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Remote services are services enabled by information and communication components and therefore do not require the physical presence of a service technician at the service object to provide a task. The impact of remote service on the capital goods industry has been increasingly significant over the recent yeas. Still many companies struggle with developing and implemenling successful business model, for remote service. This leads to a lot of unaccomplished benefits for the customer as well as for the companies themselves. A survey throughout companies in Ihe industrial machine and plant production sector was conducted in order to determine what successful companies do differently from those that cannot efficiently implement remote service business models.
The study presented in this chapter identifies key suceess factors of companies that effectively implemented remote services for their products. In order to identify the successful companies a scale for measuring remote service success was developed. Only by the use of this scale further findings regarding the success factors were possible. Key findings include the fact that successful companies actively market their remotle service to their customers. Generally they try to approach their remote service business from the operating company's perspective.
Assets of integrated production systems, especially in the heavy industry, are facing high requirements in terms of reliability and availability. In case of component breakdown, the operating firm is confronted with high costs due to downtime and loss of production. Modern maintenance concepts in combination with advanced technologies can help to improve the plant availability and reduce the downtime costs caused by unplanned breakdowns. Against this background, the research institutes FIR and IMR from RWTH Aachen University, Germany, are collaborating within the research project “SiZu”. This project deals with the integration of condition monitoring system and real time simulation to assess the condition of components and to support failure cause analysis.