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  • 151.
    Singh, Sarbjeet
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Baglee, David
    Institute for Automotive Manufacturing and Advanced Practices, University of Sunderland.
    Knowles, Michael
    Institute for Automotive Manufacturing and Advanced Practices, University of Sunderland.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Developing RCM strategy for wind turbines utilizing e-condition monitoring2015In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 6, no 2, p. 150-156Article in journal (Refereed)
    Abstract [en]

    Renewable energy sources such as wind energy are available without any limitations. In order to extract this energy efficiency, the reliability of such technologies is critical if pay back periods and power generation requirements are to be met. Due to recent developments in the field of wind engineering and in particular the expansion of installed capacity around the world, the need for reliable and intelligent diagnostic tools is of greater importance. The number of offshore wind turbines installed in the seas around Britain’s coasts is likely to increase from just fewer than 150–7,500 over the next 10 years with the potential cost of £10 billion. Operation and Maintenance activities are estimated to be 35 % against the cost of electricity. However, the development of appropriate and efficient maintenance strategies is currently lacking in the wind industry. The current reliability and failure modes of offshore wind turbines are known and have been used to develop preventive and corrective maintenance strategies which have done little to improve reliability. In addition, the failure of one minor component can cause escalated damage to a major component, which can increase repair and or replacement costs. A reliability centered maintenance (RCM) approach offers considerable benefit to the management of wind turbine operations since it includes an appreciation of the impact of faults on operations. Due to the high costs involved in performing maintenance and the even higher costs associated with failures and subsequent downtime and repair, it is critical that the impacts are considered when maintenance is planned. This paper provides an overview of the application of RCM and on line e-condition monitoring to wind turbine maintenance management. Unplanned maintenance levels can be reduced by increasing the reliability of the gear box and individual gears through the analysis of lubricants. Finally the paper will discuss the development of a complete sensor-based processing unit that can continuously monitor the wind turbines lubricated systems and provide, via wireless technology, real time data enabling on shore staff with the ability to predict degradation anticipate problems and take remedial action before damage and failure occurs

  • 152.
    Singh, Sarbjeet
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Bending moment assessment at L5/S1 and parameter optimization using Taguchi design during lifting task2012In: Journal of Ergonomic Study, ISSN 2076-5517, Vol. 14, no 2, p. 79-89Article in journal (Refereed)
    Abstract [en]

    This paper reports on the investigation of the effect of lifting parameters on bending moment at the lower back. The experimental study has been conducted under varying load weights, horizontal location of load from L5/S1 and lifting technique (stoop, full squat and lifting device). The design of experiments approach using Taguchi’s orthogonal array was used. The level of importance of the parameters on bending moment has been determined using the analysis of variance (ANOVA). After implementing a lifting device 26-34 % reduction in bending moment at L5/S1 has been observed.

  • 153.
    Singh, Sarbjeet
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Baglee, David
    Department of Computing, Engineering and Technology, Institute for Automotive and Manufacturing Advanced Practise, University of Sunderland.
    Björling, Sten-Erik
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Self-maintenance techniques: a smart approach towards self-maintenance system2014In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, no 1, p. 75-83Article in journal (Refereed)
    Abstract [en]

    The modern systems operating at varying conditions brought a new paradigm shift to in-machine renovation and repair. These systems often encounter an infinite collection of clumsy diagnostic tools and applications that decrease agility, increase time-to-repair, and increase management overheads. One approach is to remove the human and potential costly and time consuming human errors, from the diagnosis of faults and implementation of a maintenance strategy. In order to achieve this it is necessary to develop systems that support advanced intelligent maintenance systems or smart maintenance technologies. Self-maintenance machines can be a better option with the capabilities of condition monitoring, diagnosing, repair planning and executing in order to extend the life and performance of equipment. The objective of this paper is to discuss the concept of self-maintenance, need of self-maintenance, potential scenarios where self-maintenance can be successfully implemented and issues related to self-maintenance machines. It has been concluded that the aim is to have self-maintenance system in order to make a machine capable of reconfiguration, compensation, and self-maintenance.

  • 154.
    Sinkkonen, Tiina
    et al.
    School of Industrial Engineering and Management, Lappeenranta University of Technology.
    Kivimäki, Harri
    Olvi PLC.
    Marttonen, Salla
    School of Industrial Engineering and Management, Lappeenranta University of Technology.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Villarejo, Roberto
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kärri, Timo
    School of Industrial Engineering and Management, Lappeenranta University of Technology.
    Using the life-cycle model with value thinking for managing an industrial maintenance network2016In: International Journal of Industrial and Systems Engineering, ISSN 1748-5037, Vol. 23, no 1, p. 19-35Article in journal (Refereed)
    Abstract [en]

    The objective of this article is to create a general life-cycle model for maintenance decision making in different industries at the item level. The need for network-level tools will increase, as inter-organisational collaboration is emphasised more and more. Previous life-cycle models have mostly viewed the matter from the perspective of just one company, but our model takes the different members of maintenance networks into account. We have also integrated value thinking with life-cycle accounting, as it is crucial for companies to perceive which elements increase the value of each member in their network. The value-based life-cycle model introduced in this article has been mainly developed to support the future planning of maintenance operations. In addition, it can be designed how additional value can be reached through future maintenance and how this value can be equitably shared between the network partners

  • 155.
    Stenström, Christer
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Famurewa, Stephen Mayowa
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Parida, Aditya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Impact of cold climate on failures in railway infrastructure2012Conference paper (Refereed)
    Abstract [en]

    Railway traffic has increased over the last decade due to greater energy costs and the need to reduce emissions. Ensuring the dependability and capacity of railway infrastructure requires efficient and effective maintenance which, in turn, requires good understanding of various physical behaviours, e.g. deterioration and environmental effects. This paper studies the effect of cold climate on railway infrastructure performance using statistics and historical work order data. It finds differences in the number of work orders as a function of season and geographical location.Keywords: railway, performance, temperature, winter, cold, climate, failures, infrastructure, snow, ice, maintenance, reliability, dependability

  • 156.
    Stenström, Christer
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Auditoria de Manutenção Baseada em Elementos Quantitativos e Qualitativos em Sistemas de Saúde2011In: Tecno Hospital, ISSN 1645-9431, no 47, p. 24-29Article in journal (Other academic)
    Abstract [en]

    The dependability of hospital facilities and equipments is a critical element in the performance of health care systems. The availability needs to be near one hundred percent, especially equipment related to the emergency department. Faults in equipments have to be rectified as fast as possible, i.e. the organizational readiness and the maintainability of the equipments need to be excellent. This paper introduces a maintenance audit model, based on quantitative and qualitative elements, together with a maturity model for facilities and equipments of health care systems. Qualitative and quantitative methods are combined in order to complement advantages and disadvantages of them both.

  • 157.
    Stenström, Christer
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Parida, Aditya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Maintenance performance indicators for railway infrastructure management2012In: Proceedings of the First International Conference on Railway Technology: Research, Development and Maintenance / [ed] J. Pombo, Stirlingshire, UK: Civil-Comp Press , 2012Conference paper (Refereed)
    Abstract [en]

    Railway traffic has increased over the last decade and it is believed to increase further with the movement of transportation from road to rail, due to the increasing energy costs and the demand to reduce emissions. To manage the assets effectively within the business objectives, the effect of maintenance activities must be measured and monitored. Performance indicators are continuously identified and developed to support infrastructure managers in decision making, but they are often ad-hoc and seldom standardised. In this paper, about 130 maintenance performance indicators for railway infrastructures have been mapped and compared with indicators of European standard. The listed indicators form a basis for constructing a maintenance performance measurement system for railway infrastructures.

  • 158.
    Stenström, Christer
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Parida, Aditya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Performance indicators of railway infrastructure2012In: The international Journal of railway technology, ISSN 2049-5358, E-ISSN 2053-602X, Vol. 1, no 3, p. 1-18Article in journal (Refereed)
    Abstract [en]

    Railway traffic has increased over the last decade and it is believed to increase further with the movement of transportation from road to rail, due to the increasing energy costs and demand to reduce emissions. As a result of increasing need of railway capacity, more efficient and effective operation and maintenance is required. To manage the assets effectively within the business objectives, the results of operation and maintenance activities must be measured and monitored. Performance indicators are developed to support infrastructure managers in decision making, but they are often ad hoc and seldom standardised. In this paper, performance indicators for railway infrastructure, with primary focus on the railway track, have been mapped and compared with indicators of European Standards. The listed indicators can be applied to form a performance measurement system for railway infrastructure.Keywords: railway infrastructure, maintenance, operation, management, performance measurement, indicator.

  • 159.
    Stenström, Christer
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Parida, Aditya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Link and effect model for performance improvement of railway infrastructure2013In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 227, no 4, p. 392-402Article in journal (Refereed)
    Abstract [en]

    Railway traffic has increased over the last decade due to its fuel efficiency and the need to reduce emissions. The railway infrastructure performance needs to be measured to allow assets to be managed effectively against set objectives. Various systems are used to collect and store data on traffic, failures, inspections, track quality, etc. However, these systems are often used in an ad hoc manner, partly because of the weaknesses of traditional performance measurement systems. This paper proposes a link and effect model which is focused on the areas of continuous improvement, the key elements of strategic planning and on the underlying factors responsible for the railway performance. The model provides information on the performance of railway systems and components, and how they are linked to each other and to the overall objectives, thereby facilitating proactive decision-making. The model is applied in a case study on the Iron Ore Line, Sweden. The performance of a section of the line is studied in terms of failures, train delays and repair times, and ranked through a risk matrix and composite indicator.Keywords: Railway, infrastructure, performance measurement, performance indicator, reliability, availability, maintainability and supportability, maintenance, failure analysis

  • 160.
    Stenström, Christer
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Parida, Aditya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Maintenance value drivers, killers and their indicators2011In: MPMM 2011: Maintenance Performance Measurement & Management: Conference Proceedings / [ed] Diego Galar; Aditya Parida; Håkan Schunnesson; Uday Kumar, Luleå: Luleå tekniska universitet, 2011, p. 125-130Conference paper (Refereed)
    Abstract [en]

    Value driven maintenance (VDM) is a fairly new maintenance management method based on four maintenance value drivers and to calculate the discounted present value (DPV) of the maintenance strategy. However, the dependability of the engineering assets needs to be assessed in order to make an estimation of the DPV. Therefore, the European standard EN 15341 has been studied, in order to find the most essential indicators for the four value drivers and for estimation of the DPV. Terminology containing drivers and killers are common in the field of asset management, but definitions are scarce. One section in this paper is therefore dedicated to review these terms.

  • 161.
    Stenström, Christer
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Parida, Aditya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Performance indicators and terminology for value driven maintenance2013In: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 19, no 3, p. 222-232Article in journal (Refereed)
    Abstract [en]

    Purpose – Value driven maintenance (VDM) is a fairly new maintenance management methodology based on four maintenance value drivers and the formula of net present value (NPV) to calculate the value of different maintenance strategies. However, the dependability of the engineering assets needs to be assessed in order to make an estimation of the NPV. Therefore, standardised indicators have been critically analysed to find the most essential indicators for the four value drivers and for estimation of the NPV. Terminology containing performance drivers and killers are common in the field of asset management, but not many publications can be found for their detailed descriptions. One section in this paper is therefore dedicated to review these terms. A comprehensive description and classification of performance killers and drivers, and of indicators for VDM are presented in this paper.Design/methodology/approach – Review of literature for technical terminology and review of standards for identification of indicators for maintenance performance measurement and NPV of maintenance.Findings – Common description of technical terminology as used by researchers and identification of the most important indicators for maintenance performance measurement and the NPV of maintenance. Indicators classified under economic, technical, organizational and HSE perspectives from EN 15341 standards are discussed and identified.Value – Description of emerging terminology in maintenance performance measurement adds to the consistency in communication of researchers and business stakeholders. Also, the identified maintenance performance indicators can facilitate performance measurement of organisations new to the process of measuring and analysing their performance.

  • 162.
    Teymourian, Kiumars
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Seneviratne, Dammika
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Ergonomics contribution in maintainability2017In: Management Systems in Production Engineering, ISSN 2299-0461, Vol. 25, no 3, p. 217-223, article id 31Article in journal (Refereed)
    Abstract [en]

    The objective of this paper is to describe an ergonomics contribution in maintainability. The economical designs, inputs and training helps to increase the maintainability indicators for industrial devices. This analysis can be helpful, among other cases, to compare systems, to achieve a better design regarding maintainability requirements, to improve this maintainability under specific industrial environment and to foresee maintainability problems due to eventual changes in a device operation conditions. With this purpose, this work first introduces the notion of ergonomics and human factors, maintainability and the implementation of assessment of human postures, including some important postures to perform maintenance activities. A simulation approach is used to identify the critical posture of the maintenance personnel and implements the defined postures with minimal loads on the personnel who use the equipment in a practical scenario. The simulation inputs are given to the designers to improve the workplace/equipment in order to high level of maintainability. Finally, the work concludes summarizing the more significant aspects and suggesting future research.

  • 163.
    Teymourian, Kiumars
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Seneviratne, Dammika
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Ergonomics Contribution in Maintainability2017In: Proceedings of MPMM 2016: 6th International Conference on Maintenance Performance Measurement and Management, 28 November 2016, Luleå, Sweden / [ed] Diego Galar, Dammika Seneviratne, Luleå: Luleå tekniska universitet, 2017, p. 180-186Conference paper (Refereed)
    Abstract [en]

    The objective of this paper is to describe an ergonomics contribution in maintainability. The economical designs, inputs and training helps to increase themaintainability indicators for industrial devices. This analysis can be helpful, among other cases, to compare systems, to achieve a better design regarding maintainability requirements, to improve this maintainability under specific industrial environment and to foresee maintainability problems due to eventual changes in a device operation condition. With this purpose, this work first introduces the notion of ergonomics and human factors, maintainability and the implementation of assessment of human postures, including some important postures to perform maintenance activities. A simulation approach is used to identify the critical posture of the maintenance personnel and implements the defined postures with minimal loads on the personnel who use the equipment in a practical scenario. The simulation inputs are given to the designers to improve the workplace/equipment in order to high level of maintainability. Finally, the work concludes summarizing the more significant aspects and suggesting future research.

  • 164.
    Teymourian, Kiumars
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Seneviratne, Dammika
    Technalia Research and Innovation, La Amunia, Zaragoza, Spain.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Technalia Research and Innovation, La Amunia, Zaragoza, Spain.
    Ergonomics in Maintainability: System and Product Design Process2018In: Proceedings of Maintenance Preformance Measurement and Magangement (MPMM), 2018Conference paper (Refereed)
  • 165.
    Teymourian, Kiumars
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Seneviratne, Dammika
    Tecnalia Research and Innovation, La Almunia, Zaragoza, Spain.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Tecnalia Research and Innovation, La Almunia, Zaragoza, Spain.
    Integrating Ergonomics in Maintanability: A Case Study from Manufacturing Industry2019In: Journal of Industrial Engineering and Management Science, E-ISSN 2446-1822, Vol. 2018, no 1, p. 131-150, article id 8Article in journal (Refereed)
    Abstract [en]

    Maintainability is key part of Reliability, Availability, Maintainability and Safety (RAMS) estimation and prediction in complex assets. Indeed, availability calculation comprises accurate estimation of maintainability and frequently, it is just a time stamp for mean time to repair (MTTR) estimations. However, maintainability is a human related figure where the skill, capabilities, tools and the design of the asset play key role in its performance. The aim of this article is to describe the effects of ergonomists’ contribution during maintainability process for system/products design. System designer thinking in system and its subsystem in a way of technical functionality. On the other hand, ergonomists are expertise in human capability and limitation. If human become a part of system than their interface and interaction become crucial factors in a success of system performance and its sustainability. In this paper, it has discussed three main issues that help the process of maintainability design. These issues are safety, task analysis and risk analysis. It has also touched reliability engineer’s task to increase Overall Equipment Effectiveness (OEE). These issues are explained via a case study from a manufacturing industry.

  • 166.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Railway Assets: A Potential Domain for Big Data Analytics2015In: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 53, p. 457-467, article id 53Article in journal (Refereed)
    Abstract [en]

    Two concepts currently at the leading edge of todays information technology revolution are Analytics and Big Data. The public transportation industry has been at the forefront in utilizing and implementing Analytics and Big Data, from ridership forecasting to transit operations Rail transit systems have been especially involved with these IT concepts, and tend to be especially amenable to the advantages of Analytics and Big Data because they are generally closed systems that involve sophisticated processing of large volumes of data. The more that public transportation professionals and decision makers understand the role of Analytics and Big Data in their industry in perspective, the more effectively they will be able to utilize its promise. This paper gives an overview of Big Data technologies in context of transportation with specific to Railways. This paper also gives an insight on how the existing data modules from the transport authority combines Big Data and how can be incorporated in providing maintenance decision making.

  • 167.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, Ajit Kumar
    Department of Electrical Engineering, Indian Institute of Technology, Bombay, International Institute of Information Technology, P-14, Pune Infotech Park, Phase-1, Hinjawadi, Stord/Haugesund University College, Haugesund.
    Context-Based Maintenance and Repair Shop Suggestion for a Moving Vehicle2016In: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 67-81Conference paper (Refereed)
    Abstract [en]

    Maintenance of moving vehicles is quite challenging because they may disrupt the normal flow of transportation due to unexpected breakdowns, slowdowns and stoppages. In order to avoid stoppages and to minimize the downtime, maintenance and condition monitoring systems must be optimized. On one hand the condition monitoring on board should provide automatic failure detection, identification and localization together with a prognostic of the future failures. On the other hand maintenance logistics and product supportability must be also optimized since the onboard system should provide a suggestion of a repair shop that depends on location, cost and availability of spare parts, technicians’ skills and queuing time for repairs. However the vehicles are independent assets interacting among them within the traffic system and also interacting with the infrastructure (roads, rails etc.) seriously affected by weather, maintenance of infra, regulations etc. Therefore the proposed solution is to equip the vehicles with a context-aware system that monitors the condition and maintenance schedules of parts and alarm the driver of the parts that are in near to repair cycle. This system will perform risk analysis and will communicate with the cloud propose a decision of selection of repair shop on the location and path of vehicle depending on weather, road and traffic, cost and availability of spare parts at respective repair shops based on risk assessment and prediction. The information contained in the cloud will also communicate the workshop that will book time slot and block the necessary spare parts for the coming vehicle minimizing waiting time. This mechanism will help in reducing unexpected stoppages, vehicle degradation and efficient spare parts management combining in a successful way the workload of the workshops from both natural sources, the time based inspections and repairs together with the reactive maintenance coming from unexpected breakdown

  • 168.
    Tormos, B.
    et al.
    University of Politecn Valencia, CMT Motores Term.
    Olmeda, P.
    University of Politecn Valencia, CMT Motores Term.
    Gomez, Y.
    University of Politecn Valencia, CMT Motores Term.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Monitoring and analysing oil condition to generate maintenance savings: a case study in a CNG engine powered urban transport fleet2013In: Insight (Northampton), ISSN 1354-2575, E-ISSN 1754-4904, Vol. 55, no 2, p. 84-87Article in journal (Refereed)
  • 169.
    Villarejo, Roberto
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Johansson, Carl-Anders
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Menendez, Manuel
    Vias y Construcciones S.A..
    Perales, Numan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Context Awareness And Railway Maintenance2014In: Proceedings of the 3rd international workshop and congress on eMaintenance: June 17-18 Luleå, Sweden : eMaintenance, Trends in technologies & methodologies, challenges, possibilites and applications / [ed] Uday Kumar; Ramin Karim; Aditya Parida; Philip Tretten, Luleå: Luleå tekniska universitet, 2014, p. 17-24Conference paper (Refereed)
    Abstract [en]

    A railway is an extremely complex system requiring maintenancedecision support systems to gather data from many disparatesources. These sources include traditional maintenanceinformation like condition monitoring or work records, as well astraffic information, given the criticality of maintenance inavoiding traffic disruptions and the need to minimise the trackpossession time for maintenance.A methodology is required if maintainers are to understand thedata as a whole. Context engines try to link the various dataconstellations and to define interactions within the railwaysystem. This is not easy since data have different natures, originsand granularity. But if all information surrounding the railwayasset can be considered, decisions will be more accurate andproblems like false alarms or outlying anomalies will be detected.The contextualisation of the data seems to be a feasible way toallow condition monitoring data i.e physical measurements andother variables, to be understood under certain conditions(weather, regulations etc.) and as a consequence of certain actions(maintenance interventions, overhauls, outsourcing warrantiesetc.).This paper proposes the use of context engines to providemeaningful information out of the overwhelming amount ofcollected and recorded data so that proper maintenance decisionscan be made. In this scenario, fluffy information coming fromwork orders and expertise of maintainers is a big issue since suchinformation must be converted to numerical values. The fuzzylogic approach seems a promising way to integrate suchinformation sources for diagnosis.

  • 170.
    Villarejo, Roberto
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Johansson, Carl-Anders
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Sandborn, Peter
    University of Maryland, Department of Mechanical Engineering.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Context-driven decisions for railway maintenance2016In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 230, no 5, p. 1469-1483Article in journal (Refereed)
    Abstract [en]

    Railway assets suffer wear and tear during operation. Prognostics can be used to assess the current health of a system and predict its remaining life, based on features that capture the gradual degradation of its operational capabilities. Prognostics are critical to improve safety, plan successful work, schedule maintenance, and reduce maintenance costs and down time. Prognosis is a relatively new area; however, it has become an important part of condition-based maintenance of systems. As there are many prognostic techniques, usage must be tuned to particular applications. Broadly stated, prognostic methods are either data driven, or rule or model based. Each approach has advantages and disadvantages, depending on the hierarchical level of the analysed item; consequently, they are often combined in hybrid applications. A hybrid model can combine some or all model types; thus, more-complete information can be gathered, leading to more-accurate recognition of the impending fault state. However, the amount of information collected from disparate data sources is increasing exponentially and has different natures and granularity; therefore, there is a real need for context engines to establish meaningful data links for further exploration. This approach is especially relevant in railway systems where the maintainer and operator know some of the failure mechanisms, but the sheer complexity of the infrastructure and rolling stock precludes the development of a complete model-based approach. Hybrid models are extremely useful for accurately estimating the remaining useful life (RUL) of railway systems. This paper addresses the process of data aggregation into a contextual awareness hybrid model to obtain RUL values within logical confidence intervals so that the life cycle of railway assets can be managed and optimized.

  • 171.
    Villarejo, Roberto
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Johansson, Carl-anders
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Urko, Leturiondo
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. IK4 Ikerlan, P J Ma Arizmendiarrieta 2, Arrasate Mondragon 20500, Spain.
    Simon, Victor
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Seneviratne, Dammika
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Bottom to Top Approach for Railway KPI Generation2017In: Management Systems in Production Engineering, ISSN 2299-0461, Vol. 25, no 3, p. 191-198, article id 28Article in journal (Refereed)
    Abstract [en]

    Railway maintenance especially on infrastructure produces a vast amount of data. However, having data is not synonymous with having information; rather, data must be processed to extract information. In railway maintenance, the development of key performance indicators (KPIs) linked to punctuality or capacity can help planned and scheduled maintenance, thus aligning the maintenance department with corporate objectives. There is a need for an improved method to analyse railway data to find the relevant KPIs. The system should support maintainers, answering such questions as what maintenance should be done, where and when. The system should equip the user with the knowledge of the infrastructure's condition and configuration, and the traffic situation so maintenance resources can be targeted to only those areas needing work. The amount of information is vast, so it must be hierarchized and aggregated; users must filter out the useless indicators. Data are fused by compiling several individual indicators into a single index; the resulting composite indicators measure multidimensional concepts which cannot be captured by a single index. The paper describes a method of monitoring a complex entity. In this scenario, a plurality of use indices and weighting values are used to create a composite and aggregated use index from a combination of lower level use indices and weighting values. The resulting composite and aggregated indicators can be a decision-making tool for asset managers at different hierarchical levels.

  • 172.
    Wandt, Karina
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Context adapted prognostics and diagnostics2012In: The Ninth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, 2012, Vol. 1, p. 541-550Conference paper (Refereed)
    Abstract [en]

    Context adaptation is an important aspect of prognostics and diagnostics as it facilitates the ability to provide relevant information to the consumers of that information. For example, eTechnologies facilitate the communication of data between systems and they assist stakeholders in different parts of an enterprise to make decisions based on the same data. However, decisions may differ, depending on individual stakeholders and specific prognostic and diagnostic processes and techniques, e.g. data fusion or data mining. The correct use of eTechnologies can improve the maintenance of an item or system, thus extending its remaining useful life. The challenge is learning how to make good use of eTechnology and ensure that the right information is provided to the right information consumer, e.g. stakeholders within various processes of an enterprise.Technical solutions in industry are often complex; they are created in heterogeneous environments and the information generated must adapt to different user contexts. Hence, context adaptation can be considered a key requirement for systems operating in heterogeneous environments. This paper considers context to be a template that describes a set of generalised characteristics of a real-world situation; the information in the template differs depending on the situation but the type of information is the same. It defines context adaption as the process of gathering information about the context template, such as structure and information type, evaluating this information and changing the observable behaviour to fit the current context

  • 173.
    Zhang, Shuangsheng
    et al.
    School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China.Xuzhou Urban Water Resources Management Office, Xuzhou, China.
    Liu, Hanhu
    School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China..
    Qiang, Jing
    School of Mathematics, China University of Mining and Technology, Xuzhou, China.
    Gao, Hongze
    GHD Services, Inc, Waterloo, Ontario, Canada.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Lin, Jing
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Optimization of Well Position and Sampling Frequency for Groundwater Monitoring and Inverse Identification of Contamination Source Conditions Using Bayes’ Theorem2019In: CMES - Computer Modeling in Engineering & Sciences, ISSN 1526-1492, E-ISSN 1526-1506, Vol. 119, no 2, p. 373-394Article in journal (Refereed)
    Abstract [en]

    Coupling Bayes’ Theorem with a two-dimensional (2D) groundwater solute advection-diffusion transport equation allows an inverse model to be established to identify a set of contamination source parameters including source intensity (M ), release location ( X0 , Y0) and release time (T0), based on monitoring well data. To address the issues of insufficient monitoring wells or weak correlation between monitoring data and model parameters, a monitoring well design optimization approach was developed based on the Bayesian formula and information entropy. To demonstrate how the model works, an exemplar problem with an instantaneous release of a contaminant in a confined groundwater aquifer was employed. The information entropy of the model parameters posterior distribution was used as a criterion to evaluate the monitoring data quantity index. The optimal monitoring well position and monitoring frequency were solved by the two-step Monte Carlo method and differential evolution algorithm given a known well monitoring locations and monitoring events. Based on the optimized monitoring well position and sampling frequency, the contamination source was identified by an improved Metropolis algorithm using the Latin hypercube sampling approach. The case study results show that the following parameters were obtained: 1) the optimal monitoring well position (D) is at (445, 200); and 2) the optimal monitoring frequency (Δt) is 7, providing that the monitoring events is set as 5 times. Employing the optimized monitoring well position and frequency, the mean errors of inverse modeling results in source parameters (M, X0 ,Y0 ,T0 ) were 9.20%, 0.25%, 0.0061%, and 0.33%, respectively. The optimized monitoring well position and sampling frequency can effectively safeguard the inverse modeling results in identifying the contamination source parameters. It was also learnt that the improved Metropolis-Hastings algorithm (a Markov chain Monte Carlo method) can make the inverse modeling result independent of the initial sampling points and achieves an overall optimization, which significantly improved the accuracy and numerical stability of the inverse modeling results.

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