Abstract
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.
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Notes
- 1.
We focus on wearing parts as a subcategory of spare parts, because only for wearing parts are all the described objectives fulfilled. The system is of course also applicable for nonwearing spare parts; thus, we use the term “wearing parts” only for applications not applicable for spare parts in general.
- 2.
ECU: Electronic Control Unit.
- 3.
Condition-Based Service (CBS) is a system in BMW series cars that calculates service intervals based on the usage (and thus the condition) of wearing parts; e.g., based on tire rotation and the braking pressure of each braking action, the abrasion of the brake pads is calculated.
- 4.
Sometimes several parts are in one box; e.g., for brake pads there are different serial numbers for the parts of one set of brake pads, which is referred to as the product.
- 5.
In series models today, a push-button in the instrument cluster is used to select a part of the CBS and re-initialize it to the standard value; e.g., brake pads are re-initialized to 50,000 km.
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W. Wahlster (ed.), SemProM—Foundations of Semantic Product Memories for the Internet of Things. Cognitive Technologies (Springer, Berlin, 2013b)
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Neidig, J., Preißinger, J. (2013). A SemProM Use Case: Maintenance of Factory and Automotive Components. In: Wahlster, W. (eds) SemProM. Cognitive Technologies. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37377-0_22
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