The value of fleet information: a cost-benefit model

Sini-Kaisu Kinnunen, Salla Marttonen-Arola and Timo Kärri

International Journal of Industrial and Systems Engineering, 2020, vol. 34, issue 3, 321-341

Abstract: Internet of things (IoT) technologies enable the collection of wide-ranging data related to industrial assets which can be used as a support of decision making in asset management, varying from operative maintenance decisions concerning one asset to the management of asset fleets. Technologies and data-refining processes need to be invested in to create knowledge from the massive amounts of data. However, it is not clear that the investments in technologies will pay back, as the data analysis and modelling processes need to be developed as well and the potential benefits must be considerable. This paper contributes to this field by modelling the costs and benefits of IoT investments. As a result, we develop a model that evaluates the value of fleet information in the maintenance context by applying the cost-benefit approach. The costs consist of hardware, software and data processing – related work costs, while the benefits comprise savings in maintenance and quality costs, as well as other savings or increased revenues. Testing the model with a descriptive case demonstrates that the realised cost savings and other benefits need to be considerable for the investment in IoT technologies to be profitable. The results emphasise the importance of data utilisation in decision making in order to gain benefits and to create value from data.

Keywords: fleet; cost-benefit; asset management; investment appraisal; maintenance; life-cycle analysis; Weibull; life-cycle data; cost savings; value of information. (search for similar items in EconPapers)
Date: 2020
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