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CNR ExploRA
Article . 2016
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The International Journal of Advanced Manufacturing Technology
Article . 2016 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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A simulation approach for predicting energy use during general milling operations

Authors: BORGIA, STEFANO; ALBERTELLI, PAOLO; BIANCHI, GIACOMO DAVIDE;

A simulation approach for predicting energy use during general milling operations

Abstract

Manufacturing processes have a high impact on global energy consumption. Machine tool's environmental impact is typically dominated by the energy absorbed during the use phase. Energy efficiency is progressively considered as an additional performance index in comparing alternative machines, process planning, and machining strategies. For this purpose, this paper proposes a simulation approach that estimates the energy used by a machine tool in producing a generic workpiece by general milling operations. The developed tool simulates the execution of a standard ISO part program, basing on an explicit geometric and mechanistic representation of the cutting process, coupled with an energy model of the machine tool reproducing the power consumption of spindle, axes, and auxiliary units. Energy models were identified by an experimental characterization procedure that can be easily adopted in industrial contexts. The simulator was validated comparing the estimated energy with measurements performed on different cutting tests, evaluating also its computational effort. Moreover, the simulator performances were compared to alternative energy evaluation methods proposed in the literature.

Country
Italy
Keywords

Machine tool, modeling, simulation, Energy consumption; Machine tool; Modeling; Simulation; Control and Systems Engineering; Software; Mechanical Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Industrial and Manufacturing Engineering, energy consumption

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    21
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
21
Top 10%
Top 10%
Top 10%
Green