Kualitas Indeks Track Geometri Sebagai Indikator Penilaian Kualitas Track Melalui Metode Yang Berbeda (Studi Kasus: Cirebon-Cikampek)

Untuk mengatasi pergerakan pertumbuhan lalu lintas jaringan kereta api di Indonesia, khususnya di Jalur Cirebon-Cikampek dimana rute tersebut merupakan rute tersibuk di utara Pulau Jawa, hal itu dapat mempengaruhi kondisi geometri lintasan. Beberapa parameter geometri yang berpengaruh diantaranya adalah angkatan, listringan, lebar spur, dan pertinggian. Perlu adamya suatu pemeliharaan untuk mengukur suatu kondisi dan kualitas lintasan dengan menggunakan kereta ukur EM-120. Dibutuhkan pemeliharaan untuk mengukur kondisi dan kualitas lintasan menggunakan kereta ukur EM-120. Hasil kereta ukur menunjukkan nilai standar deviasi dari setiap parameter sehingga hasil kualitas segmen secara keseluruhan disebut Indeks Kualitas Track (TQI). Penelitian ini dilakukan untuk menganalisis Indeks Kualitas Track berdasarkan Standar Kereta Api Indonesia, Polandia Koefisien J-Sintetis dan Perkeretaapian India. Untuk mengetahui perbedaan hasil analisa indeks kualitas lintasan, digunakan metode tabulasi silang dan regresi linier berganda. Hasil yang didapatkan dari tabulasi silang yaitu selisih perbedaan pengukuran secara statistik sedangkan regresi linier berganda untuk mengetahui seberapa besar parameter yang mempengaruhi nilai kualitas lintasan

A Novel Short-Range Prediction Model for Railway Track Irregularity

In recent years, with axle loads, train loads, transport volume, and travel speed constantly increasing and railway network steadily lengthening, shortcomings of current maintenance strategies are getting to be noticed from an economical and safety perspective. To overcome the shortcomings, permanent-of-way departments throughout the world have given a considerable attention to an ideal maintenance strategy which is to carry out appropriate maintenances just in time on track locations really requiring maintenance. This strategy is simplified as the condition-based maintenance (CBM) which has attracted attentions of engineers of many industries in the recent 70 years. To implement CBM for track irregularity, there are many issues which need to be addressed. One of them focuses on predicting track irregularity of each day in a future short period. In this paper, based on track irregularity evolution characteristics, a Short-Range Prediction Model was developed to this aim and is abbreviated to TI-SRPM. Performance analysis results for TI-SRPM illustrate that track irregularity amplitude predictions on sampling points by TI-SRPM are very close to their measurements by Track Geometry Car

Discrete Event Simulation and Optimization Approaches for the Predictive Maintenance of Railway Infrastructure

This thesis is carried out within the PhD Course in Logistics and Transport at CIELI - Italian Centre of Excellence on Logistics, Transport and Infrastructures, University of Genoa. In this work, a discrete event simulation and optimization model is created to schedule the predictive maintenance activities. Nowadays, after a severe decrease of transport demand during the pandemic period, rail public transport is resuming a central role for both freight and passenger transport. To cope with this increase in demand, to maintain high safety standards and to avoid unnecessary costs, the idea is to switch to predictive maintenance strategy, intervening before an asset failure and when it has reached a certain state of degradation. The degradation and asset future conditions are predicted according to probabilistic models and maintenance deadlines are defined by applying a risk based approach. The problem is first formulated as a MILP (Mixed Integer Linear Programming) optimization problem and then transformed into a simulation-based optimization problem using the ExtendSim software. Different simulative models are created to take into account the stochastic nature of some variables in real processes. After the formal description of the models, some real-world applications are presented. Finally, considerations on the proposed approach are reported highlighting limits and challenges in predictive maintenance planning, such as lack of data and the stochastic and complex environment

Risk-Based Optimal Scheduling for the Predictive Maintenance of Railway Infrastructure

In this thesis a risk-based decision support system to schedule the predictive maintenance activities, is proposed. The model deals with the maintenance planning of a railway infrastructure in which the due-dates are defined via failure risk analysis.The novelty of the approach consists of the risk concept introduction in railway maintenance scheduling, according to ISO 55000 guidelines, thus implying that the maintenance priorities are based on asset criticality, determined taking into account the relevant failure probability, related to asset degradation conditions, and the consequent damages