Konfiguration logistischer Netzwerk

Stich, Volker; Quick, Jerome; Cuber, Stefan

doi:10.1007/978-3-642-28992-7_2

Cited by 4 publications

(2 citation statements)

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“…In the literature, this problem is known as a Constraint Satisfaction Problem [17]. For a further understanding of the product encryption and development implications see Herlyn, Stich, Zagel, Holtze and Frischen et al [1][2][3][4][5]. For a further study into the challenges of product personalization based on modular product families see Kuhl et al [18].…”

Section: Automobile Industrymentioning

confidence: 99%

“…This paper deals with variant management in the automotive industry. The product development process, in particular in the German automotive industry, is characterized by the challenges of the highly variant products and the resulting requirements [1][2][3][4][5]. In the early phase, assumptions, estimates and historical data from direct predecessor vehicles are used for planning.…”

Section: Introductionmentioning

confidence: 99%

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Recommender Systems for Variant Management in the Automotive Industry

Schmidt¹

2022

DS 119: Proceedings of the 33rd Symposium Design for X (DFX2022)

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This paper transfers some state-of-the-art methods of recommender systems for an application in the product development process of variant rich products in the automotive industry. Therefore, an introduction into the characteristics of the rule-based description of variant-rich products is given, followed by a presentation of three selected recommendation approaches, namely Collaborative Filtering, Association Rule Mining and Bayesian Networks. The presented approaches are then evaluated against the background of the variant-rich product configuration. Advantages and disadvantages of the methods in regard of this special use-case are highlighted and possible applications and limitations are discussed. In conclusion, further research needs for future implementation are identified.

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Section: Automobile Industrymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%