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Towards a Methodology to Determine Intersubjective Data Values in Industrial Business Activities
(2021)
This paper contributes to a valuation framework for valuing data as an intangible asset. Especially those industrial manufacturers developing and delivering holistic digital solutions are limited in calculating the true business value of data initiatives. Since the value of data is strongly dependent on the respective use case, a completely objective valuation is not possible. This complicates decision-making on the internal side regarding investments in digital transformation, and on the external side to communicate existing benefits to third parties via financial reporting. Therefore, the target is to design a valuation framework that allows industrial manufacturers to determine an intersubjective, i.e., traceable and transparent, data value. In order to develop a framework that can be applied in practice, the approach is based on industrial case study research.
Industry 4.0 and Smart Maintenance represent a great opportunity to make manufacturing and maintenance more effective, safer, and reliable. However, they also represent massive change and corresponding challenges for industrial companies, as many different options and starting points have to be weighed and the individual right paths for achieving Smart Maintenance need to be identified. In our paper, we describe our approach to evaluating maintenance organizations in a case study for the oil and gas industry, developing a shared vision for the future, and deriving economical and effective measures. We will demonstrate our approach, by showcasing a specific example from the oil and gas industry, where a need for action on HSE-relevant critical flanges in the company's piping systems was identified. We describe the steps, that were taken to identify the need for action, the specifications of the project and the criticality analysis of the piping system. This resulted in the derivation of a digitalization measure for critical flanges, which was first commercially analyzed and then the flanges were equipped with a continuous monitoring solution. Finally, a conclusion is drawn on the performed procedure and the achieved improvements.
Electricity generated by wind turbines (WT) is a mainstay of the transition to renewable energy. In order to economically utilize WT is, operating and maintenance costs, which account for 25% of total electricity generation costs in onshore WT’s, are a focus of cost reduction activities. Implementing a data-driven prescriptive maintenance approach is one way to achieve this. So far, various approaches for prescriptive maintenance for onshore WT’s have been suggested.
However, little research has addressed the practical implementation considering sociotechnical aspects. The aim of this paper is therefore to identify success factors for the successful implementation of such a maintenance strategy with clear and holistic guidance on how existing knowledge on prescriptive maintenance from science can be transferred to business practice. These recommendations are developed through case study research and classified in the four structural areas of Acatech’s Industry 4.0 Maturity Index: Resources, Information Systems, Organizational Structure and Culture.