scholarly journals Multi-Objective Optimization Model of Multi-Pass Turning Operations to Minimize Energy, Carbon Emissions, and Production Costs

2020 ◽  
Vol 21 (2) ◽  
pp. 213-224
Author(s):  
Aprilia Dityarini ◽  
Eko Pujiyanto ◽  
I Wayan Suletra
Keyword(s):  
Carbon Emissions ◽  
Optimization Model ◽  
Sustainable Manufacturing ◽  
Cutting Parameters ◽  
Production Costs ◽  
Machining Process ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Decision Variables ◽  
Optimal Values

Sustainable manufacturing aspects are environmental, economic, and social. These aspects can be applied to an optimization model in the machining process. An optimization model is needed to determine the optimum cutting parameters. This research develops a multi-objective optimization model that can optimize cutting parameters on a multi-pass turning. Decision variables are cutting parameters multi-pass turning. This research has three objective functions for minimizing energy, carbon emissions, and costs. Three functions are searched for optimal values using the GEKKO.  A numerical example is given to show the implementation of the model and solved using GEKKO and Interior Point Optimizer (IPOPT). The results of optimization indicate that the model can be used to optimize the cutting parameters.

Multi-Objective Optimization Model of Export and Transit Containers Storage in a Transshipment Port Yard

2012 ◽  
Vol 220-223 ◽  
pp. 272-278 ◽  
Author(s):  
Bin Wang ◽  
Tao Yang
Keyword(s):  
Integer Programming ◽  
Objective Function ◽  
Optimization Model ◽  
Storage Capacity ◽  
Multi Objective Optimization ◽  
Planning Period ◽  
Multi Objective ◽  
Numerical Example ◽  
Decision Variables ◽  
Operational Capacity

To effectively improve the competitiveness of port enterprises, container yard stacking optimization is an important way to raise their benefit. A multi-objective optimization model for containers stacking in the storage yard based on 0-1mixed integer programming is built to improve its efficiency. The objective function is to minimize the number of yard cranes used in the storage yard and balance the workload among different blocks during the planning period. The decision variables include the number of transit and export containers assigned to yard-bits, yard cranes distributed to blocks, yard-bits with high and low workload in a block. The constraints include meeting the shipping requirement, storage capacity and operational capacity of yard cranes. A numerical example is given and solved by Lingo9.0. The simulation is done to recover the relation between workload level and the number of yard crane used and the workload balance. The model can be used to yard stacking management and lift its level for a transshipment port.

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

Study on Cutting Parameters Optimization Based on Uniform Design Method

2010 ◽  
Vol 26-28 ◽  
pp. 764-769
Author(s):  
Deng Wan Li ◽  
Hong Tao Chen ◽  
Ming Heng Xu ◽  
Cheng Ming Zhong
Keyword(s):  
Titanium Alloy ◽  
Optimization Model ◽  
Design Method ◽  
Uniform Design ◽  
Multiple Linear Regression Model ◽  
Cutting Parameters ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Uniform Design Method ◽  
Cutting Parameters Optimization

In order to explore the cutting rules and optimize the cutting parameters of titanium alloy, multiple sets of test parameters were schemed out by using the uniform design method. Test cutting researches with these parameters were conducted under the condition of 12°C dry cutting and -50°C cold blast machining respectively. Through the regression analysis about the results of the test, a multiple linear regression model which is applicable for titanium alloy cutting on its surface roughness and cutting force has been established. The variance analysis shows that it is of remarkable linear relationship. On this basis, a multi-objective optimization model of titanium alloy has been set up. And by means of multi-objective data weighted method, successfully convert the multi-objective optimization model into a single-objective one. Verification tests were done under these cutting parameters, and the results are in good agreement with the calculated.

scholarly journals Comparison of NSGA-II, MOALO and MODA for Multi-Objective Optimization of Micro-Machining Processes

Materials ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5109
Author(s):  
Milan Joshi ◽  
Ranjan Kumar Ghadai ◽  
S. Madhu ◽  
Kanak Kalita ◽  
Xiao-Zhi Gao
Keyword(s):  
Manufacturing Industry ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Machining Process ◽  
Micro Milling ◽  
Micro Machining ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Micro Turning

The popularity of micro-machining is rapidly increasing due to the growing demands for miniature products. Among different micro-machining approaches, micro-turning and micro-milling are widely used in the manufacturing industry. The various cutting parameters of micro-turning and micro-milling has a significant effect on the machining performance. Thus, it is essential that the cutting parameters are optimized to obtain the most from the machining process. However, it is often seen that many machining objectives have conflicting parameter settings. For example, generally, a high material removal rate (MRR) is accompanied by high surface roughness (SR). In this paper, metaheuristic multi-objective optimization algorithms are utilized to generate Pareto optimal solutions for micro-turning and micro-milling applications. A comparative study is carried out to assess the performance of non-dominated sorting genetic algorithm II (NSGA-II), multi-objective ant lion optimization (MOALO) and multi-objective dragonfly optimization (MODA) in micro-machining applications. The complex proportional assessment (COPRAS) method is used to compare the NSGA-II, MOALO and MODA generated Pareto solutions.

scholarly journals Multi-Objective Optimization of Machining Parameters for Multi-Pass CNC Turning to Minimize Carbon Emissions, Energy, Noise and Cost

2021 ◽  
Vol 23 (1) ◽  
pp. 25-34
Author(s):  
Bening Maulina Fittamami ◽  
Eko Pujiyanto ◽  
Yusuf Priyandari
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Manufacturing Process ◽  
Production Cost ◽  
Sustainable Manufacturing ◽  
Machining Process ◽  
Total Carbon ◽  
Machining Parameters ◽  
Cnc Turning ◽  
Multi Objective

Global warming is a huge environmental issue today. This is due to the high level of world carbon emissions. The manufacturing process accounts for 30% of the world's carbon emissions production.  Sustainable manufacturing is necessary to implement to reduce carbon emission levels caused by the manufacturing process. There are three aspects of sustainable manufacturing, namely environmental aspects, economic aspects, and social aspects. These three aspects can be implemented in the machining process by optimizing machining parameters in multi-pass CNC turning. This research aims to optimize CNC turning machining parameters by considering energy consumption, carbon emissions, noise, and production cost. The model is solved using a Multi-objective Genetic Algorithm in Matlab 2016b then the transformation and weighting functions are carried out from the feasible value. Based on the optimization results, the total energy consumption value obtained is 2.50 MJ; total production cost is $ 2.19; total carbon emissions are 5.97 kgCO2, and noise is 236, 19 dB. The sensitivity analysis exhibits the machining parameters that affect the objective function: The cutting speed parameter and the feed rate parameter. This model can be used to improve the manufacturing process and support sustainable manufacturing.

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