Das Ziel Digital Enterprise: die professionelle digitale Abbildung von Produktentwicklung und Produktion

Huber, Anton S.

doi:10.1007/978-3-642-36917-9_7

Cited by 4 publications

(3 citation statements)

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“…In 2005, Eigner et al pointed out the topic of connecting different product structures (Eigner and Stelzer, 2009, p. 79). More recently, in (Huber and Sendler, 2013) Huber states that connections between product data at different phases of PLM are still not complete and managed (if at all) via heterogeneous interfaces. The process of publishing product data changes through these often interferes with data consistency during the PDP, because the interfaces are mostly constructed only for one specific transformation (Huber and Sendler, 2013).…”

Section: Transforming Product Structurementioning

confidence: 99%

“…More recently, in (Huber and Sendler, 2013) Huber states that connections between product data at different phases of PLM are still not complete and managed (if at all) via heterogeneous interfaces. The process of publishing product data changes through these often interferes with data consistency during the PDP, because the interfaces are mostly constructed only for one specific transformation (Huber and Sendler, 2013). In (Adolphy et al, 2015), the authors observe that existing processes for creating and transforming product structures are highly manual and error-prone.…”

Section: Transforming Product Structurementioning

confidence: 99%

“…The necessity of having different views on the product data within the PDP has been stated by (Adolphy et al, 2015;Culler and Anderson, 2016;Kehl et al, 2016). In addition, integrating different product structures along the PDP is essential for a consistent development of products (Huber and Sendler, 2013;Eigner et al, 2005). The previously explored classification approaches and industrial practice (see Section 2) show that researching classification to fulfil the use cases described above is promising.…”

Section: Research Gapmentioning

confidence: 99%

See 2 more Smart Citations

Towards Automated Classification of Product Data Based on Machine Learning

Schleibaum

Kehl

Stiefel

et al. 2020

Proc. Des. Soc.: Des. Conf.

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Modern machine learning methods have the potential to supply industrial product lifecycle management (PLM) with automated classification of product components. However, there is only little work in the literature on this topic. We propose to apply supervised machine learning on component meta-data. By analysing an industrial case study, we identify requirements and opportunities for automating classification, e.g. in part numbers and product structures. We validate our novel approach through a classification experiment comparing four machine learning methods on a realistic component dataset.

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Section: Transforming Product Structurementioning

confidence: 99%