Multi-objective optimization of machining parameters considering energy consumption

This paper deals with multi-objective optimization of machining parameters for energy saving. Three objectives including energy, cost, and quality are considered in the optimization model, which are affected by three variables, namely cutting depth, feed rate, and cutting speed. In the model, energy consumption of machining process consists of direct energy (including startup energy, cutting energy, and tool change energy) and embodied energy (including cutting tool energy and cutting fluid energy); machining cost contains production operation cost, cutting tool cost, and cutting fluid cost; and machining quality is represented by surface roughness. With simulation in Matlab R2011b, the multi-objective optimization problem is solved by NSGA-II algorithm. The simulation results indicate that cutting parameters optimization is beneficial for energy saving during machining, although more cost may be paid; additionally, optimization effect on the surface roughness objective is limited. Inspired by the second result, optimization model eliminating quality objective is studied further. Comparing the non-dominated front of three-objective optimization with the one of two-objective optimization, the latter is proved to have better convergence feature. The optimization model is valuable in energy quota determination of workpiece and product.

[1]  Huai Gao,et al.  A modeling method of task-oriented energy consumption for machining manufacturing system , 2012 .

[2]  Berend Denkena,et al.  Advancing Cutting Technology , 2003 .

[3]  He Yang,et al.  Optimization of processing parameters for double-ridged rectangular tube rotary draw bending based on grey relational analysis , 2014 .

[4]  Zuo Tie-yong,et al.  Life cycle inventories of fossil fuels in China(II):Final life cycle inventories , 2006 .

[5]  Maoguo Gong,et al.  Research on Evolutionary Multi-Objective Optimization Algorithms: Research on Evolutionary Multi-Objective Optimization Algorithms , 2009 .

[6]  David W. Corne,et al.  Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy , 2000, Evolutionary Computation.

[7]  Saad Mekhilef,et al.  A review on energy saving strategies in industrial sector , 2011 .

[8]  I. Hanafi,et al.  Optimization of cutting conditions for sustainable machining of PEEK-CF30 using TiN tools , 2012 .

[9]  M. Srinivasan,et al.  Feature-based process planning for environmentally conscious machining – Part 1: microplanning , 1999 .

[10]  P. Sheng,et al.  Multi-Objective Process Planning in Environmentally Conscious Manufacturing: A Feature-Based Approach , 1995 .

[11]  Siti Zaiton Mohd Hashim,et al.  Evolutionary techniques in optimizing machining parameters: Review and recent applications (2007-2011) , 2012, Expert Syst. Appl..

[12]  David N. Kordonowy,et al.  A power assessment of machining tools , 2002 .

[13]  Guillem Quintana,et al.  Modelling Power Consumption in Ball-End Milling Operations , 2011 .

[14]  Liang Gao,et al.  Modeling and impact factors analyzing of energy consumption in CNC face milling using GRASP gene expression programming , 2016 .

[15]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[16]  Jong-Leng Liow,et al.  Mechanical micromachining: a sustainable micro-device manufacturing approach? , 2009 .

[17]  Kalyanmoy Deb,et al.  Hybrid evolutionary multi-objective optimization and analysis of machining operations , 2012 .

[18]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[19]  Carlos A. Coello Coello,et al.  A Micro-Genetic Algorithm for Multiobjective Optimization , 2001, EMO.

[20]  Yunn-Shiuan Liao,et al.  Study of machining parameters optimization for different materials in WEDM , 2014 .

[21]  Yang Dong,et al.  Research on Evolutionary Multi-Objective Optimization Algorithms , 2009 .

[22]  P. Sheng,et al.  An analytical approach for determining the environmental impact of machining processes , 1995 .

[23]  Timothy G. Gutowski,et al.  An Environmental Analysis of Machining , 2004 .

[24]  Paul Mativenga,et al.  Sustainable machining: selection of optimum turning conditions based on minimum energy considerations , 2010 .

[25]  Jasbir S. Arora,et al.  Survey of multi-objective optimization methods for engineering , 2004 .

[26]  Guohui Zhang,et al.  Dynamic rescheduling in FMS that is simultaneously considering energy consumption and schedule efficiency , 2016 .

[27]  M. Srinivasan,et al.  Feature based process planning in environmentally conscious machining – Part 2: macroplanning , 1999 .

[28]  Vimal Dhokia,et al.  Energy efficient process planning for CNC machining , 2012 .

[29]  Makoto Fujishima,et al.  A study on energy efficiency improvement for machine tools , 2011 .

[30]  Gerry Byrne,et al.  Environmentally Clean Machining Processes — A Strategic Approach , 1993 .