scholarly journals Fuzzy Linguistic Optimization on Surface Roughness for CNC Turning

2010 ◽  
Vol 2010 ◽  
pp. 1-10 ◽  
Author(s):  
Tian-Syung Lan
Keyword(s):  
Surface Roughness ◽  
Orthogonal Array ◽  
Cnc Machining ◽  
Optimization Scheme ◽  
Cnc Turning ◽  
Finish Turning ◽  
Control Rules ◽  
Optimization Parameters ◽  
High Level ◽  
Fuzzy Linguistic

Surface roughness is often considered the main purpose in contemporary computer numerical controlled (CNC) machining industry. Most existing optimization researches for CNC finish turning were either accomplished within certain manufacturing circumstances or achieved through numerous equipment operations. Therefore, a general deduction optimization scheme is deemed to be necessary for the industry. In this paper, the cutting depth, feed rate, speed, and tool nose runoff with low, medium, and high level are considered to optimize the surface roughness for finish turning based onL9(34)orthogonal array. Additionally, nine fuzzy control rules using triangle membership function with respective to five linguistic grades for surface roughness are constructed. Considering four input and twenty output intervals, the defuzzification using center of gravity is then completed. Thus, the optimum general fuzzy linguistic parameters can then be received. The confirmation experiment result showed that the surface roughness from the fuzzy linguistic optimization parameters is significantly advanced compared to that from the benchmark. This paper certainly proposes a general optimization scheme using orthogonal array fuzzy linguistic approach to the surface roughness for CNC turning with profound insight.

FUZZY TAGUCHI DEDUCTION OPTIMIZATION ON MULTI-ATTRIBUTE CNC TURNING

2010 ◽  
Vol 34 (3-4) ◽  
pp. 401-415 ◽  
Author(s):  
Tian-Syung Lan
Keyword(s):  
Fuzzy Control ◽  
Orthogonal Array ◽  
Numerical Control ◽  
Ideal Solution ◽  
Cnc Turning ◽  
Control Rules ◽  
Order Preference ◽  
Optimization Parameters ◽  
Topsis Technique ◽  
To Receive

In this paper, four parameters with three levels are considered to optimize the multi-attribute finish CNC (computer numerical control) turning based on L9(34) orthogonal array. Additionally, nine fuzzy control rules with respective to five linguistic grades for each attribute are constructed. The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is moreover utilized to integrate and evaluate the multiple machining attributes for Taguchi experiment to receive the optimum general deduction parameters. It is shown that the attributes from the fuzzy Taguchi deduction optimization parameters are all significantly advanced comparing to those from benchmark.

Taguchi Approach for the Optimization of Cutting Parameters in Finish Turning of Medical Stainless Steel

2015 ◽  
Vol 809-810 ◽  
pp. 153-158
Author(s):  
Miroslav Radovanović ◽  
Laurentiu Slatineanu ◽  
Predrag Janković ◽  
Dušan Petković ◽  
Miloš Madić
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Taguchi Method ◽  
Orthogonal Array ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Finish Turning ◽  
Cutting Parameter ◽  
Optimization Of Cutting Parameters ◽  
Coated Carbide

Optimization of cutting parameters in finish turning of medical stainless steel 316LVM with coated carbide tools using Taguchi method is proposed in this paper. Four cutting parameters namely, insert radius, depth of cut, feed and cutting speed are optimized with considerations of surface roughness as performance characteristic. The effects of cutting parameters on the surface roughness were experimentally investigated. Experimentation was conducted as per Taguchi's orthogonal array. Four cutting parameters with three levels are arranged in L27 orthogonal array. The orthogonal array, measured values of surface roughness, signal-to-noise ratios and analysis of variance are employed to study the surface roughness. Based on the analysis, the optimal cutting parameter settings were determined. Through the confirmation test with optimal cutting parameter settings the effectiveness of the optimization approach are validated. The obtained results have shown that Taguchi method is suitable for optimizing the cutting parameter levels with the minimum number of experiments.

Monitoring of Cutting Conditions with Dry Cutting on CNC Turning Machine

2010 ◽  
Vol 443 ◽  
pp. 382-387 ◽  
Author(s):  
Somkiat Tangjitsitcharoen ◽  
Suthas Ratanakuakangwan
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Cutting Forces ◽  
Cutting Temperature ◽  
Cutting Conditions ◽  
Cutting Condition ◽  
Nose Radius ◽  
Dry Cutting ◽  
Cnc Turning ◽  
Coated Carbide

This paper presents the additional work of the previous research in order to verify the previously obtained cutting condition by using the different cutting tool geometries. The effects of the cutting conditions with the dry cutting are monitored to obtain the proper cutting condition for the plain carbon steel with the coated carbide tool based on the consideration of the surface roughness and the tool life. The dynamometer is employed and installed on the turret of CNC turning machine to measure the in-process cutting forces. The in-process cutting forces are used to analyze the cutting temperature, the tool wear and the surface roughness. The experimentally obtained results show that the surface roughness and the tool wear can be well explained by the in-process cutting forces. Referring to the criteria, the experimentally obtained proper cutting condition is the same with the previous research except the rake angle and the tool nose radius.

OPTIMAL PREDICTION AND DESIGN OF SURFACE ROUGHNESS FOR CNC TURNING OF AL7075-T6 BY USING THE TAGUCHI HYBRID QPSO ALGORITHM

2016 ◽  
Vol 40 (5) ◽  
pp. 883-895 ◽  
Author(s):  
Wen-Jong Chen ◽  
Chuan-Kuei Huang ◽  
Qi-Zheng Yang ◽  
Yin-Liang Yang
Keyword(s):  
Surface Roughness ◽  
Particle Swarm Optimization ◽  
Predictive Models ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Cutting Parameters ◽  
Optimization Methods ◽  
Swarm Optimization ◽  
Cnc Turning ◽  
Multi Objective

This paper combines the Taguchi-based response surface methodology (RSM) with a multi-objective hybrid quantum-behaved particle swarm optimization (MOHQPSO) to predict the optimal surface roughness of Al7075-T6 workpiece through a CNC turning machining. First, the Taguchi orthogonal array L27 (36) was applied to determine the crucial cutting parameters: feed rate, tool relief angle, and cutting depth. Subsequently, the RSM was used to construct the predictive models of surface roughness (Ra, Rmax, and Rz). Finally, the MOHQPSO with mutation was used to determine the optimal roughness and cutting conditions. The results show that, compared with the non-optimization, Taguchi and classical multi-objective particle swarm optimization methods (MOPSO), the roughness Ra using MOHQPSO along the Pareto optimal solution are improved by 68.24, 59.31 and 33.80%, respectively. This reveals that the predictive models established can improve the machining quality in CNC turning of Al7075-T6.

Surface Roughness Impact on Secondary Flow and Losses in a Turbine Exhaust Casing

2018 ◽  
Author(s):  
Isak Jonsson ◽  
Valery Chernoray ◽  
Borja Rojo
Keyword(s):  
Surface Roughness ◽  
Secondary Flow ◽  
Suction Side ◽  
Pressure Probe ◽  
Time Resolved ◽  
Pressure Distributions ◽  
Turbulence Decay ◽  
Inlet Swirl ◽  
High Level ◽  
The Impact

This paper experimentally addresses the impact of surface roughness on losses and secondary flow in a Turbine Rear Structure (TRS). Experiments were performed in the Chalmers LPT-OGV facility, at an engine representative Reynolds number with a realistic shrouded rotating low-pressure turbine (LPT). Outlet Guide Vanes (OGV) were manufactured to achieve three different surface roughnesses tested at two Reynolds numbers, Re = 235000 and Re = 465000. The experiments were performed at on-design inlet swirl conditions. The inlet and outlet flow of the TRS were measured in 2D planes with a 5-hole probe and 7-hole probe accordingly. The static pressure distributions on the OGVs were measured and boundary layer studies were performed at the OGV midspan on the suction side with a time-resolved total pressure probe. Turbulence decay was measured within the TRS with a single hot-wire. The results showed a surprisingly significant increase in the losses for the high level of surface roughness (25–30 Ra) of the OGVs and Re = 465000. The increased losses were primary revealed as a result of the flow separation on the OGV suction side near the hub. The loss increase was seen but was less substantial for the intermediate roughness case (4–8 Ra). Experimental results presented in this work provide support for the further development of more advanced TRS and data for the validation of new CFD prediction methods for TRS.

scholarly journals Tribological Behavior and Analysis on Surface Roughness of CNC Milled Dual Heat Treated Al6061 Composites

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
A. Bovas Herbert Bejaxhin ◽  
G.M. Balamurugan ◽  
S.M. Sivagami ◽  
K. Ramkumar ◽  
V. Vijayan ◽  
...  
Keyword(s):  
Heat Treatment ◽  
Surface Roughness ◽  
Lower Surface ◽  
Cnc Machining ◽  
Depth Of Cut ◽  
Good Surface ◽  
Heat Treated ◽  
Good Surface Finish ◽  
Artificial Neural Network Ann ◽  
Machining Properties

Dual heat treatment (DHT) effect is analyzed using the machining of Al6061-T6 alloy, a readily available material for quickly finding the machining properties. The heat treatments are conducted twice over the specimen by the furnace heating before processing through CNC machining. The HSS and WC milling cutters are preferred for the diameter of 10 mm for the reviewed rotational speeds of 2000 rpm and 4000 rpm, and the constant depth of cut of 0.5 mm is chosen based on various reviews. Worthy roughness could be provided mostly by the influence of feed rates preferred here as 0.05 mm/rev and 0.1 mm/rev. The influencing factors are identified by the Taguchi, genetic algorithm (GA), and Artificial Neural Network (ANN) techniques and compared within it. The simulation finding also helps to clarify the relationship between influenced machining constraints and roughness outcomes of this project. The average values of heat treated and nonheat treated Al6061-T6 are compared and it is to be evaluated that 41% improvement is obtained with the lower surface roughness of 1.78975 µm and it shows good surface finish with the help of dual heat treatment process.

scholarly journals ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs

Materials ◽  
2018 ◽  
Vol 11 (5) ◽  
pp. 808 ◽  
Author(s):  
Adel Abbas ◽  
Danil Pimenov ◽  
Ivan Erdakov ◽  
Mohamed Taha ◽  
Mahmoud Soliman ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Magnesium Alloy ◽  
Finish Turning ◽  
Az61 Magnesium Alloy
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