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  • 1.
    Al-Jumaili, Mustafa
    et al.
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Multi-Criteria Data Quality Assessment Maintenance perspective2014In: 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. 153-158Conference paper (Refereed)
    Abstract [en]

    Data quality (DQ) in maintenance has become an increasinglyimportant aspect to many firms as most of the maintenanceplanning and implementations are based on data analysis. PoorDQ has adverse effects at the operational, tactical, and strategiclevels of any organization. Respectively, poor DQ reducescustomer satisfaction, leading to poor decision making, and hasnegative impacts on strategy execution. To improve DQ as well asto evaluate the current status, DQ need to be measured followingthe fact that only what can be measured can be improved. Ameasure for DQ could be an important support for decisionmakers. In order to assess DQ, related attributes should bedefined. These attributes could be related to the data itself, to themetadata, or to the data representation schemes. After definingthese attributes, an assessment model should be used to evaluatethese attributes. The purpose of this paper is to propose a modelfor DQ assessment. Therefore, a study of DQ attributes and thepossible metrics that could be used to measure these attributes wasundertaken. The proposed model will be applied on datasetprovided by the Swedish Transport Administration (Trafikverket)for validation and to find an estimation measure of the DQ.

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    fulltext
  • 2.
    Aljumaili, Mustafa
    et al.
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Wandt, Karina
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Drift, underhåll och akustik.
    eMaintenance Ontologies for Data Quality Support2015In: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 21, no 3, p. 358-374Article in journal (Refereed)
    Abstract [en]

    Purpose – The purpose of this paper is to explore the main ontologies related to eMaintenance solutions and to study their application area. The advantages of using these ontologies to improve and control data quality will be investigated.

    Design/methodology/approach – A literature study has been done to explore the eMaintenance ontologies in the different areas. These ontologies are mainly related to content structure and communication interface. Then, ontologies will be linked to each step of the data production process in maintenance.

    Findings – The findings suggest that eMaintenance ontologies can help to produce a high quality data in maintenance. The suggested maintenance data production process may help to control data quality. Using these ontologies in every step of the process may help to provide management tools to provide high quality data.

    Research limitations/implications – Based on this study, it can be concluded that further research could broaden the investigation to identify more eMaintenance ontologies. Moreover, studying these ontologies in more technical details may help to increase the understandability and the use of these standards.

    Practical implications – It has been concluded in this study that applying eMaintenance ontologies by companies needs additional cost and time. Also the lack or the ineffective use of eMaintenance tools in many enterprises is one of the limitations for using these ontologies.

    Originality/value – Investigating eMaintenance ontologies and connecting them to maintenance data production is important to control and manage the data quality in maintenance.

  • 3.
    Al-Jumaili, Mustafa
    et al.
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Rauhala, Ville
    Kemi-Tornio University of Applied Science Technology, Kemi, Finland.
    Tretten, Phillip
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Data quality in eMaintenance: a call for research2011In: MPMM 2011: Maintenance Performance Measurement & Management: Conference Proceedings / [ed] Diego Galar; Aditya Parida; Håkan Schunnesson; Uday Kumar, Luleå: Luleå tekniska universitet , 2011, p. 69-73Conference paper (Refereed)
    Abstract [en]

    Effective and efficient maintenance requires a proper information logistics, which can be delivered through eMaintenance solutions. Development of eMaintenance solutions faces extensive challenges. One of these challenges is how to ensure the quality of data used in different eMaintenance solutions. Data Quality (DQ) concerns all phases of the maintenance process.

    The purpose of this paper is to answer the research question: How should DQ be considered and managed when developing eMaintenance solutions?

    To deal with such challenges a case study was conducted at a mining company. Empirical data has been collected through interviews, observations, archival records and workshops.

    The data analysis has been based on an empirical framework that supports the identification of required information services. Conditions that support the DQ and the information logistics, along with that, support the maintenance process have been presented. These aspects have also been related to the phases of a generic maintenance process.

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    FULLTEXT01
  • 4.
    Kour, Ravdeep
    et al.
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Drift, underhåll och akustik.
    EMaintenance solutions for railway maintenance decisions2015In: World Congress on Engineering, WCE 2014: London, 2 - 4 July 2014 / [ed] S.I. Ao; Len Gelman; David W.L. Hukins; Andrew Hunter; Alexander Korsunsky, Hong Kong: Newswood Limited , 2015, p. 228-232Conference paper (Refereed)
    Abstract [en]

    The term eMaintenance emerged in the early 2000s and has become a popular topic in maintenance related literature because of ongoing technological improvements. This paper uses a recent approach, i.e. cloud-based technology, to provide an eMaintenance solution for online time data analysis to make effective and efficient railway maintenance decisions. Due to increased traffic, the Swedish railway sector needs to optimise maintenance, using predictive maintenance to a much higher degree so that unplanned breakdowns and downtime are drastically reduced. The paper shows how research within the railway sector is developing eMaintenance solutions using the cloud and web-based applications for improved condition monitoring, better maintenance and increased uptime. In the proposed solution, data are acquired from railway measurement stations and sent to the eMaintenance cloud, where they are filtered, fused, integrated and analysed to assist maintenance decisions. The paper provides a concept for a web-based eMaintenance solution to assist railway maintenance stakeholders make fact-based decisions and develop more efficient and economically sound maintenance policies.

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    FULLTEXT01
  • 5.
    Kour, Ravdeep
    et al.
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Drift, underhåll och akustik.
    eMaintenance solution through online data analysis for railway maintenance decision-making2014In: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 20, no 3, p. 262-275Article in journal (Refereed)
    Abstract [en]

    Purpose – The purpose of this paper is to demonstrate how research within the railway sector is developing eMaintenance solutions using the cloud and web-based applications for improved condition monitoring, better maintenance and increased uptime. This eMaintenance solution is based on the on-line data acquisition, integration and analysis leading to effective maintenance decision making.Design/methodology/approach – In the proposed methodology, data are acquired from railway measurement stations to the eMaintenance cloud, where they are filtered, fused, integrated and analyzed to assist maintenance decisions. Extensive consultation with stakeholders has resulted in the analysis of railway data.Findings – The paper provides a concept for a web-based eMaintenance solution for railway maintenance stakeholders for making fact-based decisions and develops more efficient and economically sound maintenance policies. Train wheels reaching their maintenance and safety limits are visualised in grids and graphs to assist stakeholders in making the appropriate maintenance decisions.Practical implications – In this paper the authors have demonstrated that the wheel profile and force data can be remotely collected through cloud utilization. The information generated can be used for maintenance decision making. Similarly, other measurable data can also be utilized for maintenance decision making.Originality/value – This paper describes the importance of eMaintenance solution through online data analysis to make effective and efficient railway maintenance decisions, as a case study.

  • 6.
    Kumar, Uday
    et al.
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Karim, RaminLuleå tekniska universitet, Drift, underhåll och akustik.Parida, AdityaLuleå tekniska universitet, Drift, underhåll och akustik.Tretten, PhillipLuleå tekniska universitet, Drift, underhåll och akustik.
    Proceedings of the 3rd international workshop and congress on eMaintenance: June 17-18 Luleå, Sweden : eMaintenance, Trends in technologies & methodologies, challenges, possibilites and applications2014Conference proceedings (editor) (Refereed)
    Abstract [en]

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

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    FULLTEXT01
  • 7.
    Morant, Amparo
    et al.
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle.
    Galar, Diego
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Improvement of configuration management in railway signalling system2012In: Proceedings of the 2nd International Workshop & Congress on eMaintenance: Dec 12-14 Luleå, Sweden : eMaintenace: trends in technologies and methodologies, challenges, possibilities and applications / [ed] Ramin Karim; Aditya Parita; Uday Kumar, Luleå: Luleå tekniska universitet , 2012, p. 23-32Conference paper (Refereed)
    Abstract [en]

    The railway network composed by different systems, such assignalling, power supply, rolling stock and others. The signalling system is used for control, supervision and protection of railway traffic. Its reliability, maintainability and related maintenance support affect the availability of the railway network. Often,signalling system itself is considered as a system-of-systems spread over a wide geographical area and consists of a large number of items with different lifecycle. However, managing a complex technical system with large number of items in different lifecycle phases to achieve required availability is challenging. One major challenge is to define and describe the structure and relation between the system’s inherent items at any specific period of time, i.e. the configuration of the system. The system configuration is important during the design and manufacturing of systems, but it is also essential during the utilisation and retirement of a system. Furthermore, system configuration can be considered as an essential data container to which other data sources can be related, e.g. design data, reliability data, maintainability data, operation data, and maintenance data. Aproper management of configuration data is highly important during a system’s whole lifecycle, e.g. the railway signalling system. Hence, the purpose of this paper is investigate how the process of configuration management related to railway signalling system can be improved through utilisation of Capability Maturity Model Integrated (CMMI).

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    FULLTEXT01
  • 8.
    Tretten, Phillip
    et al.
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Kumar, Uday
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Usability-based eMaintenance for effective performance measurement2011In: MPMM 2011: Maintenance Performance Measurement & Management: Conference Proceedings / [ed] Diego Galar; Aditya Parida; Håkan Schunnesson; Uday Kumar, Luleå: Luleå tekniska universitet , 2011, p. 53-59Conference paper (Refereed)
    Abstract [en]

    Today’s providers of eMaintenance solutions for maintenance and support related to complex technical systems are facing increasing amounts of information flow with the increased complexity of managing data. Organizations developing and providing maintenance support solutions and services also need to improve the capability to efficiently and effectively exploit the increasing amount of design data, product data, operational data, and maintenance data during the system’s whole lifecycle. eMaintenance includes monitoring, collection, recording, and distribution of real-time system health data, maintenance-generated data, as well as, other decision and performance-support information to different types of users.

    To address the challenges that arise in complex information environments providers need to adapt usability-centered methodologies, technologies, and tools that enable utilization of the advantages eMaintenance solutions can give. Since humans make critical maintenance decisions based upon system performance measured by use of available data, it is necessary that the users understand the underlying data correctly in the correct context.

    Subsequently the amount of maintenance data is increasing constantly, thus, human factors issues need to be considered in development of eMaintenance solutions so that performance quality, productivity, and profitability are maintained. In turn this would also reduce situations where too much or incorrect information would decrement the users cognitive capabilities to make good decisions.

    The usability challenges faced by eMaintenance are complex and need to be taken seriously. Hence, the purpose of this paper is to explore eMaintenance design challenges based upon user issues in complex system environments. The results of this paper will present an overview of areas that need to be considered for further research within the field of eMaintenance.

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    FULLTEXT01
  • 9.
    Wandt, Karina
    et al.
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle.
    Karim, Ramin
    Luleå tekniska universitet, Drift, underhåll och akustik.
    Usability aspects of eMaintenance solutions2012In: Proceedings of the 2nd International Workshop & Congress on eMaintenance: Dec 12-14 Luleå, Sweden : eMaintenace: trends in technologies and methodologies, challenges, possibilities and applications / [ed] Ramin Karim; Aditya Parida; Uday Kumar, Luleå: Luleå tekniska universitet , 2012, p. 77-84Conference paper (Refereed)
    Abstract [en]

    As technological development progresses in society, there are several new possibilities to make the maintenance process in industry more efficient. Today, eMaintenance solutions facilitate data management in maintenance activities; data can easily be integrated and shared between sources in heterogeneous environments. This enables systems used in maintenance, such as Computerized Maintenance Management Systems (CMMS), to base decisions on various data, e.g. data produced in other processes. These systems often fulfil the technical requirements (e.g. data consistency control) required to support activities in the maintenance process (e.g. management, support planning, and assessment), but the human interaction with the systems is still essential to the quality of the work performed.

    Since many maintenance activities require manual input of data the interaction between user, e.g. technician, and system, e.g. CMMS, has impact on the quality of the data; in order for the data to be right and relevant, the technician may need supporting directives from the CMMS. Hence, the system usability must be considered when assuring the quality of the manually inputted data. 

    The focus of this paper is to investigate CMMS limitation issues due to usability aspects. Furthermore, the paper discusses the role of context awareness within user interfaces managing data obtained through eMaintenance solutions and presents ideas for future research on context awareness in eMaintenance solutions. Data and conclusions have been conducted through literature studies and case studies within the area.

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    FULLTEXT01
1 - 9 of 9
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