Software analyses of optimum toolpath strategies from computer numerical control (CNC) codes

被引:5
作者
Edem, Isuamfon F. [1 ]
Balogun, Vincent A. [2 ]
Nkanang, Bassey D. [1 ]
Mativenga, Paul T. [3 ]
机构
[1] Akwa Ibom State Univ, Dept Mech Engn, Fac Engn, Mkpat Enin, Akwa Ibom State, Nigeria
[2] Edo Univ Iyamho, Dept Mech Engn, Fac Engn, Iyamho, Edo State, Nigeria
[3] Univ Manchester, Sch Mech Aerosp & Civil Engn, Manchester M13 9PL, Lancs, England
关键词
Energy demand software; NC programmes; Toolpaths; Energy efficiency; Surface roughness; CUTTER PATH STRATEGIES; ENERGY DEMAND; ROUGHNESS; CONSUMPTION; PREDICTION; IMPACT;
D O I
10.1007/s00170-019-03604-6
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This study presents an approach for determining energy efficient toolpaths using numerical control (NC)-based energy demand software. To achieve this, NC programmes were generated for the true spiral, rectangular spiral, and square contour toolpaths from HyperMill, a commercially available Computer-Aided Manufacturing (CAM) software for performing pocket milling of AISI 1018 steel on a 3-axis CNC milling machine. These programmes were uploaded as input on the graphical user interface (GUI) of the NC code-based energy demand software. The result obtained from NC code-based energy software was validated against the theoretical total energy and processing time, and the pocket milling of AISI 1018 steel on a 3-axis CNC milling machine. The theoretical, software, and experimental analyses show that the true spiral toolpath had the lowest total electrical energy demand and processing time. The result also shows that the energy demand software could be adopted to accurately predict the total electrical energy and processing time pre-machining. This could save setting up and trial by error practices and costs. Further studies included surface roughness analyses of the machined pockets after milling, and an improved surface finish of the pocket was obtained with the true spiral toolpath when compared with the other considered toolpaths. Therefore, for energy efficient machining, it is recommended that NC code-based energy demand software which incorporates the weights of feed axes, vice, and workpiece, as well as the power required by the feed drive during cutting should be adopted for the accurate prediction of total electrical energy demand and total processing time of a machining process.
引用
收藏
页码:997 / 1007
页数:11
相关论文
共 35 条
  • [1] Holistic Simulation Environment for Energy Consumption Prediction of Machine Tools
    Abele, Eberhard
    Braun, Steffen
    Schraml, Philipp
    [J]. 22ND CIRP CONFERENCE ON LIFE CYCLE ENGINEERING, 2015, 29 : 251 - 256
  • [2] Modelling and optimization of energy consumption for feature based milling
    Altintas, Resul Sercan
    Kahya, Muge
    Unver, Hakki Ozgur
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2016, 86 (9-12) : 3345 - 3363
  • [3] [Anonymous], 2018, CO2 Emissions from Fuel Combustion
  • [4] Critical factors in energy demand modelling for CNC milling and impact of toolpath strategy
    Aramcharoen, Ampara
    Mativenga, Paul T.
    [J]. JOURNAL OF CLEANER PRODUCTION, 2014, 78 : 63 - 74
  • [5] Evaluating the use phase energy requirements of a machine tool system
    Avram, Oliver Ioan
    Xirouchakis, Paul
    [J]. JOURNAL OF CLEANER PRODUCTION, 2011, 19 (6-7) : 699 - 711
  • [6] E-smart toolpath machining strategy for process planning
    Balogun, Vincent A.
    Edem, Isuamfon F.
    Mativenga, Paul T.
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2016, 86 (5-8) : 1499 - 1508
  • [7] Modelling of direct energy requirements in mechanical machining processes
    Balogun, Vincent Aizebeoje
    Mativenga, Paul Tarisai
    [J]. JOURNAL OF CLEANER PRODUCTION, 2013, 41 : 179 - 186
  • [8] Evaluating the roughness according to the tool path strategy when milling free form surfaces for mold application
    de Souza, Adriano Fagali
    Machado, Adriane
    Beckert, Sueli Fischer
    Diniz, Anselmo Eduardo
    [J]. 6TH CIRP INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE CUTTING (HPC2014), 2014, 14 : 188 - 193
  • [9] Diaz N., 2010, P MTTRF 2010 ANN M
  • [10] Digest of United Kingdom Energy Statistics (DUKES), 2017, NAT STAT DEP BUS EN