Customers are demanding a guaranteed availability of machine components in capital goods industry. However, manufacturers are not willing to guarantee the demanded availability due to increasing costs based on high risks and uncertainties resulting from missing operational data, insufficient transparency of the machine condition as well as missing information of the customer behaviour. In this paper, a strategy to enable the development of availabilityoriented Product-Service Systems (PSS) is presented. This strategy is based on condition monitoring and lifetime model development for service-relevant components. Therefore, a use case focusing on the agricultural industry is regarded. The key tasks of this strategy are to identify service-relevant parts and to determine failure mechanisms of these parts. Based on this, a wear model and a service life model of the conveyor belt of a potato harvester are developed. In order to implement the predictive maintenance approach, intelligent components will be developed. This paper presents the steps necessary to develop intelligent, servicerelevant components for industry 4.0 applications. The requirements of customers, operators, machine manufacturers and technology are summarized. The procedure for the development of the components, identification of the service-relevant components, investigation of the failure mechanisms, definition of measurable physical quantities, creation of monitoring concepts and testing of the monitoring concepts will be presented exemplarily. A potato harvester is used as a specific use case.
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