Power-level sampling of metal cutting machines for data representation in discrete event simulationShow others and affiliations
2014 (English)In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 53, no 23, p. 7060-7070Article in journal (Refereed) Published
Abstract [en]
An extension to the application area for discrete event simulation (DES) has been ongoing since the last decade and focused only on economic aspects to include ecologic sustainability. With this new focus, additional input parameters, such as electrical power consumption of machines, are needed. This paper aim at investigating how NC machine power consumption should be represented in simulation models of factories. The study includes data-sets from three different factories. One factory producing truck engine blocks, one producing brake disc parts for cars and one producing forklift components. The total number of data points analysed are more than 2,45,000, where of over 1,11,000 on busy state for 11 NC machines. The low variability between busy cycles indicates that statistical representations are not adding significant variability. Furthermore, results show that non-value-added activities cause a substantial amount of the total energy consumption, which can be reduced by optimising the production flow using dynamic simulations such as DES.
Place, publisher, year, edition, pages
Taylor & Francis Group, 2014. Vol. 53, no 23, p. 7060-7070
Keywords [en]
sustainable manufacturing, production flow analysis, simulation, data mining, discrete event simulation, energy modelling, power-level sampling
National Category
Production Engineering, Human Work Science and Ergonomics Energy Systems Environmental Management
Identifiers
URN: urn:nbn:se:his:diva-24329DOI: 10.1080/00207543.2014.980456ISI: 000367046100008Scopus ID: 2-s2.0-84914145184OAI: oai:DiVA.org:his-24329DiVA, id: diva2:1883457
Funder
Vinnova
Note
This is an Open Access article. Non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly attributed, cited, and is not altered,transformed, or built upon in any way, is permitted. The moral rights of the named authors have been asserted.
This work has been performed within the Sustainable Production Initiative and the Production Area of Advance at Chalmers. The support is gratefully acknowledged. The authors would also like to thank Vesa Rosvall, the Electrical Engineer performing the power measurements. Finally, Edward Williams (University of Michigan and PMC, Dearborn, Michigan, USA) has kindly provided valuable suggestions for enhancing the presentation of this paper.
The funding for this research is granted by VINNOVA (Swedish Governmental Agency for Innovation Systems).
2024-07-102024-07-102025-02-10Bibliographically approved