
Open access
Date
2015Type
- Conference Paper
Citations
Cited 22 times in
Web of Science
Cited 26 times in
Scopus
ETH Bibliography
yes
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Abstract
Resource consumption measurement, analysis, and improvement in the context of sustainability in manufacturing reveal extensive fields of research and have become important in order to fulfil multiple requirements in ecological, economic and legislative activities. Solutions for energy consumption measurement in manufacturing are known but rarely implemented due to several reasons such as high costs, implementation complexity or unknown information. Despite the availability of several standards and guidelines towards environmental performance evaluation and optimization as well as punctual energy measurements for production systems, a user-oriented monitoring system to gather the relevant data in an efficient way has not been formulated yet.
The following paper introduces a condign monitoring strategy and architecture that fills this gap and fulfils the requirements of accuracy within an acceptable cost-to-information ratio. A combination of internal sensors, external sensors and simulation provides comprehensive information of the monitored manufacturing system according to ISO 14955 and ISO 50001 standards. The implementation is verified within an industrial case study and meets the industrial needs in line with the current legislation. Further, the revealed information enables users to apply micro and macro-optimization activities. Show more
Permanent link
https://doi.org/10.3929/ethz-a-010279101Publication status
publishedExternal links
Book title
12th Global Conference on Sustainable Manufacturing – Emerging PotentialsJournal / series
Procedia CIRPVolume
Pages / Article No.
Publisher
ElsevierEvent
Subject
Energy consumption; Machine tool measurement; Energy efficiency in manufacturing; OptimizationOrganisational unit
03641 - Wegener, Konrad / Wegener, Konrad
02623 - Inst. f. Werkzeugmaschinen und Fertigung / Inst. Machine Tools and Manufacturing
Related publications and datasets
Is cited by: https://doi.org/10.3929/ethz-b-000438683
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Show all metadata
Citations
Cited 22 times in
Web of Science
Cited 26 times in
Scopus
ETH Bibliography
yes
Altmetrics