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Optimization of machining processes from the perspective of energy consumption: A case study
Department of Engineering, Indiana University Purdue University Fort Wayne, IN, USA.
University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.ORCID iD: 0000-0001-8679-8049
2012 (English)In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 31, no 4, p. 420-428Article in journal (Refereed) Published
Abstract [en]

One of the primary objectives of sustainable manufacturing is to minimize energy consumption in its manufacturing processes. A strategy of energy saving is to adapt new materials or new processes; but its implementation requires radical changes of the manufacturing system and usually a heavy initial investment. The other strategy is to optimize existing manufacturing processes from the perspective of energy saving. However, an explicit relational model between machining parameters and energy cost is required; while most of the works in this field treat the manufacturing processes as black or gray boxes. In this paper, analytical energy modeling for the explicit relations of machining parameters and energy consumption is investigated, and the modeling method is based on the kinematic and dynamic behaviors of chosen machine tools. The developed model is applied to optimize the  machine setup for energy saving. A new parallel kinematic machine Exechon is used to demonstrate the procedure of energy modeling. The simulation results indicate that the optimization can result in 67% energy saving for the specific drilling operation of the given machine tool. This approach can be extended and applied to other machines to establish their energy models for sustainable manufacturing.

Place, publisher, year, edition, pages
Elsevier, 2012. Vol. 31, no 4, p. 420-428
Keywords [en]
Energy modeling, Computer aided processing planning, Computer aided manufacturing, Sustainable manufacturing
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-7152DOI: 10.1016/j.jmsy.2012.07.002ISI: 000312355200007Scopus ID: 2-s2.0-84868696619OAI: oai:DiVA.org:his-7152DiVA, id: diva2:604215
Available from: 2013-02-08 Created: 2013-02-07 Last updated: 2023-05-12Bibliographically approved

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Wang, Lihui

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  • apa
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  • de-DE
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  • nn-NB
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  • Other locale
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