GreenCC: A Hybrid Approach to Sustainably Validate Manufacturing Data in Industry 4.0 Environments.

Simon Paasche; Sven Groppe

doi:10.5220/0012147900003541

GreenCC: A Hybrid Approach to Sustainably Validate Manufacturing Data in Industry 4.0 Environments.

Original language	English
Title of host publication	DATA
Number of pages	8
Publication date	2023
Pages	621-628
DOIs	https://doi.org/10.5220/0012147900003541
Publication status	Published - 2023

Research Areas and Centers

Centers: Center for Artificial Intelligence Luebeck (ZKIL)
Research Area: Intelligent Systems

DFG Research Classification Scheme

409-06 Information Systems, Process and Knowledge Management

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.5220/0012147900003541

Cite this

@inproceedings{667801c9ebc94513bfa1b187479e4717,

title = "GreenCC: A Hybrid Approach to Sustainably Validate Manufacturing Data in Industry 4.0 Environments.",

author = "Simon Paasche and Sven Groppe",

note = "DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.",

year = "2023",

doi = "10.5220/0012147900003541",

language = "English",

pages = "621--628",

booktitle = "DATA",

}

TY - GEN

T1 - GreenCC: A Hybrid Approach to Sustainably Validate Manufacturing Data in Industry 4.0 Environments.

AU - Paasche, Simon

AU - Groppe, Sven

N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2023

Y1 - 2023

UR - https://www.mendeley.com/catalogue/dfa58f0b-33b7-383d-8b54-d36ceefa47c7/

U2 - 10.5220/0012147900003541

DO - 10.5220/0012147900003541

M3 - Conference contribution

SP - 621

EP - 628

BT - DATA

ER -

GreenCC: A Hybrid Approach to Sustainably Validate Manufacturing Data in Industry 4.0 Environments.

Research Areas and Centers

DFG Research Classification Scheme

UN SDGs

Access to Document

Other files and links

Cite this