systems. The model is later coded in MATLAB. Maintenance and failure data for a marine vehicle were statistically fitted using ReliaSoft, from which a three-parameter Weibull distribution best fitted all the mechanical system classifications. Model inputs were based on both the maintenance data and expert knowledge of the maintenance crew. Based on a 20-year marine vehicle life span, the optimal maintenance costs for plant and machinery are relatively the same. The model predicted annual total maintenance cost of US$183,029.24 is 11.11% more than the maintenance cost derived from experts’ threshold of US$164,726. Marine vehicle machinery presents a higher maintenance interval of 3.23 years compared to 2.92 years for marine vehicle plants. It was observed that for the performance thresholds greater than 84.54%, there is an insignificant difference between the plant and machinery maintenance costs. Sensitivity analysis results suggest there is little justification that changing maintenance costs will have an impact on the performance threshold [Formula: see text] and maintenance interval [Formula: see text]. A maintenance interval of 3 years results in a lower total annual maintenance cost deviation of 2.66% from the optimal total annual maintenance cost.

scholarly journals ANALISIS PEMELIHARAAN MESIN CCO (CRUDE COCONUT OIL) STUDI KASUS PADA PT. SPO AGRO RESOURCES

2020 ◽  
Vol 6 (1) ◽  
pp. 10-19
Author(s):  
Dewi Sartika ◽  
Asngadi Asngadi ◽  
Syamsuddin Syamsuddin
Keyword(s):  
Preventive Maintenance ◽  
Quantitative Methods ◽  
Coconut Oil ◽  
Maintenance Cost ◽  
Maintenance Costs ◽  
Machine Maintenance ◽  
Time Period ◽  
Calculation Results ◽  
Maintenance Activities ◽  
Maintenance Policies

This  study  aims  to  determine  and  analyze  machine  maintenance carried  out  by  PT.  SPO  Agro Resources and to find out whether the presence of preventive maintenance policies can improve the effectiveness  of  time  and  costs.  This  research  uses  qualitative methods  by  describing  maintenance activities carried out by PT. SPO Agro Resources, as well as using quantitative methods in the form of mathematical  statistics  as  a  tool  to  help  decide  policies  to  be taken  at  a  certain  time  period  and efficiency  measurements  using descriptive  percentages.  The  results  showed  preventive  maintenance costs  once  a  month  Rp.138,012,968, - efficiency  value  was  39.63%, preventive  maintenance  costs every two months Rp.196,689,315, - efficiency value was 56.48%, preventive maintenance costs every three months  Rp.  258,731,341, - the  efficiency  value  is  74.29%,  repair maintenance  costs Rp.247,164,000, - the efficiency value is 70.97%. Based on the calculation it is known that the policy that  makes maintenance  costs  efficient  is  maintenance  once  a  month  because this  policy  is  the smallest maintenance cost compared to other policies, where the percentage value is smaller which is 39.63%,  according  to table  2 which  states  if  the  calculation  results  are  below 60%  said  to  be  very efficient. Penelitian  ini bertujuan  untuk  mengetahui  dan  menganalisis pemeliharaan  mesin  yang  dilakukan oleh PT. SPO Agro Resources dan untuk mengetahui apakah dengan adanya kebijakan pemeliharaan pencegahan  dapat  meningkatkan  efektivitas  waktu  dan  biaya. Penelitian  ini menggunakan metode kualitatif dengan menjabarkan aktivitas kegiatan pemeliharaan yang dilaksanakan oleh PT. SPO Agro Resources, serta  menggunakan  metode  kuantitatif  berupa  statistik matematik  sebagai  alat  untuk membantu  memutuskan  kebijakan yang  akan  diambil  pada jangka  waktu  tertentu  dan pengukuran efisiensi  menggunakan deskriptif  presentase.  Hasil  penelitian menunjukkan  biaya pemeliharaan pencegahan sebulan sekali Rp.138.012.968,- nilai efisiensinya 39,63%,  biaya pemeliharaan pencegahan  dua  bulan  sekali  Rp.196.689.315,- nilai  efisiensinya 56,48%,  biaya pemeliharaan pencegahan  tiga  bulan  sekali Rp.258.731.341,- nilai  efisiensinya 74,29%, biaya pemeliharaan perbaikan Rp.247.164.000,- nilai  efisiensinya 70,97%.  Berdasarkan perhitungan diketahui bahwa kebijakan yang mengefisiensikan  biaya pemeliharaan  yaitu pemeliharaan  sebulan  sekali karena kebijakan ini biaya  pemeliharaannya paling  kecil  dibandingkan  dengan  kebijakan yang  lain, dimana nilai  persentasenya  lebih  kecil  yaitu  39,63%, sesuai  dengan tabel  2 yang  menyatakan  apabila  hasil perhitungan di bawah 60% maka dikatakan sangat efisien.

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