Optimization of process parameters for minimum energy consumption based on cutting specific energy consumption

Deng, Zhaohui; Zhang, Hua; Fu, Yahui; Wan, Linlin; Liu, Wei

doi:10.1016/j.jclepro.2017.08.022

Cited by 73 publications

(13 citation statements)

References 29 publications

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“…Deng et al 30 proposed a method to optimize the machining parameters in order to reduce the specific energy consumption and the processing time. Real constraint conditions were considered, and the model was solved using a genetic algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

Use of a virtual milling system to generate power-aware tool paths for 2.5-dimensional pocket machining

González

Ferreira

2019

Proceedings of the Institution of Mechanical Engineers, Part B:

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Traditional (direction-parallel and contour-parallel) and non-traditional (trochoidal) tool paths are generated by specialized geometric algorithms based on the pocket shape and various parameters. However, the tool paths generated with those methods do not usually consider the required machining power. In this work, a method for generating power-aware tool paths is presented, which uses the power consumption estimation for the calculation of the tool path. A virtual milling system was developed to integrate with the tool path generation algorithm in order to obtain tool paths with precise power requirement control. The virtual milling system and the tests used to calibrate it are described within this article, as well as the proposed tool path generation algorithm. Results from machining a test pocket are presented, including the real and the estimated power requirements. Those results were compared with a contour-parallel tool path strategy, which has a shorter machining time but has higher in-process power consumption.

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Section: Literature Reviewmentioning

confidence: 99%

Use of a virtual milling system to generate power-aware tool paths for 2.5-dimensional pocket machining

González

Ferreira

2019

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…Albertelli et al [15] conducted multi-cutting parameters (cutting speed, the feed and the radial depth of cut) using energy as an optimization goal in face milling, which refined energy consumption composition. Deng et al [16] optimized the process parameters using cutting specific energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Minimizing the Energy Consumption of Holes Machining Integrating the Optimization of Tool Path and Cutting Parameters on CNC Machines

Feng

Chen

Zhang

et al. 2021

Preprint

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The application of sustainable manufacturing technologies is the new challenge faced by enterprises, industries, and researchers under the background of supporting carbon peak and carbon neutral. This paper studies how to reduce the energy consumption of holes machining through optimizing tool path and cutting parameters simultaneously. The integrated optimization methodology can further reduce the energy consumption comparing with optimizing the tool path or cutting parameters separately. Firstly, the energy model of holes machining is established based on machine tools’ energy composition, tool path planning, and process parameters. Due to tool path planning as air cutting process has big relationship with reducing energy, especially for holes group with a big proportion in the whole process. The tool path of holes processing is optimized by the improved ant colony algorithm to solve the issue considering the distance from one hole to the next hole. Based on this optimized path, a multi-objective optimization model for hole cutting parameters is established, considering the spindle speed and feed rate as the optimization variables and machining time, energy consumption, and surface roughness as the objective function. The non-dominated sorting genetic algorithm (NSGA-Ⅱ) is employed to solve the multi-objective optimization problem of holes machining. The case study with 50 holes is used to testify the application of the proposed method to provide the practical energy efficiency strategy for holes group or multi-hole parts on CNC machines assisting in achieving sustainable production in manufacturing sectors.

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“…Shin et al [23] have advanced the energy prediction and optimization knowledge by developing and implementing on-line optimization so that real-time process control can be accomplished to minimize energy consumption. Deng et al [24] in their study attempted to reduce the energy consumption by milling machine tool. They have performed the optimization within the constraints of surface roughness, tool life and maximum power of machine tool.…”

Section: Introductionmentioning

confidence: 99%

Investigations of surface quality and energy consumption associated with costs and material removal rate during face milling of AISI 1045 steel

Pimenov

Abbas

Gupta

et al. 2020

Int J Adv Manuf Technol

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Face milling is a well known commercial process highly used in heavy industries that consumes high amount of power. Besides power issue, modern manufacturing industries are aiming for per part cost reduction keeping the product quality unimpaired. Unexpectedly if the part is rejected in any stage of manufacturing, the cost of manufacturing dramatically increases. Major cause of part rejection is excessive tool wear that imparts poor surface profile or catastrophic tool failure that causes adherence of broken tool debris onto machined surface. Furthermore, the tool wear is associated with sliding distance (frictional distance) and the tool life quantifies the cost of tools. As such, from the perspective of manufacturing industries it is imperative to optimize the surface quality parameter, cost of part, power consumption, and material removal -this is exactly what is accomplished here. By this work, it is possible to conserve power consumption, produce parts with lower cost, manufacture with uncompromising surface quality and enhanced material removal rate. Moreover, as intermediate factors of interest, the influences of sliding distance, tool life and tool flank wear on the overall machining performance are evaluated. The multi-objective optimization by Grey Relational Analysis (GRA) revealed that for improved product performance and fast manufacturing (case 1) optimum results are: feed per tooth fz = 0.25 mm/tooth, cutting speed vc = 392.6 m/min and cutting length l = 0.5 mm; for resource conservation (case 2) the optimum results are: feed per tooth fz = 0.125 mm/tooth, cutting speed vc = 392.6 m/min, cutting length l = 0.5 mm.

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Optimization of process parameters for minimum energy consumption based on cutting specific energy consumption

Cited by 73 publications

References 29 publications

Use of a virtual milling system to generate power-aware tool paths for 2.5-dimensional pocket machining

Use of a virtual milling system to generate power-aware tool paths for 2.5-dimensional pocket machining

Minimizing the Energy Consumption of Holes Machining Integrating the Optimization of Tool Path and Cutting Parameters on CNC Machines

Investigations of surface quality and energy consumption associated with costs and material removal rate during face milling of AISI 1045 steel

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