Maintenance can represent a significant portion of the cost in asset intensive organisations, as breakdowns have an impact on the capacity, quality and cost of operation. However, the formulation of a maintenance strategy depends on a number of factors, including the cost of down time, reliability characteristics and redundancy of assets. Consequently, the balance between preventive maintenance (PM) and corrective maintenance (CM) for minimising costs varies between organisations and assets. Nevertheless, there are some rules of thumb on the balance between PM and CM, such as the 80/20 rule. Studies on the relationship between PM and CM in practice are rare. Therefore, PM and CM costs are studied in this article by analysing historical maintenance data. A case study of rail infrastructure historical data is carried out to determine the shares of PM and CM, together with a cost–benefit analysis (CBA) to assess the value of PM. The results show that the PM represents 10% to 30% of the total maintenance cost when user costs, i.e. train delays, are included as a CM cost. The CBA shows the benefit of PM is positive with a benefit–cost ratio at 3.3. However, the results depend on the inclusion/exclusion of user costs, besides individual organisational parameters.

Railway transport infrastructure is a linearly distributed asset that requires an effective performance management system to meet sectional and overall business objectives. In particular, an effective performance measurement system with relevant analysis technique in an ongoing manner is necessary to facilitate continuous improvement. Maintenance performance measurement (MPM) is essential to quantify the impact of past maintenance decisions and actions and also to support new decisions. This article presents the challenges of implementing and using MPM systems for maintenance decisions in the railway industry. Thereafter, a risk matrix with maintenance performance indicators is introduced as a complementary analysis tool to identify weak links on a railway line. A case study of a section on the heavy haul line of the Swedish Transport Administration railway network is presented to demonstrate the application of the risk matrix tool for continuous improvement. The results identified the bottlenecks on the line section, which are improvement opportunities for maintenance performance in terms of service quality and capacity target of the infrastructure manager

Railways are large, geographically dispersed assets, consisting of numerous systems, subsystems and components, for which considerable amounts of data and numerous indicators are generated for monitoring their operation and maintenance. Proper assessment of operation and maintenance performance is essential for sustainable and competitive rail transportation. Composite indicators (CIs), or indices, can simplify the performance measurement by summarising the overall performance of a complex asset into a single figure, making it easier to interpret than multiple indicators and plots. In this article, a CI termed ‘rail infrastructure integrity index’ is developed and verified in a case study. The results show that CIs can be used for benchmarking and assessing the overall performance of railway sections in a single figure, indicating which sections need further study. Their implementation should allow data users to do sensitivity analysis and decomposition for traceability.Keywords: rail infrastructure; composite indicator; integrity index; dependability; RAMS; benchmarking

Railway transport system is massive and complex, and as such it requires effective maintenance to achieve the business goal of safe, economic and sustainable transportation of passengers and goods. The growing demand for improved service quality and capacity target by railway infrastructure managers requires appropriate maintenance analysis to facilitate continuous improvement of infrastructure performance. This paper presents the application of risk matrix as a maintenance analysis method for the identification of track zones that are bottlenecks that limit operational capacity and quality. Furthermore, an adapted analysis method is proposed to create a hierarchical improvement list for addressing the problem of train mission interruption and reduced operational capacity. A case study of a line section of the Swedish network is presented. The result classifies the zones on the line section into different risk categories based on their contribution to loss of capacity and punctuality. In addition, an improvement list for the lower-level system is presented to facilitate maintenance decisions and continuous improvement at both operational and strategic levels.

Enterprise resource planning systems and maintenance management systems are commonly used by organisations for handling of maintenance records, through a graphical user interface. A maintenance record consists of a number of data fields, such as drop-down lists, list boxes, check boxes and text entry fields. In contrast to the other data fields, the operator has the freedom to type in any text in the text entry fields, to complement and make the maintenance record as complete as possible. Accordingly, the text entry fields of maintenance records can contain any words, in any number.Data quality is crucial in statistical analysis of maintenance records, and therefore manual analysis of maintenance records’ text entry fields is often necessary before any decision making. However, this may be a very tedious and resource consuming process.In this article, natural language processing is applied to text entry fields of maintenance records in a case study, to show how it can bring further value in the assessment of technical assets’ performance.Keywords: Maintenance records, Natural language processing, Structured and unstructured data, Data quality, Rail infrastructure.

Purpose:The purpose of this paper is to provide a literature review of the performance measurement in maintenance. The authors aim to discuss the background and development of the performance measurement for maintenance, besides defining the concept of performance measures for maintenance and the frameworks developed.Design/methodology/approach:A detailed and extensive literature search and study was undertaken by the authors on the concept and definition of performance measurement, performance indicators, maintenance performance indicators and various performance frameworks. The history and theory of performance measurement over different phases of business and technological developments have been critically examined and analysed in this review paper. Findings:This paper reviews and presents the different performance indicators (PIs) and performance measurement (PM) frameworks like; balanced scorecard, performance prism, performance pyramid and performance matrix etc, and identifies their characteristics and shortcomings. After considering related issues and challenges, frameworks and approaches for the maintenance performance measurement (MPM) are also presented, where the emerging techniques like; e-maintenance have also been discussed amongst others. More and more industries are applying the balanced and integrated MPM frameworks for their competitive survivability and sustainability.Practical implications:The concept, issues and approaches considered for the MPM frameworks can be adapted by the practicing managers, while trying to define and develop an MPM framework for the operation and maintenance activities. The considerations of the advantages and limitations of different frameworks can provide insights to the managers for implementation. Originality/value:Some literature reviews on MPM and MPM frameworks are available today. This paper makes an attempt to provide a detailed and relevant literature review, besides adding value in this new and emerging area.

Radio Frequency Identification (RFID) helps automatic identification of objects using radio waves. This is not a new technology instead decades old and has been used during the World War II, when it was used by allied ground forces to track German bombers. It is a technology for wireless communication between a reader and a transponder/tag. This technology permits the transfer of data to the most diverse objects without the need for physical contact and uses intelligent barcodes to track items and have been successfully applied in military, security, healthcare, real time location tracking, vehicle identification and other areas. This paper is based on applications of radio frequency identification technology with eMaintenance cloud for railway system to analyze and visualize data of trains for the cost effective maintenance planning. Further, cloud computing is an emerging research area that can be utilised for acquiring an effective and efficient information logistics. Specifically, the widespread use of RFID will enable wagons to be tracked leading to better resource utilization, lower freight costs, and better maintenance. Therefore, it helps to provide greater control of the train carriages, making it easier to plan resources. However, RFID is a powerful tool that can help to improve industry proficiency, implementing this technology is not easy. Furthermore, operating RFID systems can be a challenging process. Thus, this paper is based on the application of RFID in the context of railway operation.

Increased environmental awareness in the industry combined with the globalized market economy makes increasing demands for sustainable and efficient resource utilization. In this context, maintenance plays a critical role by linking business objectives to the strategic and operational activities aimed at retaining the system’s availability performance, cost-efficiency and sustainability. Performing maintenance effectively and efficiently requires corresponding infrastructure for decision-support provided through eMaintenance solutions. A proper eMaintenance solution needs to provide services for data acquisition, data processing, data aggregation, data analysis, data visualization, context-sensing etc. To en Quality of Service (QoS) in eMaintenance solutions, the performance of both system-of-interest, enabling systems and related processes have to be measured and managed. However, the QoS has to be considered on all aggregation levels and encompass the aspects of Content Quality (CQ), Data Quality (DQ) and Information Quality (IQ). Hence, the purpose of this paper is to study and describe some aspects of DQ in eMaintenance related to process industry in northern Europe

Rail traffic has increased manifold during the last decade. This development and the need for shift transportation from road to rail to decrease CO2 emission, creates a challenge for the railway industry to improve capacity in the network. The challenge is to do more effective inspection and maintenance in less time. An EU project ‘AUTOMAIN’ was initiated to optimize and automate maintenance and inspection activities with introduction of new planning and scheduling tools and methodologies. The project looked into reducing the maintenance possession time by around 40%. The project aim was to; adopt best practices from other industries in maintenance optimization, developing novel track inspection approaches for freight routes. The scope was for in-train measuring and self-inspecting switch, researching and assessing innovations that can improve the effectiveness and efficiency of large scale inspection and maintenance processes with a scope on track and switch maintenance, track inspection; developing key technologies that will drive the development of modular infrastructure design, and developing a new maintenance planning and scheduling tool to optimize the maintenance activities, taking account of the benefits brought about by other improvements in this project.The Consortium composition covers the railway maintenance and inspection field like; infrastructure managers, contractors, train operating companies, railway component industry, research organizations, small and medium enterprises (SMEs) and railway industry related organizations. In this paper, the authors have tried to summarize the methodology and results achieved in this project and how it has achieved the reduced maintenance possession time for higher railway traffic movements.

Achieving business excellence within industries which utilise complex technical systems requires effective and efficient maintenance. Maintenance is an important enabler of business performance. An effective maintenance strategy creates additional values in an organisation’s value-generating process. Establishing an effective and efficient maintenance process is highly dependent on supporting Information and Communication Technology (ICT) infrastructure for information logistics that facilitates maintenance decision support. eMaintenance solutions facilitates effective and efficient management and control of maintenance activities through an enhanced utilisation of computing; like;.estimation of their Remaining Useful Life (RUL); reduction of No-Fault Found (NFF); and prediction of fault. eMaintenance solutions enable a seamless integration and fusion of information services provided by information intensive systems with embedded components in order to manage increasing and extentensively distributed real‐time data collected via different data sources (e. g. sensors). Since, the emerging ‘Internet of Things’ is expecting to dramatically change information systems with inherent embedded components, eMaintenance solutions need to be adapted to this new context to fulfil the overall business requirements on an effective and efficient decision-making process; for e.g.: real‐time analysis based on real‐time data and context-aware information logistics. However, development and establishment of proper eMaintenance solutions can be facilitated through utilisation of appropriate framework which deals with real-world challenges. This paper explores some of the issues and challenges pertaining to eMaintenance industrial application.