scholarly journals Delayed maintenance modelling considering speed restriction for a railway section

2017 ◽  
Vol 231 (4) ◽  
pp. 411-428
Author(s):  
Hui Shang ◽  
Christophe Bérenguer ◽  
John Andrews
Keyword(s):  
Survival Time ◽  
Preventive Maintenance ◽  
Railway Track ◽  
System Throughput ◽  
Maintenance Cost ◽  
Decision Variable ◽  
Track Geometry ◽  
Coloured Petri Net ◽  
Maintenance Activities ◽  
System Benefit

The deterioration of track geometry depends on several factors of which the speed of the train is one. Imposing a speed restriction can slow down the track deterioration and allows a longer survival time before a serious condition is achieved. Preventive maintenance delays can be authorized during the survival time. However, speed restrictions also reduce the system throughput. On the other hand, a longer interval between preventive maintenance activities has a lower maintenance action cost and it also enables grouping the maintenance activities to save set-up costs as well as system downtime. If the repair delay is too long, it may cause unacceptable conditions on the track and lead to higher maintenance costs and accidents. Therefore, it is interesting to assess the effect of a speed restriction on the delayed maintenance strategies for a railway track section. We want to solve a maintenance optimization problem to find the optimal tuning of the maintenance delay time and imposition of a speed restriction. To this aim, a delayed maintenance model is developed, in which track deterioration depends on the train speed and the number of passing trains. The model is used to determine an optimal speed restriction strategy and a preventive repair delay for the optimization of the system benefit and unavailability. Coloured Petri Nets are adopted to model the maintenance and operation of the railway track section. The Coloured Petri Net model describes the gradual track deterioration as a stochastic process. Different speed restriction policies and maintenance delay strategies are modelled and activated by the observed component states. Monte Carlo simulations are carried out to estimate the maintenance cost, the system benefit and the system downtime under different policies. Numerical results show the maintenance decision variable trade-off.

Monte Carlo simulation of railway track geometry deterioration and restoration

2011 ◽  
Vol 226 (3) ◽  
pp. 274-282 ◽  
Author(s):  
L M Quiroga ◽  
E Schnieder
Keyword(s):  
High Speed ◽  
Railway Track ◽  
Ageing Process ◽  
Previous Knowledge ◽  
Planning And Scheduling ◽  
Track Geometry ◽  
Marquardt Algorithm ◽  
Non Linear ◽  
Maintenance Activities ◽  
Parameter Values

Travelling safely and comfortably on high-speed railway lines requires excellent conditions of the whole railway infrastructure in general and of the railway track geometry in particular. The maintenance process required to achieve such excellent conditions is complex and expensive, demanding a large amount of both human and technical resources. In this framework, choosing the right maintenance strategy becomes a critical issue. A reliable simulation of the railway geometry ageing process would offer a great advantage for the optimization of planning and scheduling of maintenance activities. A fundamental requirement for such simulation is a statistical model describing the behaviour of the railway track geometry deterioration as well as the effects of maintenance activities. The French railway operator SNCF has been periodically measuring the geometrical characteristics of its high-speed network since its commissioning (i.e. for more than 20 years now). These records are an excellent data source to achieve a sound statistical description of the process. In this paper a new system identification method to obtain such simulations is presented. The proposed method uses a grey-box model: a model structure and its constraints are specified basing on previous knowledge of the process to be identified, and then the set of parameter values which best fits the signal measurements is searched. As previous knowledge indicates that the process is non-linear, parameter values are searched by means of the Levenberg–Marquardt algorithm, an iterative technique that finds a local minimum of a function that is expressed as the sum of squares of non-linear functions. Furthermore, the presented model is extended in order to analyse the effect of the variation of factors influencing the ageing process (e.g. operational speed). Finally, the method is applied and validated with real data of a French high-speed TGV line.

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.

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 The impact of summer heatwaves on railway track geometry maintenance

2021 ◽  
pp. 095440972098429
Author(s):  
Ben Davies ◽  
John Andrews
Keyword(s):  
Asset Management ◽  
Response Times ◽  
Railway Track ◽  
Management Support ◽  
Maintenance Policy ◽  
Management Tools ◽  
Support Tool ◽  
Track Geometry ◽  
Maintenance Activities ◽  
The Impact

Elevated summer temperatures are a disrupting factor on the rail network. Due to the risk of a track buckling under thermal expansion forces, geometry maintenance must be delayed during heatwaves, leading to an overall decreased network availability and reliability. Track asset management support tools are used to plan and schedule a variety of maintenance activities, with tamping and stoneblowing being the primary activities for geometry maintenance. No management tools seen in the literature consider the influences of weather on the scheduling and delivery of maintenance. This paper describes a Petri net modelling approach to railway track asset management. This is demonstrated to be a highly flexible method able to capture the complexities of degradation, inspection, and maintenance, and predict the evolution of track geometry quality over time. Different maintenance strategies are tested, varying the degradation thresholds, inspection intervals, policy decisions, and maintenance response times. Excessively hot weather is introduced as an inhibiting factor for all maintenance activities, resulting in extended periods where interventions are delayed. Simulation results show that frequent inspection and timely maintenance scheduling strategies could be followed to attain a highly performing and resilient track system. This asset management support tool could be added to the suite used by the rail industry, providing guidance on maintenance policy through a summer season where heatwave disruptions are expected.

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.

Bottleneck-based opportunistic maintenance model for series production systems

2015 ◽  
Vol 21 (1) ◽  
pp. 70-88 ◽  
Author(s):  
Binghai Zhou ◽  
Jiadi Yu ◽  
Jianyi Shao ◽  
Damien Trentesaux
Keyword(s):  
Production System ◽  
Production Systems ◽  
System Capacity ◽  
System Throughput ◽  
Maintenance Cost ◽  
Series Production ◽  
Opportunistic Maintenance ◽  
Content Type ◽  
Maintenance Activities ◽  
Bottleneck Machine

Purpose – The purpose of this paper is to develop a bottleneck-based opportunistic maintenance (OM) model for the series production systems with the integration of the imperfect effect into maintenance activities. Design/methodology/approach – On the analysis of availability and maintenance cost, preventive maintenance (PM) models subjected to imperfect maintenance for different equipment types are built. And then, a cost-saving function of OM is established to find out an optimal OM strategy, depending on whether the front-bottleneck machines adopt OM strategy or not. A numerical example is given to show how the proposed bottleneck-based OM model proceeded. Findings – The simulation results indicate that the proposed model is better than the methods to maintain the machines separately and the policy to maintain all machines when bottleneck machine reaches its reliability threshold. Furthermore, the relationship between OM strategy and corresponding parameters is identified through sensitivity analysis. Practical implications – In practical situations, the bottleneck machine always determines the throughput of the whole series production system. Whenever a PM activity is carried out on the bottleneck machine, there will be an opportunity to maintenance other machines. Under such circumstances, findings of this paper can be utilized for the determination of optimal OM policy with the objective of minimizing total maintenance cost of the system. Originality/value – This paper presents a bottleneck-based OM optimization model with the integration of the imperfect effect as a new method to schedule maintenance activities for a series production system with buffers. Furthermore, to the best of the knowledge, this paper presents the first attempt to considering the bottleneck constraint on system capacity and diverse types of machines as a means to minimize the maintenance cost and ensure the system throughput.

scholarly journals Maintenance Optimization for Repairable Deteriorating Systems under Imperfect Preventive Maintenance

Mathematics ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 716
Author(s):  
Juhyun Lee ◽  
Byunghoon Kim ◽  
Suneung Ahn
Keyword(s):  
System Reliability ◽  
Preventive Maintenance ◽  
Cost Effective ◽  
Optimal Number ◽  
Sensitivity Analyses ◽  
Maintenance Cost ◽  
Maintenance Optimization ◽  
Maintenance Strategies ◽  
Cost Rate ◽  
Maintenance Activities

This study deals with the preventive maintenance optimization problem based on a reliability threshold. The conditional reliability threshold is used instead of the system reliability threshold. Then, the difference between the two thresholds is discussed. The hybrid failure rate model is employed to represent the effect of imperfect preventive maintenance activities. Two maintenance strategies are proposed under two types of reliability constraints. These constraints are set to consider the cost-effective maintenance strategy and to evaluate the balancing point between the expected total maintenance cost rate and the system reliability. The objective of the proposed maintenance strategies is to determine the optimal conditional reliability threshold together with the optimal number of preventive maintenance activities that minimize the expected total maintenance cost per unit time. The optimality conditions of the proposed maintenance strategies are also investigated and shown via four propositions. A numerical example is provided to illustrate the proposed preventive maintenance strategies. Some sensitivity analyses are also conducted to investigate how the parameters of the proposed model affect the optimality of preventive maintenance strategies.

scholarly journals An efficient physical-based method for predicting the long-term evolution of vertical railway track geometries

2021 ◽  
pp. 095440972110248
Author(s):  
Nishant Kumar ◽  
Claudia Kossmann ◽  
Stephan Scheriau ◽  
Klaus Six
Keyword(s):  
Long Term Evolution ◽  
Contact Forces ◽  
Railway Track ◽  
Model Parameters ◽  
Relative Height ◽  
Vehicle Model ◽  
Track Geometry ◽  
Term Evolution ◽  
Maintenance Activities

The dynamic wheel-rail contact forces resulting from the interaction between vehicle and track are responsible for the local track settlement. If these local settlements vary along the track, geometric irregularities develop further amplifying the dynamic loading of the track caused by the interaction between the vehicle and track. In this work, an efficient vehicle-track interaction (VTI) model is presented for predicting the long-term evolution of vertical track settlement during operation. The VTI model has two interacting components – vehicle and track. The vehicle model describes the vertical dynamics of an 8th of a car. The track model considers an elastic rail on discrete (sleeper) supports. Each sleeper location can have its own stiffness, relative height and settlement characteristics. Dependent on the distribution of stiffness and settlement behaviour along the track together with the initial track geometry, each sleeper settles dependent on the number of load cycles (vehicle passes). The track model is initialized with measured vertical track geometry data and static track deflection data at the beginning (day 0) for two types of track sections in the field, a track section where concrete sleepers with Under Sleeper Pads (USP) are used and a track section where only concrete sleepers are used. Using the same settlement model parameters (constant along the track) for the two tracks, the physical-based VTI model can predict the different track geometry quality evolution for both tracks over 350 days. Finally, the VTI model is used to assess the track geometry deterioration when the track/vehicle properties are changed. The prediction strength of the fast VTI model based on the physical understanding can assist in designing and optimizing tracks and in supporting of maintenance activities.

scholarly journals Micro-mechanical investigation of railway ballast behavior under cyclic loading in a box test using DEM: effects of elastic layers and ballast types

2019 ◽  
Vol 21 (4) ◽  
Author(s):  
Nishant Kumar ◽  
Bettina Suhr ◽  
Stefan Marschnig ◽  
Peter Dietmaier ◽  
Christof Marte ◽  
...  
Keyword(s):  
Cyclic Loading ◽  
Early Stage ◽  
Damage Model ◽  
Simulation Models ◽  
Railway Track ◽  
Maintenance Cost ◽  
Particle Movement ◽  
Railway Ballast ◽  
Elastic Layers ◽  
The Impact

Abstract Ballasted tracks are the commonly used railway track systems with constant demands for reducing maintenance cost and improved performance. Elastic layers are increasingly used for improving ballasted tracks. In order to better understand the effects of elastic layers, physical understanding at the ballast particle level is crucial. Here, discrete element method (DEM) is used to investigate the effects of elastic layers – under sleeper pad ($$\text {USP}$$USP) at the sleeper/ballast interface and under ballast mat ($$\text {UBM}$$UBM) at the ballast/bottom interface – on micro-mechanical behavior of railway ballast. In the DEM model, the Conical Damage Model (CDM) is used for contact modelling. This model was calibrated in Suhr et al. (Granul Matter 20(4):70, 2018) for the simulation of two different types of ballast. The CDM model accounts for particle edge breakage, which is an important phenomenon especially at the early stage of a tamping cycle, and thus essential, when investigating the impact of elastic layers in the ballast bed. DEM results confirm that during cyclic loading, $$\text {USP}$$USP reduces the edge breakage at the sleeper/ballast interface. On the other hand, $$\text {UBM}$$UBM shows higher particle movement throughout the ballast bed. Both the edge breakage and particle movement in the ballast bed are found to influence the sleeper settlement. Micro-mechanical investigations show that the force chain in deeper regions of the ballast bed is less affected by $$\text {USP}$$USP for the two types of ballast. Conversely, dense lateral forces near to the box bottom were seen with $$\text {UBM}$$UBM. The findings are in good (qualitative) agreement with the experimental observations. Thus, DEM simulations can aid to better understand the micro-macro phenomena for railway ballast. This can help to improve the track components and track design based on simulation models taking into account the physical behavior of ballast. Graphical Abstract

scholarly journals Optimal Preventive Maintenance of Wind Turbine Components with Imperfect Continuous Condition Monitoring

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3801 ◽  
Author(s):  
Ahmed Raza ◽  
Vladimir Ulansky
Keyword(s):  
Wind Turbine ◽  
Condition Monitoring ◽  
Preventive Maintenance ◽  
False Negative ◽  
Maintenance Cost ◽  
Arbitrary Distribution ◽  
Average Lifetime ◽  
True Negative ◽  
Degradation Failure ◽  
Lifetime Maintenance

Among the different maintenance techniques applied to wind turbine (WT) components, online condition monitoring is probably the most promising technique. The maintenance models based on online condition monitoring have been examined in many studies. However, no study has considered preventive maintenance models with incorporated probabilities of correct and incorrect decisions made during continuous condition monitoring. This article presents a mathematical model of preventive maintenance, with imperfect continuous condition monitoring of the WT components. For the first time, the article introduces generalized expressions for calculating the interval probabilities of false positive, true positive, false negative, and true negative when continuously monitoring the condition of a WT component. Mathematical equations that allow for calculating the expected cost of maintenance per unit of time and the average lifetime maintenance cost are derived for an arbitrary distribution of time to degradation failure. A numerical example of WT blades maintenance illustrates that preventive maintenance with online condition monitoring reduces the average lifetime maintenance cost by 11.8 times, as compared to corrective maintenance, and by at least 4.2 and 2.6 times, compared with predetermined preventive maintenance for low and high crack initiation rates, respectively.

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