Multi-objective optimization model of CNC machining to minimize processing time and environmental impact

2017 ◽  
Author(s):  
Aulia Hamada ◽  
Cucuk Nur Rosyidi ◽  
Wakhid Ahmad Jauhari
Keyword(s):  
Environmental Impact ◽  
Optimization Model ◽  
Processing Time ◽  
Cnc Machining ◽  
Multi Objective Optimization ◽  
Multi Objective

scholarly journals Multi objective optimization model of CNC turning for minimizing processing time and carbon emission with real machining application

2021 ◽  
Vol 14 (2) ◽  
pp. 376
Author(s):  
Cucuk Nur Rosyidi ◽  
Wahyu Widhiarso ◽  
Eko Pujiyanto
Keyword(s):  
Carbon Emissions ◽  
Optimization Model ◽  
Carbon Emission ◽  
Processing Time ◽  
Cutting Speed ◽  
Cutting Fluid ◽  
Multi Objective Optimization ◽  
Cnc Turning ◽  
Multi Objective ◽  
Cnc Turning Process

Purpose: The purpose of this research is to develop an optimization model of CNC turning process. The objective function of the model is to minimize processing time and carbon emission. We implemented the results of optimization with real machining application using a certain workpiece.Design/methodology/approach: The model in this research used multi objective optimization involving two objective functions, namely processing time which includes cutting time and auxiliary time and carbon emissions resulted from the electricity energy consumptions, cutting tool, cutting fluid or coolant, raw materials production, and chip removal.Findings: The results of multi objective optimization indicate that the model can be used to minimize the processing time and carbon emissions with the optimal cutting speed and feed rate are 193.7 m/minute and 0.405 mm/rev. The results of sensitivity analysis showed that the higher weights of processing time will decrease the cutting speed, while the higher carbon emissions weight will result in faster cutting speed. The weight has no effects on feed rate.Originality/value: This paper gives a real machining application to show the applicability of the optimization model

Multi-Objective Design of Process Parameter Based on Game Theory

2011 ◽  
Vol 121-126 ◽  
pp. 964-967 ◽  
Author(s):  
Yan Li ◽  
He Ping Wang ◽  
Fu Yu Wang
Keyword(s):  
Optimization Model ◽  
Game Design ◽  
Processing Time ◽  
Design Method ◽  
Process Parameter ◽  
Game Model ◽  
Multi Objective Optimization ◽  
Game Analysis ◽  
Multi Objective ◽  
Processing Cost

Taking the processing time ,the processing cost per workpiece as objective funtion,two optimization model is established.Multi-objective solving method based on nash equilibrium game model is put forward.Taking the sub-objective function of multi-objective optimization model as game party ,all design variable as strategy set,calculation steps of process parameter multi-objective optimization based on game analysis are founded .As turing technology an example,the result of analysis show multi-objective game design method is effective and feasible

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

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