eMaintenance solutions are extensively used by the industry today. eMaintenance is an emerging technology aimed to support the industry to achieve effectiveness and efficiency in their maintenance process through enhanced use of Information and Communication Technology (ICT) . One of the essential components is an eMaintenance solution is data acquisition. Supervisory Control and Data Acquisition (SCADA) has been used to manage data acquisition is many industrial systems. Nowadays, modern SCADA systems are available through internet and other networks via IP protocol. An increased use of internet–based solution requires appropriate management approaches to improve the safety and security aspects of a system. Hence, this paper suggests a new security model based security for SCADA systems through Cloud computing and Artificial Immune System (AIS). Furthermore, the paper provides AIS, which is based on Decision Tree (C4.5 algorithm) using clustered feature set. The features set are selected from NSL-KDD cup. It is a new version of KDD dataset. As a result, two Antibodies are generated (that could recognize Normal and Antigen). After applying the resulted antibodies on the testing data set, the outputs are Normal, Antigen, and Unknown. Finally it is treated with Unknown as Antigen. As a result, high accuracy of the suggested model reaches 96.3%.

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.

Infrared thermography has been investigated as a non destructive testing method for health monitoring of rotating mining mills. The idea is to monitor the thermal differences on the mill surface with thermal camera in order to detect and maintain cracks and other material damage in the mill material. A general description of the thermography technique, the theory behind, advantages and drawbacks as well as its use in other applications is presented. To test the usefulness of the method, real life measurements with IR-camera have been performed on several mining mills at a mining company located in northern Sweden. The results from these measurements are presented and discussed in this article. Infrared thermography is a fast and relatively cheap inspection method which can find and monitor material damage in rotating mining mills and help the maintenance personal in taking the corrective maintenance decisions.

The present day e-maintenance space is evolving with isolated legacy sub-systems or packages that span heterogeneous and domain specific industry verticals. Developing a unified platform for e-maintenance catering to the varied domains shall hence pose a major challenge. An open systems based platform for emaintenance can overcome some of these hurdles by defining the otherwise disparate systems as abstract entities with well defined public interfaces. The interfaces can be broadly classified based on the technology types, thus allowing individual vertical emaintenance applications to align with their respective business interests. In all, this shall greatly help in reducing the overall operating costs and at the same time provide increased flexibility, reusability and reliability. The underlying standard protocol, defined through a group consensus, shall be responsible for transport of the e-maintenance data between the distributed subsystems via the TCP/IP standard within multiple administrative domains of e-maintenance across wired and wireless networks. This paper also looks at e-maintenance from a systems integration perspective and illustrates how open systems based approach can help achieve integration better.

Maintenance and support providers to modern aircraft need to manage an increasing amount of information generated by growing system complexity and stakeholder requirements. This introduces new risks in the information management process and makes traditional information services and systems inadequate. However, recent advancements in information and communication technology (ICT) have contributed to the emerging approach of e-Maintenance, which forms an important building block to achieve the desired information logistics. e-Maintenance enables remote and real time maintenance, and includes; collection, monitoring, analysis and distribution of data and information as decision-support to stakeholders of the maintenance and support processes, independent of organization or geographical location, 24 hours a day and 7 days a week (24/7). This paper describes a proposed development of information products by linking theories to practical methodologies and tools (e.g., Quality Function Deployment, QFD) through the development of a demonstrator of a stakeholder-based information product in the context of a modern combat aircraft. Read more about November 2011 P8 - Development of Information System for e-Maintenance Solutions within the Aerospace Industry by www.ijpe-online.com

Work integrated blended learning for asst managers is targeted to the senior engineers and managers. Main purpose of this blended learning is to enhance asset management skills in establishing and managing capital intensive assets and infrastructures. A course in asset management systems in line with PAS55 was developed to reflect the best known practices in asset management, to cover some long-term but little understood issues, and to deliver it in such a way that it was highly effective from the point of view of industries, participants and the delivery team. It includes establishing asset management systems and standards, and taking effective decisions considering asset maintenance costs, risks and performance. This paper is to outline the needs of target audience and provide overview of the work integrated blended course for asset management system for improving decision making by asset managers

The paper proposes a framework for analysing the performances of product-service systems (PSSs) development processes using a balanced scorecard (BSC) as an instrument to guide the implementation and the evaluation of new methods and tools. Emerging from a case study in the aerospace industry, the paper discusses the main challenges in PSS development and proposes a performance measurement framework for PSS development based on multi-criteria indicators. Finally, the benefits of a framework for PSS development performance measurement are discussed.

To be competitive with other modes of transport, the railway needs to be cost-effective. In order to become more competitive in the logistics industry, Indian Railways has taken new initiative to improve their operations in recent years. A rail-truck intermodal transportation service for Indian Railways is described in this paper. The main focus of the present research is to optimize the freight rate and terminal location together, in order to minimize the total shipping cost of truckers while ensuring the targeted profit of the railway. A model has been developed for the determination of the optimal freight rate and the corresponding intermodal terminal location. The key regulators of this model are the price sensitivity of the trucker and profit guarantee for railways. A case study was developed on the Delhi - Mumbai freight corridor. An analysis was performed to gain insight into the trade-offs among shipment cost and terminal locations.

Inspection of the liner wear in the mill of an ore dressing plant is one of the critical parameters in the context of mill downtime and production performance. The total downtime cost during measurement can be reduced by a significant fraction by using appropriate measurement devices. Due to the different quality dimensions of a measuring device, e.g. the cost, accuracy, reliability and accessibility, it is necessary to select an appropriate device based on the specific needs of the industry. Customer satisfaction is perhaps the most important performance measure for the service quality of the device, and therefore this paper provides an approach to define the customer satisfaction with reference to the mentioned quality dimensions. The main aim of this paper is to determine a unified measure or quality index for the service quality of the measurement device across all the dimensions. Each quality index will then correspond to the total predicted usability of the particular measurement method based on the industry needs. Furthermore, this study also discusses the advantages and disadvantages of existing measurement methods and proposes an indirect measurement method to reduce the downtime during inspection.

Railway transport system is complex and requires effective maintenance to achieve the business goal of safe, economic and sustainable transportation of passengers and goods. The maintenance service either provided by internal or external agents is anticipated to reach specified objectives. The major objective of maintenance is to assure dependable infrastructure with the available resources, to meet operational target and other business objectives of infrastructure manager. This however requires continuous improvement through effective performance measurement and management. This article has identified some salient criteria or perspective of maintenance process that are essential to quantify the impact of past maintenance decisions and actions. The challenges of developing and implementing maintenance performance system in the railway industries are discussed. A synthesised system of maintenance performance measurement is also suggested, this emphasises the important performance aspects. A case study of a line section on the heavy haul line with mixed traffic, belonging to the Swedish railway network is presented as well to demonstrate the analytical perspective of performance indicators. This will enhance the identification of improvement opportunities in railway infrastructure maintenance. Such improvements will support the overall business goal of meeting service quality and capacity target of infrastructure manager.

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.

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

The use of automated systems for monitoring or surveillance of the condition of machinery for an industrial plant is becoming more common. Variables or indicators are transmitted to a database connected "on line" with such systems, allowing us to correctly track the condition parameters included in the PdM (Predictive Maintenance) Program. A practical example of an installation of 500 measuring points in a paper mill is presented in this paper. Paper mill plants show a wide variety of defects and conditions related to problems in rotating machinery bearings, gears, low speed operation, variable speed machine due to harsh conditions in the environment for elements of the installation and other adverse factors. Therefore, the vibration analyses are presented as physical indicators of the technical system for this type of machinery, on which the maintenance performance metrics are built. The article concludes presenting the "state of the art in data transmission to remote facilities engineering, for predictive diagnostic in order to detect potential problems in machinery which facilitate decisionmaking process in maintenance departments. These systems allow the rapid construction of the KPIs at different hierarchical levels. Therefore an approach to decision making based on the Maintenance methodology has been developed as a result of technological advances in the collection of physical data

The measurement of the performance in the maintenance function has produced large sets of indicators that due to their nature and disparity in criteria and objectives have been grouped in different subsets lately, emphasizing the set of financial indicators. The generation of these indicators demands data collection of high reliability that is only made possible through a model of costs adapted to the special casuistry of the maintenance function, characterized by the occultism of these costs.

The system of performance measurement of maintenance function should cover all processes related to it within the organization. There must be an interconnection between the different indicators, so the numbers can be interpreted in order to reach a good conclusion for decision making. This premise implies a hierarchy of indicators needed in a dual way. First, it will require maintenance indicators to be segmented according to the areas of influence for the rest of the organization, posed by interactions with finance department, human resources, purchasing, and, of course, with production in the seeking of compliance with corporate objectives. Simultaneously, these indicators correspond to different levels in the organization and therefore they will be segmented according to the hierarchical position of end users.

The maintenance performance measurement is often faced with a lack in knowledge about the real function of the maintenance department within organizations, and consequently the absence of appropriate targets emanating from the global mission and vision. These facts bring about metrics not adapted to the real needs, which has a strong load of human factor and without a roadmap of the amount of data to be collected, their processing and use in decision making. This article proposes a model where qualitative and quantitative methods are combined in order to complement advantages and disadvantages of them both.

Lean Maintenance (LM) enhances organizational profitability by identifying and eliminating maintenance related wastes. There exists no singular metric that measures maintenance related wastes. The paper identifies the LM features and models them using incidence-matrix. LM features are represented by diagonal elements, while its off-diagonal elements represent mutual influences among the LM features. The maintenance system leanness is quantified using the permanent of the matrix. The metric of leanness is proposed to be defined as Lean maintenance index (LMI) and is a ratio of the actual to the ideal values of permanent of actual and ideal maintenance system matrices. A high value of LMI indicates that the maintenance system is operating in a reduced waste scenario with respect to its resources. Among all the LM features, LMI was found to be most sensitive to management support including organizational processes. The results of the methodology are a good guide for managers. The shortcoming of the methodology is that, it relies on values and weights of the inter-relations among the features, which may not be necessarily true and may need further scientific rigor. The proposed methodology of using LMI as a singular metric to judge maintenance efficacy is expected to aid the operation managers in quantifying the maintenance leanness and may help them focus their efforts appropriately. There is no evidence to indicate existence of comprehensive list of LM features that culminate into a singular metric of maintenance productivity. This paper attempts to fill this gap.

Performance needs to be measured in order to manage the business goals. Performance measurement (PM) has caught the imagination of almost all industries in the last decade. A number of PM frameworks are in use by different industries. Due to global competition and high dynamic market demand, the pressure on the process industries like; the mining industries, is too high. In order to manage and meet the challenging market demands of high productivity, mining industries are trying to apply the concept of PM and performance measures. Before applying performance measures for PM, the production process need to be organized and the management needs to be fully committed for PM implementation. PM measures can be divided into hard and soft measures, which are necessary to monitor, control and measure the productivity. Hard measures like the technical, productivity and financial measures can be well defined and relatively easy to control, where as soft parameters pertaining to human factors like; competence, motivation and organizational climate are critical and hard to measure. In this paper, the authors have discussed the concept of performance measurement and measures for achieving desired productivity. Based on their experience of a related project, the authors have discussed the performance measures for LKAB underground mining industry.

A root cause failure analysis of coal mill vertical shaft used in thermal power plant has been carried out. The failed parts of the shaft showed the signature of fatigue failures. The fatigue cracks originated from the top edge of the keyway area, where the bowl is assembled. Operating conditions, material of the shaft and design of the shaft for strength are the possible causes for the fatigue failure. Due to some constrains the operating conditions cannot be changed. It is found after conducting experiments that the strength of the material used for the shaft is not uniform, however, the material change is beyond the scope of the plant. Therefore, the initial design of the shaft has been analyzed. It is found that the high stress concentration is at the top edge of the keyway, where the fatigue crack originates. The value of stress concentration can be reduced by changing the geometry of the keyway. Therefore, four cases of the change in keyway geometry has been studied using commercial software ANSYS. The result showed in one of the cases that the stress concentration reduces by 36% and it is implementable in plant location. The failure analysis results of coal mill vertical shaft used in thermal power plant as carried out in a case study, will be available to the designer and manufacturer, besides the users and the experts, through the e-Maintenance system.

The business scenario is focusing more on e-business intelligence to perform transaction with customers needs for enhanced value and improvement in asset management. Such prognostic business requirement is compelling the organizations to minimize the production and service downtime by reducing the machine performance degradation. The purpose of this paper is to undertake a mapping of the present status of the maintenance of the Swedish process industry, study their linkage and correlation between the business and maintenance processes, and the supporting Information & Communication Technology (ICT), in order to identify the feasibilities and challenges for implementing eMaintenance system. The focus of the work was to identify how the current maintenance process is defined, organized and performed; and how it is linked and correlated to the business and support processes and besides what is executed within the maintenance process.

The global business scenario under the economic slowdown demands an increased environmental sustainability of asset during its whole life cycle, besides the other requirements like, Life Support Cost (LSC) and availability performance. To fulfill these requirements, a need exist for introducing asset management philosophy with integrated management strategy. Further, an effective asset management is also dependent on other prerequisites such as a proper support infrastructure, which include human resources, support equipment, materials and spare parts, facilities, documentation, information and information systems. Information is essential in order to facilitate asset management and enable the achievement of overall business objectives. Hence, asset related information need to be provided through a proper information logistics.Information logistics aims to provide just-in-time information to the actors of asset management and to optimize the information supply process, i.e. making the right information available at the right time and at the right point of location. In this context the delivery of accurate and timely information to the information consumer and its adaption to the right situation is highly important.Information logistics for an extensive information context related to complex technical systems with capability such as mobility, real-time delivery, context-awareness and situation-awareness requires appropriate methodologies and technologies. These methodologies and technologies are aimed to be utilized to provide an efficient ICT infrastructure, context-dependent extraction of complex data and information and also to facilitate autonomous decision-making and control. Furthermore, since asset management is a process that should consider all phases of a systems whole lifecycle, e.g. conceptual design; preliminary system design; detailed system design and development; production and construction; utilisation and support; and retirement and disposal; its related information logistics also needs to provide capability to manage information from all inherent phases of the system lifecycle. However, establishment of appropriate information logistics including mechanism for time management, which addresses 'when to deliver'; content management, which refers to 'what to deliver'; communication management, which refers to 'how to deliver'; and context management, which addresses 'where and why to deliver' throughout all phases of a system lifecycle is a great challenge, since necessary information is often hidden among vast quantities of data, stored for other purposes, in different places, and in different formats, and generated throughout the entire lifecycle of a system. Hence, it is commonly realized that the establishment of a dynamic and effective solution for information logistics requires appropriate software architecture and related infrastructure. However, the ultimate goal of information logistics in this context is to support the asset management process to achieve the overall business objectives through provision of information to its stakeholders. This paper describes a service-oriented approach to establishment of information logistics related to asset management of complex technical system within the context of military aviation.

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.

Compilation of papers presented in the technical sessions during the eMaintenance 2012.

Cloud Computing is an emerging research area. It can be utilised for acquiring an effective and efficient information logistics. This paper uses cloud-based technology for the establishment of information logistics for railway system which requires information based on data from different data sources (e.g. railway maintenance, railway operation, and railway business data). In order to improve the performance of the maintenance process relevant data from various sources need to be acquired, filtered, fused, integrated, and analysed for decision making and to facilitate for example, diagnostics and prognostics decisions. The process of maintenance information provisioning is highly dependent on an appropriate information logistics. In this paper the authors have tried to study the improvement in the maintenance performance of railway operations in Sweden.

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.

There is increasing interest in the use of maintenance performance measurement (MPM) and the possibility of using the maintenance audits for benchmarking metrics. This article proposes a methodology for simple measurement, one that accepts the indicators used on a scorecard with four perspectives and is hierarchized according to organizational level. The maintenance audit will evaluate the degree of fulfillment of objectives and the degree of satisfaction obtained from each of those perspectives. It will provide a clear picture of the current status of maintenance organization and the success of implemented policies taking into account the maintenance maturity model, i.e, the logical evolution of the maintenance function in the company.

This paper provides an overview of research and developments in the measurement of maintenance performance. It considers the problems of various measuring parameters and comments on the lack of structure in, and references for, the measurement of maintenance performance.The main focus is to determine how value can be created for organizations by measuring maintenance performance, looking at such maintenance strategies as condition based maintenance, reliability centered maintenance, e-maintenance etc. In other words, the objectives are to find frameworks or models that can be used to evaluate different maintenance strategies and determine the value of these frameworks for an organization.The paper asks the following research questions:- What approaches and techniques are used for Maintenance Performance Measurement (MPM) and which MPM techniques are optimal for evaluating maintenance strategies?- In general, how can MPM create value for organizations, and more specifically, which system of measurement is best for which maintenance strategy?The body of knowledge on maintenance performance is both quantitative and qualitative based. Quantitative approaches include economic and technical ratios, value-based and balanced scorecards, system audits, composite formulations, and statistical and partial maintenance productivity indices. Qualitative approaches include human factors, amongst others. Qualitative-based approaches are adopted because of the inherent limitations of effectively measuring a complex function such as maintenance through quantitative models. Maintenance decision makers often come to the best conclusion using heuristics, backed up by qualitative assessment, supported by quantitative measures. Both maintenance performance perspectives are included in this overview.

Purpose - This paper provides an overview of research and development in the measurement of maintenance performance. It considers the problems of various measuring parameters and comments on the lack of structure in and references for the measurement of maintenance performance. The main focus is to determine how value can be created for organizations by measuring maintenance performance, examining such maintenance strategies as condition-based maintenance, reliability-centred maintenance, e-maintenance, etc. In other words, the objectives are to find frameworks or models that can be used to evaluate different maintenance strategies and determine the value of these frameworks for an organization.Design/methodology/approach - A state-of-the-art literature review has been carried out to answer the following two research questions. Firstly, what approaches and techniques are used for maintenance performance measurement (MPM) and which MPM techniques are optimal for evaluating maintenance strategies? Secondly, in general, how can MPM create value for organizations and, more specifically, which system of measurement is best for which maintenance strategy?Findings - The body of knowledge on maintenance performance is both quantitatively and qualitatively based. Quantitative approaches include economic and technical ratios, value-based and balanced scorecards, system audits, composite formulations, and statistical and partial maintenance productivity indices. Qualitative approaches include human factors, amongst other aspects. Qualitatively based approaches are adopted because of the inherent limitations of effectively measuring a complex function such as maintenance through quantitative models. Maintenance decision makers often come to the best conclusion using heuristics, backed up by qualitative assessment, supported by quantitative measures. Both maintenance performance perspectives are included in this overview.Originality/value - A comprehensive review of maintenance performance metrics is offered, aiming to give, in a condensed form, an extensive introduction to MPM and a presentation of the state of the art in this field.

Compilation of papers presented in the technical sessions during the eMaintenance 2014.

This paper presents an approach to determine the optimal aircraft overhaul capacity in the workshops for an aircraft fleet. The aircraft fleet contains one aircraft type with different models of that type. A mathematical model has been constructed to calculate the lowest cost alternative.The mathematical model uses various types of data to calculate the optimal workshop overhaul capacity like costs, times, numbers of workers, aircrafts used flight time etc. the paper presents one case study carried out representing a future coming need. Parts of the sensitivity analysis are given to show the models behaviour. The objective of this paper is to introduce a model that can be used as a decision helping tool for the decision makers when determine the future needed aircraft overhaul capacity in the workshops. The model can be a part of the emaintenance platform.

This paper proposes a new approach to study reliability of locomotive wheels with Bayesian framework, utilizing locomotive wheel degradation data sets that can be small or incomplete. In our study, a linear degradation path is assumed and locomotive wheels’ installation positions are considered as covariates. A Markov Chain Monte Carlo (MCMC) computational method is also implemented. In the case study, data were collected from a Swedish railway company. This data includes, the diameter measurements of the locomotive wheels, total distances corresponding to their “time to maintenance”, and the wheels’ bill of material (BOM) data. During this study, likelihood functions were constructed for Expontional regression models, Weibull regression models, and lognormal regression models. The results show that the locomotive wheels’ lifetimes are dependent on installation positions. For the studied locomotive wheels data, the Lognormal regression model is a better choice, because the model obtained the lowest Deviance Information Criterion (DIC) values. In addition, under current operation situation (e.g. topography) and current maintenance strategies (re-profiled, lubrication, etc.), the locomotive wheels installed in the second bogie have longer lifetimes than those installed in the first bogie; the wheels installed on the “back” axle have longer lifetimes than those on the “front” axle; and the right side wheels’ lifetime is shorter than that for the left side under a given running situation.

This paper undertakes a reliability study using a Bayesian survival analysis framework to explore the impact of a locomotive wheel's installed position on its service lifetime and to predict its reliability characteristics. The Bayesian Exponential Regression Model, Bayesian Weibull Regression Model and Bayesian Log-normal Regression Model are used to analyze the lifetime of locomotive wheels using degradation data and taking into account the position of the wheel. This position is described by three different discrete covariates: the bogie, the axle and the side of the locomotive where the wheel is mounted. The goal is to determine reliability, failure distribution and optimal maintenance strategies for the wheel. The results show that: (i) under specified assumptions and a given topography, the position of the locomotive wheel could influence its reliability and lifetime; (ii) the Bayesian Log-normal Regression Model is a useful tool.

Spherical roller bearings in railway car wheels are critical components whose failure may have catastrophic consequences. The present study aims to analyse the mechanical stability of greases and temperature of bearings as indicators for condition-based bearing maintenance. The performed case study includes nine fully-formulated commercial greases examined in the wheel bearings of five ore cars operated in northern Scandinavia. The studied ore cars travelled a distance of about 300 000 km during a period of three years. Small samples of the greases were taken on eight occasions to test their mechanical stability. In addition, the temperatures of the bearings were continuously recorded. After the test period, the wear, electrical damage, and corrosion of the bearings were examined. One of the findings is that the shear stress of the grease at a certain shear velocity (the certain yieldstress (CEY) value) is a good maintenance indicator and is highly dependent on the grease type. The bearing's wear, electrical damage and corrosion also depend on the grease type. However, no oxidation of the greases was identified. The paper also outlines a systematic methodology to determine an overall maintenance indicator for railway roller bearings which is based on the field measurements

Machine health monitoring in today's complex plant systems has gained moreprominence than ever before because of steep increase in machinery costs, plant investments and maintenance expenses. A breakdown in any one machine or a component in a plant could mean huge losses coupled with safety and environmental threats as in the case of nuclear or chemical plants. The advances in manufacturing technology and the competition in the market necessitate the continuous availability of machinery for production. This has created a need for integrating maintenance with other manufacturing activities for better plant availability and efficiency. The objective of present research work is to present one such integrated machine health monitoring (IMHM) system developed using knowledge-based systems. The proposed model can be a useful maintenance tool in majority of small and medium scale manufacturing plants. A comprehensive knowledge based system (KBS)could bedeveloped over a period of time for industrial machinery which can monitor the major machinery faults and provide expert maintenance solutions through measurement and analysis of machine parameters such as power, vibration, noise, temperature, wear debris, lubricant condition, etc. A fault diagnosis system with KBS is based on computer programs interlinking fault symptoms, faults and remedies. These solutions are based on published information about permissible machine parameters in handbooks, journals, conferences besides the past maintenance experiences and from machine expert's knowledge regarding specific machinery problem and its solution. The paper outlines possible sub-modules for IMHM along with their features.

There has been a steady rise in the machine health monitoring research due to increasing complexities of the industrial machinery. Cost of the machines and machine downtime effects like production loss, maintenance expenses and reduction in overall plant productivity are the areas of concern for modern manufacturing plants. Researchers are developing newer models and algorithms to overcome new issues and challenges in the machine health monitoring using various tools and techniques for both online and off-line machine conditions. The present paper proposes an off-line knowledge based application for machine health monitoring using MATLAB. The application has modules for intelligently addressing the machinery troubleshooting problems based on vibration standard, ISO 10816. The proposed application has three modules: machinery vibration troubleshooting, vibration severity criterion and induction motor troubleshooting. The application is simple to use and modify in which, the machine faults can be detected and analyzed quickly. This will reduce the machine down-time, maintenance costs, etc., and increase the plant productivity

The advances in manufacturing technology and the competition in the market necessitate the continuous availability of machinery for production. This has created a need for effective and efficient maintenance practices resulting in improved plant performance. Instead of the common fragmented approaches to maintenance, an integrated approach is recommended. One such approach to effective maintenance is, Knowledge Based Maintenance Systems for machine health monitoring which can be integrated with plant maintenance. A fault diagnosis system with Knowledge Based System (KBS) is based on computer programs interlinking fault symptoms, faults and remedies. A comprehensive KBS system can be developed for industrial machinery which can monitor the major machinery faults or abnormalities of the machining centres and provide expert maintenance solutions through measurement and analysis of machine health parameters such as vibration, temperature, wear debris, lubricant condition, etc. These solutions are based on published information about permissible machine parameters in handbooks, journals and conferences, past maintenance experiences and from machine expert’s knowledge regarding specific machinery problem and its solution. The objective of the present research paper is, to suggest one such system for machine health monitoring which would be a useful maintenance tool in a majority of small and medium scale manufacturing units. The KBS for machine health monitoring has modules on various aspects of machine health monitoring. Many of these sections are interactive type with easy-to-answer questions, posed by the system. Based on the user’s response and built-in knowledge base, comparisons are made by the system and appropriate maintenance solutions are suggested to the used.