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  • 201.
    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.

  • 202.
    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 Performance Measurement and Management (MPMM) Conference 2018 / [ed] José Torres Farinha; Diego Galar, FCTUC-DEM , 2018, p. 18-23Conference paper (Refereed)
    Abstract [en]

    Maintainability is key part of RAMS estimation and prediction in complex assets. Indeed, availability calculation comprises accurate estimation of maintainability and many times, it is just a time stamp for 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 ergonomist 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, ergonomist 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 four main issues that help the process of maintainability design. These issues are safety (Safety I and Safety II), task analysis (Hierarchical Task Analysis (HTA) as tool) and risk analysis (using William Fine method). It has also touched reliability engineer’s task in order to increase Overall Equipment Effectiveness (OEE).

  • 203.
    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.

  • 204.
    Teymourian, Kiumars
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Seneviratne, Dammika
    TECNALIA, Basque Research and Technology Alliance (BRTA).
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. TECNALIA, Basque Research and Technology Alliance (BRTA).
    Ergonomics Evaluation in Designed Maintainability:Case Study Using 3 DSSPP2021In: Management Systems in Production Engineering, ISSN 2299-0461, Vol. 29, no 4, p. 309-319Article in journal (Refereed)
    Abstract [en]

    Maintainability is one of the design parameters (reliability, availability, maintainability, and safety (RAMS)) and maintenance is needed to keep the respective design in sustainable use. At the same time, the human is involved in the form of interface and interaction in an engineered product/system designed. Ergonomics is a multi-disciplinary science that considers human capabilities and limitations in a broader sense. The objective of this paper is to integrate ergonomics into the maintainability design process in order to facilitate maintenance operation in lesser; time, cost, easier operation as well as the well-being of human who is involved. In other words, good ergonomics lead to good economics and in a broader sense, sustainability. This investigation shows that designing comfortable workplaces and lesser workload for maintenance operators will be beneficial for the maintainability design process and also improve the meantime to repair MTTR. In order to evaluate the effect of designed work-place and workload on maintainers 3 D Static Strength Prediction Program (3D SSPP) that is commonly used as an ergonomics evaluation tool in scientific studies was applied.

  • 205.
    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, 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.

  • 206.
    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.
    Space weather climate impacts on railway infrastructure2020In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 11, no 2, p. 267-281Article in journal (Refereed)
    Abstract [en]

    Space weather is a phenomenon in which radioactivity and atomic particles is caused by emission from the Sun and stars. It is one of the extreme climate events that could potentially has short-term and long-term impacts on infrastructure. The effects of this phenomenon are a multi-fold process that include electronic system, equipment and component failures, short-term and long-term hazards and consequences to astronauts and aircraft crews, electrostatic charge variation of satellites, disruptions in telecommunications systems, navigational systems, power transmission failures and disturbances to the rail traffic and power grids. The critical infrastructures are becoming interdependent to each other and these infrastructures are vulnerable if one of them is affected due to space weather. Railway infrastructure could be affected by the extreme space weather events and long-term evolution due to direct and indirect effects on system components, such as track circuits, electronic components in-built in signalling systems or indirectly via interdependencies on power, communications, etc. While several space weather-related studies focus on power grids, Global Navigation Satellite System (GNSS) and aviation sectors, a little attention has focused towards probability of railway infrastructure disruptions. Nevertheless, disruptions due to space weather on signalling and train control systems has documented but other systems that railway infrastructure dependent upon are not very well studied. Due to the advancements in digitalization, cloud storage, Internet of Things (IoT), etc., that are embedded with electronic equipment are also possible to prone to these effects and it is even become more susceptible to the extreme space weather events. This paper gives a review of space weather effects on railways and other transportation systems and provide some of the mitigation measures to the infrastructure and societal point of view.

    Download full text (pdf)
    fulltext
  • 207.
    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

  • 208.
    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: Non-Destructive Testing & Condition Monitoring, ISSN 1354-2575, E-ISSN 1754-4904, Vol. 55, no 2, p. 84-87Article in journal (Refereed)
    Abstract [en]

    A case study was conducted in a CNG engine powered urban transport fleet to monitor and analyze oil condition required to generate maintenance savings. The case study used a real urban transport fleet, which used diesel and CNG powered vehicles, to quantify the differences in the engine oil degradation rate for the two types of engine and to assess how different cost or quality engine oils behaved in CNG vehicles. A comparative assessment of engine oil behavior between diesel and CNG engine powered vehicles was performed, showing that demands on CNG engine oils were higher than in diesel engines, as highlighted by a faster oil degradation rate in the earlier engine. An urban transport fleet company agreed to collaborate with the case study to realize these objectives. Two different vehicle types were considered for the investigations, such as CNG and diesel engine powered vehicles.

  • 209.
    Torres Farinha, José
    et al.
    CEMMPRE-Centre for Mechanical Engineering, Materials and Processes, Univ. of Coimbra, Portugal; ISEC/IPC-Polytechnic Institute of Coimbra, Portugal.
    Raposo, Hugo Nogueira
    CEMMPRE-Centre for Mechanical Engineering, Materials and Processes, Univ. of Coimbra, Portugal; ISEC/IPC-Polytechnic Institute of Coimbra, Portugal.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Life Cycle Cost versus Life Cycle Investment - A New Approach2020In: WSEAS transactions on systems and control, ISSN 1991-8763, E-ISSN 2224-2856, Vol. 15, p. 743-753Article in journal (Refereed)
    Abstract [en]

    The paper proposes a model for the life cycle of physical assets that includes the maintenance policy, because it has direct implications on the equipment’s Return On Investment (ROI) and Life Cycle Cost; the developed model can be applied to any type of physical asset. The model is called Life Cycle Investment (LCI) instead of the traditional Life Cycle Cost (LCC). The paper proposes a new methodology based on the modified economic life cycle and lifespan methods by including the maintenance policy using maintenance Key Performance Indicators (KPI), namely Availability, based on the Mean Time Between Failures (MTBF) and the Mean Time To Repair (MTTR). The benefits (profits) that result from the asset’s Availability must be balanced with the initial investment and the variable maintenance investment along its life, which has relation with the maintenance policy and the ROI.

  • 210.
    van Horenbeek, Adriaan
    et al.
    Centre for Industrial management, KU Leuven, Leuven, Belgium.
    Pintelon, Liliane
    Centre for Industrial management, KU Leuven.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Integration of disparate data sources to perform maintenance prognosis and optimal decision making2012In: The Ninth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, 2012, Vol. 1, p. 386-397Conference paper (Refereed)
    Abstract [en]

    Prognosis can be defined as the course of predicting a failure of equipment or a component in advance, whereas prognostication refers to the act of prediction. The three main branches of condition based maintenance are diagnosis, prognosis, and treatment-prognosis, however prognosis is admittedly the most difficult. Also, this area has been the least described in literature and the knowledge about it in a maintenance management context is still poorly systematized. To this day, formal professional attention to prognosis, in the field of maintenance management and engineering in the everyday care of machinery, is often relegated to a secondary status although the availability of prognostic information can considerably improve (e.g. reduce costs, maximize uptime) the performance of machinery and maintenance processes. Ideally, assessment of a prognosis of remaining useful life should be deliberate and explicit. In order to support the maintenance crew in the achievement of this objective an increasing amount of prognostic information is available. Over the last decade, system integration has grown in popularity as it allows organizations to streamline business processes. It is necessary to integrate management data from CMMS (Computer Maintenance Management Systems) with CM (Condition Monitoring) systems and finally SCADA (Supervisory Control And Data Acquisition) and other control systems, widely used in production but with a seldom usage in asset diagnosis and prognosis. The most obvious obstacle in the integration of these data is the disparate nature of the data types involved, moreover several attempts to remedy this problem have fizzled out. Although there have been many recent efforts to collect and maintain large repositories of these types of data, there have been relatively few studies to identify the ways these datasets could be related and linked for prognosis and maintenance decision making. After identifying what and how to predict incipient failures and developing a corresponding prognosis, maintenance engineers must consider how to communicate the prediction. In this activity once again, technicians' psychosocial attributes and values may influence how they discuss prognoses with asset managers. Regardless of whether prognostic assessments are subjective or objective, however, technicians should consider two major points. Firstly, the maintenance crew should clarify in their own minds the link, if any, between their prognostic assessment and their consequent decision making. Secondly, they should consider the ways that they and their assets might benefit from explicitly discussing how the prognostic assessment is linked with diagnostics and preventive maintenance recommendations. These and other steps that maintenance engineers should take in incorporating prognostic information into their decision making are discussed in this paper. The objective is to give an overview of how the integration of disparate data sources, commonly available in industry, can be achieved for maintenance prognosis and optimal decision making.

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    fulltext
  • 211.
    Vila Forteza, Marc
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Repsol, Petronor oil refinery, Muskiz, Bizkaia, Basque Country, Spain.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. TECNALIA, Basque Research and Technology Alliance (BRTA), Paseo Mikeletegi 7, 20009, San Sebastian, Spain.
    Lin, Jing
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Liyanage, Jayantha Prasanna
    University of Stavanger (UiS) Department of Mechanical and Structural Engineering and Materials Science.
    New paradigms in Maintenance, operation, and health management of rotating machinery large fleets. The effect of Industry 4.02022In: 18th International Conference on Condition Monitoring and Asset Management (CM 2022), British Institute of Non-Destructive Testing (BINDT) , 2022, p. 311-321Conference paper (Refereed)
    Abstract [en]

    Rotating machinery belong to the category of major equipment in many large industries as oil refineries. When such assets are installed in an industrial plant, they are expected to perform with minimal faults and failures guaranteeing that the plant can be operated within pre-defined reliability, safety, availability, and performance specifications. This paper provides an insight into current practices when dealing with large fleets of rotating machines in an Industry 4.0 context and what opportunities and challenges are encountered towards improving their safe operation and reliability by taking advantage of the development of new technologies.

    Bearing in mind that centrifugal pumps are the most common rotating machines in oil refineries, this paper is specially focused in this case, but its guidelines can be applied to all types of rotating equipment installed in an industrial plant.

  • 212.
    Vila Forteza, Marc
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Repsol, Petronor oil refinery, Muskiz, Bizkaia, Basque Country, Spain.
    Galar Pascual, 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, A.K.
    Faculty of Engineering and Natural Sciences, Western Norway University of Applied Sciences, Haugesund, Norway.
    Work-In-Progress: Reliability Prediction of Api Centrifugal Pumps Using Survival Analysis2023In: 19th IMEKO TC10 Conference: “MACRO meets NANO in Measurement for Diagnostics, Optimization and Control”: Proceedings / [ed] Zsolt János Viharos; Lorenzo Ciani; Piotr Bilski, International Measurement Confederation (IMEKO) , 2023, p. 116-121Conference paper (Refereed)
  • 213.
    Vila-Forteza, Marc
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. PETRONOR S.A., Barrio San Martin s/n, Muskiz, Spain.
    Jimenez-Cortadi, Alberto
    TECNALIA, Basque Research and Technology Alliance (BRTA), Paseo Mikeletegi 7, 20009, San Sebastian, Spain; Department of Computer Sciences and Artificial Intelligence, University of the Basque Country (UPV/EHU), 20018, Donostia-San Sebastián, Spain.
    Diez-Olivan, Alberto
    TECNALIA, Basque Research and Technology Alliance (BRTA), Paseo Mikeletegi 7, 20009, San Sebastian, Spain; Department of Computer Sciences and Artificial Intelligence, University of the Basque Country (UPV/EHU), 20018, Donostia-San Sebastián, Spain.
    Seneviratne, Dammika
    TECNALIA, Basque Research and Technology Alliance (BRTA), Paseo Mikeletegi 7, 20009, San Sebastian, Spain.
    Galar-Pascual, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. TECNALIA, Basque Research and Technology Alliance (BRTA), Paseo Mikeletegi 7, 20009, San Sebastian, Spain.
    Advanced Prognostics for a Centrifugal Fan and Multistage Centrifugal Pump Using a Hybrid Model2023In: Proceedings of the 5th International Conference on Maintenance, Condition Monitoring and Diagnostics 2021 / [ed] E. Juuso; D. Galar, Springer Nature, 2023, p. 153-165Conference paper (Refereed)
  • 214.
    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.

    Download full text (pdf)
    FULLTEXT01
  • 215.
    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.

  • 216.
    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.

  • 217.
    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

  • 218.
    Zhang, K.
    et al.
    State Key Laboratory of Mechanical Transmission, Shazheng Street 174 Shapingba District, Chongqing, 400044, China.
    Shao, Y.
    State Key Laboratory of Mechanical Transmission, Shazheng Street 174 Shapingba District, Chongqing, 400044, China.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    The dynamic response of a planetary gear train in the presence of a spalling fault2018In: MFPT 2018 - Intelligent Technologies for Equipment and Human Performance Monitoring, Proceedings, Society for Machinery Failure Prevention Technology , 2018, p. 252-266Conference paper (Other academic)
    Abstract [en]

    Planetary gear trains (PGTs) are widely used in industrial applications. Failure often occurs under working conditions. Tooth surface spalling is one of the most common defects in a PGT system; it seriously affects the reliability and safety of the mechanical transmission system and may even cause serious incidents. However, research into the faults of planetary gear trains is insufficient, especially with respect to the response characteristics of a PGT in the presence of a spalling defect. The paper designs spalling cases with different localized distributions to demonstrate their influence on the dynamic performance of the planetary gear set. The research provides a theoretical basis for health diagnosis and early fault detection for a PGT system.

  • 219.
    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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