Abstract

Exabytes of data from various sources are available for maintenance decision makers. The yearly increase in data is exponential due to technological developments such as the rapid increase in the amount of interconnected systems and assets, which utilize smart sensors, cloud-based computing and eMaintenance. All of these are supported by the rapid developments in the Internet. The data provide vast possibilities for smart, autonomous assets and predictive maintenance. However, in practice, there are technical, managerial, and organizational challenges, which impede the maintenance decision makers from exploiting the information retrieved from the data analyses. The existing literature has discussed the data required in different maintenance decision making situations extensively, although there is a limited number of academic publications which explore general-level frameworks or tools to support the management of maintenance data. This paper builds upon a review of the current literature on the value of maintenance data management. The data needed to support a number of different maintenance management situations are discussed, and an approach to analyze and increase the value and resource efficiency of the maintenance data management process is suggested. The paper presents a case study example conducted in collaboration with a UK manufacturing industry. The objective of the paper is to map the current state of maintenance data exploitation paths. This makes the different value-based development needs in the data management process visible. The results of this paper will contribute to future empirical research including modelling and optimizing the use of data in maintenance decision making through adopting lean management principles. The majority of previous lean management research has focused on the optimal management of production processes and the maintenance processes. In this research, the principles of lean management will be taken to the level of optimizing the maintenance data management process.