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Energy Modeling of Machine Tools for Optimization of Machine Setups
Indiana University Purdue University Fort Wayne.
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: IEEE Transactions on Automation Science and Engineering, ISSN 1545-5955, E-ISSN 1558-3783, Vol. 9, no 3, p. 607-613Article in journal (Refereed) Published
Abstract [en]

In this paper, a new energy model is developed based on the kinematic and dynamic behaviors of a chosen machine tool. One significant benefit of the developed energy model is their inherited relationship to the design variables involved in the manufacturing processes. Without radical changes of the machine tool’s structure, the proposed model can be readily applied to optimize process parameters to reduce energy consumption. A new parallel kinematic machine Exechon is used as a case study to demonstrate the modeling procedure. The derived energy model is then used for simulation of drilling operations on aircraft components to verify its feasibility. Simulation results indicate that the developed energy model has led to an optimized machine setup which only consumes less than one-third of the energy of an average machine setup over the workspace. This approach can be extended and applied to other machines to establish their energy models for green and sustainable manufacturing.

Place, publisher, year, edition, pages
New York: IEEE Robotics and Automation Society, 2012. Vol. 9, no 3, p. 607-613
Keywords [en]
Dynamics, energy modeling, green manufacturing, kinematics, metrics, optimization, parallel kinematic machine
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-6572DOI: 10.1109/TASE.2012.2195173ISI: 000309841800014Scopus ID: 2-s2.0-84863452951OAI: oai:DiVA.org:his-6572DiVA, id: diva2:562615
Available from: 2012-10-25 Created: 2012-10-25 Last updated: 2023-05-09Bibliographically approved

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Wang, Lihui

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