2016
DOI: 10.1007/978-3-319-27064-7_33
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Decision Making Situations Define Data Requirements in Fleet Asset Management

Abstract: Large amounts of data are increasingly gathered in order to support decision making processes in asset management. The challenge is how best to utilise the large amounts of fragmented and unorganised data sets to benefit decision making, also at fleet level. It is therefore important to be able to utilize and combine all the relevant data, both technical and economic, to create new business knowledge to support effective decision making especially within diverse situations. It is also important to acknowledge … Show more

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Cited by 12 publications
(9 citation statements)
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“…A framework for collaborative SC presented by Gnimpieba et al [9] via using various IT enablers with cloud platform. The internet of things technologies regarding to data acquisition in industrial management of asset presented by Kinnunen et al [10]. The recent trends in smart transportation presented by Singh and Gupta [11].…”
Section: -Enable Process Of Supply Chainmentioning
confidence: 99%
“…A framework for collaborative SC presented by Gnimpieba et al [9] via using various IT enablers with cloud platform. The internet of things technologies regarding to data acquisition in industrial management of asset presented by Kinnunen et al [10]. The recent trends in smart transportation presented by Singh and Gupta [11].…”
Section: -Enable Process Of Supply Chainmentioning
confidence: 99%
“…Gnimpieba et al (2015) used different IT enablers to set a framework for a collaborative supply chain describing data storage and real time event processing with the cloud platform. Kinnunen et al (2016) discussed the IoT technologies related to data acquisition in industrial asset management. Karakostas (2013) suggested a Domain Names Server (DNS) architecture adapted to IoT.…”
Section: It Enablersmentioning
confidence: 99%
“…The amount of data available to maintenance decision makers has increased exponentially due to recent technological developments such as sensors, the Internet of Things and eMaintenance (Baglee et al , 2015; Candell et al , 2009). The decision makers can become overwhelmed by the vast amount of data, and unable to optimally manage the process of gathering, integrating, analyzing and exploiting the data (Kinnunen et al , 2016). This results in wasted resources and suboptimal decision making in maintenance management.…”
Section: Introductionmentioning
confidence: 99%