A SemProM Use Case: Maintenance of Factory and Automotive Components
Maintenance is essential to guarantee the availability of any technical equipment, but is the dominant cost factor during the equipment’s operating phase. In this chapter it is shown how Digital Product Memories (DPMs) can be used to optimize different ma
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bstract Maintenance is essential to guarantee the availability of any technical equipment, but is the dominant cost factor during the equipment’s operating phase. In this chapter it is shown how Digital Product Memories (DPMs) can be used to optimize different maintenance tasks. Therefore, the analysis is focused on the requirements of two domains: industrial manufacturing and automobiles.
1 Introduction The required availability of machines, plants, automobiles, or any other technical equipment can only be guaranteed if sufficient maintenance is performed. This is essential for the longevity of any technical product. Therefore, maintenance is one of the industrial branches with the largest trade volume worldwide. On the other hand, users aim to minimize maintenance costs. The potential for high profits in this area attracts illegal practices such as counterfeiting of spare parts. Digital Product Memories (DPMs) show great potential for optimizing the respective tasks, for example, by supplying necessary information and preventing malpractice (Wahlster 2013a).
2 Related Work RFID-based maintenance is a field of application of growing importance, and the number of such installations is rising fast. Several pilot projects have shown that, in general, return on investment can be reached within 2–3 years (RFID im Blick 2011; Bartneck et al. 2008; RFID Journal Blog 2008). Nevertheless, so far no standardized approach for implementations is known. Typically, such installations are designed J. Neidig (B) Siemens AG, Sector Industry, Nuremberg, Germany e-mail: [email protected] J. Preißinger BMW Research and Technology, Munich, Germany e-mail: [email protected] W. Wahlster (ed.), SemProM, Cognitive Technologies, DOI 10.1007/978-3-642-37377-0_22, © Springer-Verlag Berlin Heidelberg 2013
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from scratch specifically for the needs of the given task. This includes proprietary software applications, data models, and hardware (Bandow and Martin 2010). Digital product memories have the potential to unify the different approaches, resulting in more cost-efficient implementations. Several approaches to detect counterfeit parts exist, of which a large number are based on optical properties, such as holograms, flip colors or microprinting. The problem with these approaches is, in general, that on the one hand the optical properties themselves can be imitated more and more easily while on the other hand the consumer needs more and more knowledge and time to identify fake products. RFID-based solutions provide advantages over optical approaches, as discussed in detail in Staake and Fleisch (2008). An overview of different RFID-based approaches and the cryptographic systems used for protection against counterfeit products can also be found in Cole and Ranasinghe (2007). Many approaches try to detect counterfeit products before they reach the customer (e.g., at the customs control or at the retailer), because the customer has no technical equipment or no appropriate knowledge to identif
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