Automated production data integration for energy-oriented process chain design

Ingo Labbus; Christopher Schmidt; Antal Dér; Christoph Herrmann; Sebastian Thiede

doi:10.1016/j.procir.2018.03.184

Automated production data integration for energy-oriented process chain design

Ingo Labbus^*
, Christopher Schmidt
, Antal Dér
, Christoph Herrmann
, Sebastian Thiede

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › Academic › peer-review

7 Citations (Scopus)

77 Downloads (Pure)

Abstract

Energy efficiency is an important aspect in automotive industry. While energy demand occurs during the operation phase of a production system, it is determined during the planning process. To enable a forecast of energy consumption during process chain design and a demand specific dimensioning of machine components, a modular framework consisting of specialized planning tools and an integrated database is developed. A seamless information flow based on OPC UA and AutomationML connects shop floor and planning environment and ensures data consistency. A database integrates available data sources and condenses acquired raw data to relevant reference data. The concept is prototypically implemented in a crank shaft production line.

Original language	English
Pages (from-to)	551-556
Number of pages	6
Journal	Procedia CIRP
Volume	72
DOIs	https://doi.org/10.1016/j.procir.2018.03.184
Publication status	Published - 1 Jan 2018
Externally published	Yes
Event	51st CIRP Conference on Manufacturing Systems, CIRP CMS 2018 - Stockholm, Sweden Duration: 16 May 2018 → 18 May 2018 Conference number: 51

UN SDGs

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

SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation, and Infrastructure

Keywords

Energy efficiency
Production data acquistion
Production engineering

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10.1016/j.procir.2018.03.184Licence: CC BY-NC-ND

Labbus2018automatedFinal published version, 852 KBLicence: CC BY-NC-ND

Cite this

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title = "Automated production data integration for energy-oriented process chain design",

abstract = "Energy efficiency is an important aspect in automotive industry. While energy demand occurs during the operation phase of a production system, it is determined during the planning process. To enable a forecast of energy consumption during process chain design and a demand specific dimensioning of machine components, a modular framework consisting of specialized planning tools and an integrated database is developed. A seamless information flow based on OPC UA and AutomationML connects shop floor and planning environment and ensures data consistency. A database integrates available data sources and condenses acquired raw data to relevant reference data. The concept is prototypically implemented in a crank shaft production line.",

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doi = "10.1016/j.procir.2018.03.184",

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T1 - Automated production data integration for energy-oriented process chain design

AU - Labbus, Ingo

AU - Schmidt, Christopher

AU - Dér, Antal

AU - Herrmann, Christoph

AU - Thiede, Sebastian

N1 - Conference code: 51

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Energy efficiency is an important aspect in automotive industry. While energy demand occurs during the operation phase of a production system, it is determined during the planning process. To enable a forecast of energy consumption during process chain design and a demand specific dimensioning of machine components, a modular framework consisting of specialized planning tools and an integrated database is developed. A seamless information flow based on OPC UA and AutomationML connects shop floor and planning environment and ensures data consistency. A database integrates available data sources and condenses acquired raw data to relevant reference data. The concept is prototypically implemented in a crank shaft production line.

AB - Energy efficiency is an important aspect in automotive industry. While energy demand occurs during the operation phase of a production system, it is determined during the planning process. To enable a forecast of energy consumption during process chain design and a demand specific dimensioning of machine components, a modular framework consisting of specialized planning tools and an integrated database is developed. A seamless information flow based on OPC UA and AutomationML connects shop floor and planning environment and ensures data consistency. A database integrates available data sources and condenses acquired raw data to relevant reference data. The concept is prototypically implemented in a crank shaft production line.

KW - Energy efficiency

KW - Production data acquistion

KW - Production engineering

UR - https://www.scopus.com/pages/publications/85049595273

U2 - 10.1016/j.procir.2018.03.184

DO - 10.1016/j.procir.2018.03.184

M3 - Conference article

AN - SCOPUS:85049595273

SN - 2212-8271

VL - 72

SP - 551

EP - 556

JO - Procedia CIRP

JF - Procedia CIRP

T2 - 51st CIRP Conference on Manufacturing Systems, CIRP CMS 2018

Y2 - 16 May 2018 through 18 May 2018

ER -

Automated production data integration for energy-oriented process chain design

Abstract

UN SDGs

Keywords

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