Decision Making Situations Define Data Requirements in Fleet Asset Management

Part of book or chapter of book English OPEN
Kinnunen, Sini ; Marttonen-Arola, Salla ; Yla-Kujala, Antti ; Karri, Timo ; Ahonen, Toni ; Valkokari, Pasi ; Baglee, David (2016)

Large amounts of data are increasingly gathered in order to support de-cision making processes in asset management. The challenge is how best to utilise the large amounts of fragmented and unorganised data sets to benefit decision mak-ing, 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 that different types of data are required in different deci-sion making context. A review of the literature has shown that decision making situations are usually categorized according to the decision making levels, namely strategic, tactical and operational. In addition, they can be classified according to the amount of time used in decision making. For example, two situations can be compared: 1) optimization decision where a large amount of time and consideration is used to determine an optimum solution, and 2) decisions that need to be made instantly. Fleet management of industrial assets suffers from a lack of asset man-agement strategies in order to ensure the correct data is collected, analysed and used to inform critical business decisions with regard to fleet management. In this paper we categorize the decision making process within certain situation and propose a new framework to identify fleet decision making situations.
  • References (14)
    14 references, page 1 of 2

    Andersen, J., Crainic, T.G., and Christiansen, M. (2012) “Service network design with management and coordination of multiple fleets”, European Journal of Operational Research, Vol. 193, No. 2, pp. 377-389.

    Antuñano M.S. and Dessureault, S.D. (2011) “Development of a real-time fleet cost tool as part of an integrated remote mine control centre”, Proceedings of 35th APCOM Symposium - Application of Computers and Operations Research in the Minerals Industry, pp. 789-793.

    Davenport, T.H. and Harris, J.G. (2005) “Automated Decision Making Comes of Age”, MIT Sloan Management Review, Vol. 46, No. 4 pp. 83-89.

    Hounsell, N.B., Shrestha, B.P., and Wong, A. (2012) “Data management and applications in a world-leading bus fleet”, Transportation Research Part C: Emerging Technologies, Vol. 22, pp. 76-87.

    Knowles, M and Baglee D. (2015) “Ultra Low Carbon Vehicle Management based on telematic monitoring”, Through Life Engineering Services, Ch. 16, pp. 83-94.

    Mishra, S., Sharma, S., Khasnabis, S., and Mathew, T.V. (2013) “Preserving an aging transit fleet: An optimal resource allocation perspective based on service life and constrained budget”, Transportation Research Part A: Policy and Practice, Vol. 47, pp. 111-123.

    Ngai, E.W.T., Leung, T.K.P., Wong, Y.H., Lee, M.C.M., Chai, P.Y.F., and Choi, Y.S. (2012) “Design and development of a context-aware decision support system for real-time accident handling in logistics”, Decision Support Systems, Vol. 52, No. 4, pp. 816-827.

    Porter, M.E. and Heppelmann, J.E. (2014) “How Smart, Connected Products Are Transforming Competition”, Harvard Business Review, Vol. 92, No. 11 pp. 64-88.

    Richardson, S., Kefford, A., and Hodkiewicz, M. (2013) “Optimised asset replacement strategy in the presence of lead time uncertainty”, International Journal of Production Economics, Vol. 141, No. 2, pp. 659-667.

    Sardar, G., Ramachandran, N., and Gopinath, R. (2006) “Challenges in Achieving Optimal Asset Performance Based on Total Cost of Ownership”, Proceedings of the 1st World Congress on Engineering Asset Management, pp. 54-63.

  • Metrics
    views in OpenAIRE
    views in local repository
    downloads in local repository

    The information is available from the following content providers:

    From Number Of Views Number Of Downloads
    Sunderland University Institutional Repository - IRUS-UK 0 25
Share - Bookmark