Abstract
Automotive companies tend to apply modular approaches in their product development processes in order to save costs and meet increasingly diversified customer demands. In largely decentralized environments with cross-branded development projects over multiple departments in different sites this modular approach leads to very complex and large data structures. Maintaining consistency and transparency, as well as coordinating information flows in such an environment is a major task which is often accomplished manually. Based on a real world case study, this paper analyzes a key development process: the connection of geometric (geometries) and logistical data (parts). During this time consuming process information carriers (geometries and parts) with independent lifecycles that are maintained by different stakeholders (designer and purchaser) of different departments (and in this scenario even within multiple brands) are linked as these carriers themselves are mutually dependent. This paper then proceeds to model five agent-based architecture variants to support this process. In addition, an algorithm to map geometric and logistical data which aims to relieve the actors involved (regarding the organizational overhead) is outlined.The paper concludes with a comparison of the different agent architecture variants and emphasizes the most promising variants to partly automate the connection of geometric and logistical data.
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Notes
- 1.
It should be noted that the function property is optional as not every component fulfills a specific function. For example, a simple screw that is used a few hundred times across different locations within a vehicle. It does to some extend contribute to several functions but cannot be connected to one specific function.
- 2.
Depending on the architecture variant this could be the Extended Component, Extended Context or (Extended) Usage Agent.
- 3.
It should be noted that the whole communication part does not apply to Architecture Variant IV because there is only one agent (the Extended Context Agent) which handles the mapping negotiations internally.
- 4.
Engineers and Purchasers.
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Bender, J., Kehl, S., Müller, J.P. (2015). A Comparison of Agent-Based Coordination Architecture Variants for Automotive Product Change Management. In: Müller, J., Ketter, W., Kaminka, G., Wagner, G., Bulling, N. (eds) Multiagent System Technologies . MATES 2015. Lecture Notes in Computer Science(), vol 9433. Springer, Cham. https://doi.org/10.1007/978-3-319-27343-3_14
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