eMaintenance—Information logistics for maintenance support

Candell, Olov; Karim, Ramin; Söderholm, Peter

doi:10.1016/j.rcim.2009.04.005

Cited by 110 publications

(64 citation statements)

References 13 publications

(20 reference statements)

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“…When scoping down on research papers focussing on the aircraft maintenance domain the contribution is limited. The main problem of aircraft (legacy) maintenance documentation is that the majority is either paper based or a 'paper-onscreen' solution (e.g., Portable Document Format (PDF)), which prevents information from being readily available at the right time and place (Candell and Karim, 2008). To provide the right information to the right user at the right time and place, both content and technology to supply information to the user should be considered (Candell, 2004).…”

Section: Research and Industry Solutionsmentioning

confidence: 99%

Contextualising aircraft maintenance documentation

Koornneef

Verhagen

Curran

2017

IJASM

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Biographical notes: Hemmo Koornneef obtained his MSc at the Delft University of Technology and currently works there on obtaining his PhD at the section of Air Transport and Operations. His research focuses on aircraft maintenance operations, in particular improving efficiency of line maintenance operations by developing knowledge-based (mobile) tools to aid technicians in task execution and decision making. AbstractThe use of documentation for task support in aircraft line maintenance is still mostly paperbased, which is slow, burdensome and prone to error. This paper provides an overview of the issues associated with the use of paper-based documentation in aircraft maintenance and describes the development of a novel concept for contextualized documentation to address these issues. The developed system features ontology-based data access (OBDA) for improved contextualization and additional flexibility for future integration of other data sources. The ontology is developed in Protégé. The maintenance documents are accessed through the FileTable feature of Microsoft's SQL Server and is linked to the ontology using Ontop. By inferencing the aircraft manufacturer and family are derived from the registration mark and used as attributes for a Boolean search in the maintenance documentation database.The OBDA system is able to retrieve relevant documents approximately twice as fast as existing relational database systems and provides support for a wide variety of file types. Limitations of the developed system are software vendor dependency, compatibility issues between integrated software solutions and lack of support for automatic mappings. Nevertheless, the developed system provides a proof of concept for a mobile tool to overcome the weaknesses of maintenance documentation in line maintenance, working towards increased operational efficiency, reduction of human factor induced maintenance errors and reduced paper consumption.

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Section: Research and Industry Solutionsmentioning

confidence: 99%

Contextualising aircraft maintenance documentation

Koornneef

Verhagen

Curran

2017

IJASM

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“…Extensive application of ICT and other emerging technologies facilitate easy and effective collection of data and information (Parida, 2006;Candell et al, 2009). In maintenance, enhanced use of ICT facilitates the development of artefacts (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…The knowledge discovery, which is an essentially a major aspect for maintenance decision support; is usually done by discovering special pattern of data, i.e. by clustering together data that share certain common properties (Wang, 1997).Extensive application of ICT and other emerging technologies facilitate easy and effective collection of data and information (Parida, 2006;Candell et al, 2009). In maintenance, enhanced use of ICT facilitates the development of artefacts (e.g.…”

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confidence: 99%

Maintenance Analytics – The New Know in Maintenance

Karim

Westerberg²,

Galar

et al. 2016

IFAC-PapersOnLine

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Decision-making in maintenance has to be augmented to instantly understand and efficiently act, i.e. the new know. The new know in maintenance needs to focus on two aspects of knowing: 1) what can be known and 2) what must be known, in order to enable the maintenance decision-makers to take appropriate actions.Hence, the purpose of this paper is to propose a concept for knowledge discovery in maintenance with focus on Big Data and analytics. The concept is called Maintenance Analytics (MA). MA focuses in the new knowledge discovery in maintenance. MA addresses the process of discovery, understanding, and communication of maintenance data from four time-related perspectives, i.e. 1) "Maintenance Descriptive Analytics (monitoring)"; 2) "Maintenance Diagnostic Analytics"; 3) "Maintenance Predictive Analytics"; and 4) "Maintenance Prescriptive analytics".Keywords: big data, maintenance analytics, eMaintenance, Knowledge discovery, maintenance decision support. INTRODUCTIONThe dynamic global and local business scenarios put new demands on the decision-making processes in an organisation.The new decision-making processes need to provide enhanced capability for knowledge discovery online and in real-time. To increase the overall business efficiency, organisations need to implement a knowledge discovery platform in their core processes such as business, operation, and maintenance. Knowledge discovery is depended on availability if accurate and consistence data and information.Today, enterprises are overwhelmed by managing data and its logistics. It can be testified that there is a growing gap between data generation and data understanding (Witten et. al, 2011). It can be considered that decisions are also becoming more complex with greater uncertainty, increasing time pressure, more rapidly changing conditions, and higher stakes (Busemeyer & Pleskac, 2009). The increased information needs and the development of Information and Communication Technology (ICT) have added velocity to everything that is done within an organization through transforming the business process into eBusiness (Lee, 2003). The knowledge discovery, which is an essentially a major aspect for maintenance decision support; is usually done by discovering special pattern of data, i.e. by clustering together data that share certain common properties (Wang, 1997).Extensive application of ICT and other emerging technologies facilitate easy and effective collection of data and information (Parida, 2006;Candell et al., 2009). In maintenance, enhanced use of ICT facilitates the development of artefacts (e.g. frameworks, tools, methodologies and technologies); which aim to support maintenance decision-making. These artefacts also enable improvement of different maintenance approaches, such as; preventive maintenance and corrective maintenance. Furthermore, ICT provide additional capabilities, which can be used within diagnostic and prognostic processes. The prognostic and diagnostic processes in an enterprise can be facilitated through provision of pr...

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“…They collectively develop , use (Faleg and Giovannini, 2012), and maintain assets based on innovative expertise and IT (e.g. prognostics) (Candell et al, 2009). Horizontal relationships (between asset users) interrelate with vertical upstream relationships (Bloch, 2013).…”

Section: For Instance Us Army Materiel Command and Us Marine Corps Lomentioning

confidence: 99%

“…Organizations may have to standardize their operations, product data, and technical infrastructures in order to share information (Candell et al, 2009;Lia et al, 2006) (Gebauer et al, 2011), especially in case ISS is located in developing countries (Dahan et al, 2010) or concerns offshore/off-road or mobile serviscapes.…”

Section: Nested Structures: Strategy Governance and Operationsmentioning

confidence: 99%

Alliance strategy: context, process, and requirements

Keers

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eMaintenance—Information logistics for maintenance support

Cited by 110 publications

References 13 publications

Contextualising aircraft maintenance documentation

Contextualising aircraft maintenance documentation

Maintenance Analytics – The New Know in Maintenance

Alliance strategy: context, process, and requirements

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