Automated Environmental Impact Assessment (EIA) via Asset Administration Shell

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Automated Environmental Impact Assessment (EIA) via Asset Administration Shell

Al Assadi, Anwar / Waltersmann, Lara / Miehe, Robert / Fechter, Manuel / Sauer, Alexander

Due to growing public awareness and rising requirements of legislation and customers’ expectations in the field of sustainability, it is increasingly important for enterprises to assess and subsequently reduce their environmental impact. However, the acquisition of environmental data in enterprises still causes considerable effort, due to the necessary manual acquisition.

A unified asset administration shell (AAS) potentially provides data transparency and environmental data interoperability along the value chain and thus a more detailed (real-time capable) accounting of the environmental impact of products and services. Hence, this paper presents an approach for an automated environmental impact assessments (EIA) of products and production sites.Thereby, a first application of the AAS in the context of automated EIAs was implemented at the ARENA2036 research factory. The AAS automatically collects energy and emission data throughout a production process and thus allows the allocation of actual emissions to product and equipment (environmental wallet). The results reveal a first starting point for automated EIA, facilitating individual EIAs to address increasing product variety.

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Document information

Title :

Automated Environmental Impact Assessment (EIA) via Asset Administration Shell

Additional title:

ARENA2036

Contributors:

Weißgraeber, Philipp (editor) / Heieck, Frieder (editor) / Ackermann, Clemens (editor) / Al Assadi, Anwar (author) / Waltersmann, Lara (author) / Miehe, Robert (author) / Fechter, Manuel (author) / Sauer, Alexander (author)

Published in:

Advances in Automotive Production Technology – Theory and Application ; Chapter : 6 ; 45-52

ARENA2036

Publication date :

2021-06-02

Size :

8 pages

ISBN :

978-3-662-62962-8 , 978-3-662-62961-1

ISSN :

2524-7255 , 2524-7247

DOI :