A holistic approach to railway infrastructure asset management

In the railway industry asset management decisions are focused on the maintenance, enhancement and renewal of assets in order to ensure a required level of dependability and improvement in services at the lowest whole life costs. To achieve these objectives system lifecycle models, rather than individual asset models,= offer a greater advantage. The paper presents a modelling approach developed for constructing multi asset system models to support well-informed railway infrastructure asset management decisions. The models are built using the Petri Net formalism and are analysed by a means of Monte Carlo simulations. A specific example of the railway superstructure model is presented. Its simulation results demonstrate the superiority of the system-wide model against individual asset models in terms of its accuracy in predicting the superstructure (system) performance and information available to support asset management decisions. Furthermore, by using the multi-asset system model interdependencies among maintenance regimes of different assets and different parts of the infrastructure can be modelled

System-wide assessment of intervention strategies for railway infrastructure

The existing railway infrastructure exhibits faster degradation rates and requires more maintenance effort as a result of increased utilisation. At the same time, due to increased numbers of freight and commuter trains obtaining access to the railway infrastructure to carry out maintenance and repairs, not to mention major enhancements, is becoming more problematic. Furthermore, safety measures put in place in the event of infrastructure faults or delayed completion of intervention activities will cause greater disruptions to train services in the parts of the network with intense train traffic. Taking a system wide view is, therefore, vital for developing efficient intervention strategies that could deliver the desired infrastructure outputs. In this paper we propose a modelling approach for simulation and analysis of railway track asset management strategies integrating different elements of the whole railway system. The approach uses a Petri net modelling technique to construct the railway system model. The model is built in a hierarchical, modular fashion, meaning that the system can be represented at any level of granularity and complexity, ranging from a single-asset system in a small segment of the network to a complex multi-asset system in a large geographical region. The impact of different asset management strategies on the infrastructure functionality and the operation of train services is assessed using the Monte Carlo simulation technique

Fault detection and diagnostics of a three-phase separator

A high demand of oil products on daily basis requires oil processing plants to work with maximum efficiency. Oil, water and gas separation in a three-phase separator is one of the first operations that are performed after crude oil is extracted from an oil well. Failure of the components of the separator introduces the potential hazard of flammable materials being released into the environment. This can escalate to a fire or explosion. Such failures can also cause downtime for the oil processing plant since the separation process is essential to oil production. Fault detection and diagnostics techniques used in the oil and gas industry are typically threshold based alarm techniques. Observing the sensor readings solely allows only a late detection of faults on the separator which is a big deficiency of such a technique, since it causes the oil and gas processing plants to shut down. A fault detection and diagnostics methodology for three-phase separators based on Bayesian Belief Networks (BBN) is presented in this paper. The BBN models the propagation of oil, water and gas through the different sections of the separator and the interactions between component failure modes and process variables, such as level or flow monitored by sensors installed on the separator. The paper will report on the results of the study, when the BBNs are used to detect single and multiple failures, using sensor readings from a simulation model. The results indicated that the fault detection and diagnostics model was able to detect inconsistencies in sensor readings and link them to corresponding failure modes when single or multiple failures were present in the separator

Bayesian belief networks for fault detection and diagnostics of a three-phase separator

A three-phase separator (TPS) is one of the key components of offshore oil processing facili-ties. Oil is separated from gas, water and solid impurities by the TPS before it can be further processed. Fail-ures of the TPS can lead to unplanned shutdowns and reduction of the efficiency of the whole oil processing facility as well as posing hazards to safety of personnel. A novel fault detection and diagnostic (FDD) meth-odology for the TPS is proposed in this paper. The core of the methodology is based on Bayesian Belief Net-works (BBN). A BBN model is built to replicate the operation of the TPS: when the system is fault free or operating with single or multiple failed components. Results of the capabilities of the BBN model to detect and diagnose single and multiple faults of the TPS components are reported in this paper

Railway bridge asset management using a Petri-Net modelling approach

Infrastructure assets can be difficult to manage due to the array of defects, the variety of environmental situations and the different operational scenarios. A number of studies have tried to model bridge asset management. The main focus of these models has been on the deterioration profiling as capturing this can be complex. The model presented tries to model railway bridge detrioration as well as the inspection and intervention processes to give a more rounded overview of railway bridge asset management. A Petri-Net (PN) modelling approach is used accompanied by historical data, used to calibrate the deterioration of the model. Industry policies are used to govern the inspection and intervention procedures. Various aspects of the model have been adjusted or enhanced by industry experts. The model is simulated to provide essential outputs for railway bridge portfolio mangers

Equalities analysis of post-pandemic results in general and vocational and technical qualifications

Objectives We exploited linked administrative data to study attainment gaps in GCSEs, A level, and vocational and technical qualifications. Our aim was to compare how grades for groups of students with different protected characteristics and socio-economic status have changed in 2022 compared to previous years. Methods We used a multilevel regression modelling to evaluate the impact of each demographic and socio-economic characteristic on students’ results, once other factors are controlled for. The purpose was to examine how the relationship between students’ attainment and their characteristics has changed between 2018 and 2022. The characteristics analysed were: • ethnicity • gender • special educational needs and disabilities status free school meal eligibility • Income Deprivation Affecting Children Index score • prior attainment • first language • region • centre type We collected results and prior attainment data from awarding organisations and linked it with data from the Individual Learner Record and the National Pupil Database. Results Of the many different comparisons between groups of students, the majority showed no notable change in attainment gaps in 2022, compared with both pandemic and pre-pandemic years. Some degree of minor fluctuation is always to be expected. Attainment gaps and changes over time differ across qualifications. At A level, the analysis highlighted some key changes in results in relation to gender (the difference between boys and girls reversed during the pandemic), ethnicity and school and/or college type. At GCSE, the analysis showed notable changes for ethnicity, with Gypsy and Roma students narrowing the gap compared to White British students, school and/or college type and socio-economic background. For vocational and technical qualifications, we found fewer notable changes than for GCSEs and A levels. Conclusion The use of linked administrative data helped to gain better insights in attainment gap changes over time. Many gaps remained the same, some gaps widened, and others narrowed. The findings make it difficult to draw firm conclusions about the cause of these differences, many of which existed before the pandemic