Energy Cost Optimization in High Speed Hard Turning Using Simulated Annealing Algorithm

2015 ◽  
Vol 1115 ◽  
pp. 104-108
Author(s):  
Muataz Hazza F. Al Hazza ◽  
Erry Y.T. Adesta ◽  
Muhammad Hasibul Hasan ◽  
Norhashimah Shaffiar
Keyword(s):  
Simulated Annealing ◽  
Energy Cost ◽  
High Speed ◽  
Hard Turning ◽  
Simulated Annealing Algorithm ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Rake Angle ◽  
Depth Of Cut ◽  
Annealing Algorithm

Selecting the cutting conditions to optimize the economics of machining process as assessed by energy machining cost is essential. The aim of this research is to determine the optimum cutting parameters that minimize the energy cost needed for removing one cubic centimetre of material in High Speed Hard Turning (HSHT) process. To achieve that, a set of experimental machining data to cut hardened steel AISI 4340 was obtained with different ranges of cutting speed, feed rate, depth of cut and negative rake angle using mixed ceramic as a cutting tool. Regression models have been developed by using Box-Behnken design as a design of experiment. Then, the Simulated Annealing Algorithm (SAA) has been used to optimize the cutting parameters. The data collected was statistically modelled. The results show that the range of minimum energy cost to remove one cubic centimetre of material for the three techniques can be achieved in the range of 300 to 308 as a cutting speed, -12 for cutting rake angle, 0.125 as a feed rate and 0.15 as a depth of cut.

Development of Tooling Cost Model for High Speed Hard Turning

2011 ◽  
Vol 418-420 ◽  
pp. 1482-1485 ◽  
Author(s):  
Erry Yulian Triblas Adesta ◽  
Muataz Al Hazza ◽  
Delvis Agusman ◽  
Agus Geter Edy Sutjipto
Keyword(s):  
Feed Rate ◽  
High Speed ◽  
Hard Turning ◽  
Cost Model ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Rake Angle ◽  
Depth Of Cut ◽  
Predictive Regression ◽  
Aisi 4340

The current work presents the development of cost model for tooling during high speed hard turning of AISI 4340 hardened steel using regression analysis. A set of experimental data using ceramic cutting tools, composed approximately of Al2O3 (70%) and TiC (30%) on AISI 4340 heat treated to a hardness of 60 HRC was obtained in the following design boundary: cutting speeds (175-325 m/min), feed rate (0.075-0.125 m/rev), negative rake angle (0 to -12) and depth of cut of (0.1-0.15) mm. The output data is used to develop a new model in predicting the tooling cost using in terms of cutting speed, feed rate, depth of cut and rake angle. Box Behnken Design was used in developing the model. Predictive regression model was found to be capable of good predictions the tooling cost within the boundary design.

Achieving Optimal Process Parameters during Hard Turning of AISI 52100 Bearing Steel Using Hybrid GRA-PCA

2019 ◽  
Vol 818 ◽  
pp. 87-91 ◽  
Author(s):  
P. Umamaheswarrao ◽  
D. Ranga Raju ◽  
K.N.S. Suman ◽  
B. Ravi Sankar
Keyword(s):  
Hard Turning ◽  
Cubic Boron Nitride ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Rake Angle ◽  
Bearing Steel ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Aisi 52100 ◽  
Input Parameters

In the present work hard turning of AISI 52100 steel has been performed using Polycrystalline cubic boron nitride (PCBN) tools. The input parameters considered are cutting speed, feed, depth of cut, nose radius and negative rake angle and the measured responses are machining force and workpiece surface temperature. Experiments are planned as per Central Composite Design (CCD) of Response Surface Methodology (RSM). The effect of input parameters and their interactions are discussed with main effects plot. Further, the multi-objective optimization scheme is proposed by adopting Grey Relational Analysis (GRA) coupled with Principle Component Analysis (PCA). Results demonstrated that speed is the most significant factor affecting the responses followed by negative rake angle, feed, depth of cut, and nose radius. The optimum cutting parameters obtained are cutting speed 1000 rpm, feed 0.02 mm/rev, depth of cut 0.5 mm, Nose radius 1 mm and Negative rake angle 5o.

Predictive Modeling and Optimization of Cutting Forces Through RSM and Taguchi Techniques in the Turning of ASTM B574 (Hastelloy C-22)

2018 ◽  
pp. 398-417
Author(s):  
İsmail Kırbaş ◽  
Musa Peker ◽  
Gültekin Basmacı ◽  
Mustafa Ay
Keyword(s):  
Feed Rate ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Rake Angle ◽  
Orthogonal Experimental Design ◽  
Depth Of Cut ◽  
Effective Parameters ◽  
Factors Affecting ◽  
The Impact

In this chapter, the impact of cutting parameters (depth of cut, cutting speed, feed, flow, rake angle, lead angle) on cutting forces in the turning process with regard to ASTM B574 (Hastelloy C-22) material has been investigated. Variance analysis has been applied in order to determine the factors affecting the cutting forces. The optimization of the parameters affecting the surface roughness has been obtained using response surface methodology (RSM) based on the Taguchi orthogonal experimental design. The accuracy of the developed models required for the estimation of the force values (Fx, Fy, Fz) is quite successful. In this study, where the R2 value has been used as the criterion/measure, accuracy values of 93.35%, 95.03%, and 95.09% have been achieved for Fx, Fy, and Fz, respectively. As a result of the ANOVA analysis, the most effective parameters for Fx at a 95% confidence interval are depth of cut, feed rate, flow, and rake angle. The most effective parameter for Fy is depth of cut, while the most effective parameters for Fz are depth of cut, feed rate, and flow, respectively.

scholarly journals Surface Quality Assessment after Milling AZ91D Magnesium Alloy Using PCD Tool

Materials ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 617 ◽  
Author(s):  
Ireneusz Zagórski ◽  
Jarosław Korpysa
Keyword(s):  
Surface Roughness ◽  
Magnesium Alloy ◽  
High Speed ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Roughness Parameters ◽  
Operational Parameters

Surface roughness is among the key indicators describing the quality of machined surfaces. Although it is an aggregate of several factors, the condition of the surface is largely determined by the type of tool and the operational parameters of machining. This study sought to examine the effect that particular machining parameters have on the quality of the surface. The investigated operation was the high-speed dry milling of a magnesium alloy with a polycrystalline diamond (PCD) cutting tool dedicated for light metal applications. Magnesium alloys have low density, and thus are commonly used in the aerospace or automotive industries. The state of the Mg surfaces was assessed using the 2D surface roughness parameters, measured on the lateral and the end face of the specimens, and the end-face 3D area roughness parameters. The description of the surfaces was complemented with the surface topography maps and the Abbott–Firestone curves of the specimens. Most 2D roughness parameters were to a limited extent affected by the changes in the cutting speed and the axial depth of cut, therefore, the results from the measurements were subjected to statistical analysis. From the data comparison, it emerged that PCD-tipped tools are resilient to changes in the cutting parameters and produce a high-quality surface finish.

RSM Based Investigations on the Effects of Cutting Parameters on Surface Integrity during Cryogenic Hard Turning of AISI 52100

2015 ◽  
Vol 15 (3) ◽  
pp. 309-318 ◽  
Author(s):  
Suha K. Shihab ◽  
Zahid A. Khan ◽  
Arshad Noor Siddiquee
Keyword(s):  
Surface Integrity ◽  
Feed Rate ◽  
Hard Turning ◽  
Desirability Function ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machined Surface ◽  
Aisi 52100 ◽  
Model Equations

AbstractEffect of cryogenic hard turning parameters (cutting speed, feed rate, and depth of cut) on surface roughness (Ra) and micro-hardness (µH) that constitute surface integrity (SI) of the machined surface of alloy steel AISI 52100 is investigated. Multilayer hard surface coated (TiN/TiCN/Al2O3/TiN) insert on CNC lathe is used for turning under different cutting parameters settings. RSM based Central composite design (CCD) of experiment is used to collect data for Ra and µH. Validity of assumptions related to the collected data is checked through several diagnostic tests. The analysis of variance (ANOVA) is used to determine main and interaction effects. Relationship between the variables is established using quadratic regression model. Both Ra and µH are influenced principally by the cutting speed and the feed rate. Model equations are found to predict accurate values of Ra and µH. Finally, desirability function approach for multiple response optimization is used to produce optimum SI.

Cutting Forces in High Speed Milling of Hardened Steel by Coated Tool

2009 ◽  
Vol 69-70 ◽  
pp. 418-422
Author(s):  
L.D. Wu ◽  
Cheng Yong Wang ◽  
D.H. Yu ◽  
Yue Xian Song
Keyword(s):  
Cutting Forces ◽  
High Speed ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Hardened Steel ◽  
Depth Of Cut ◽  
Coated Tool ◽  
Radial Depth ◽  
Solid Carbide ◽  
End Mills

Hardened steel P20 at 50 HRC is milled at high speed by TiN coated and TiAlN coated solid carbide straight end mills, and the cutting forces and tool wear are measured. The result shows that TiAlN coated tool is more suitable for cutting hardened steel at high speed. Then the hardened steel is milled under different cutting parameters. It is indicated that the effect of cutting speed on cutting forces is small, but the effect of cutting speed on machine vibration should be considered. Increase feed per tooth or radial depth of cut will increase the cutting forces.

scholarly journals Track allocation optimization in high-speed railway stations from infrastructure management and service perspectives

2018 ◽  
Vol 51 (7-8) ◽  
pp. 243-259 ◽  
Author(s):  
Qin Zhang ◽  
Xiaoning Zhu ◽  
Li Wang
Keyword(s):  
Simulated Annealing ◽  
High Speed ◽  
Simulated Annealing Algorithm ◽  
Accurate Method ◽  
Nonlinear Integer Programming ◽  
Walking Distance ◽  
Infrastructure Management ◽  
High Speed Railway ◽  
Railway Stations ◽  
Annealing Algorithm

Background: The high-speed railway has been developed rapidly, making track allocation optimization in high-speed railway stations one of the most important problems for traffic control. Methods: This paper proposes a 0-1 nonlinear integer programming model from both infrastructure management and service perspectives to solve this problem at the tactical level. The goal is to balance the track occupation time and at the same time to minimize the total walking distance between the entrance hall and the platforms for all passengers. A pre-calculation technique of time points considering the preparation of the route and a line group method are firstly studied. In order to solve the programming, the simulated annealing algorithm is applied. Results: A case of a China high-speed railway station is used to verify the effectiveness of this model. The optimized result is much better than the original plan in some key indicators. A comparison between the proposed algorithm and an accurate method, the branch-and-bound, is demonstrated. The simulated annealing algorithm obtains almost the same result as the accurate method in a much shorter time. Conclusions: The proposed model is practicable for the the high-speed railway stations.

scholarly journals Multi-Response Optimization in High-Speed Machining of Ti-6Al-4V Using TOPSIS-Fuzzy Integrated Approach

Materials ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1104 ◽  
Author(s):  
Adel T. Abbas ◽  
Neeraj Sharma ◽  
Saqib Anwar ◽  
Monis Luqman ◽  
Italo Tomaz ◽  
...  
Keyword(s):  
Titanium Alloys ◽  
High Speed ◽  
Removal Rate ◽  
Cutting Speed ◽  
Optimal Solution ◽  
Cutting Parameters ◽  
Integrated Approach ◽  
High Heat ◽  
Depth Of Cut ◽  
Cutting Processes

Titanium alloys are widely used in various applications including biomedicine, aerospace, marine, energy, and chemical industries because of their superior characteristics such as high hot strength and hardness, low density, and superior fracture toughness and corrosion resistance. However, there are different challenges when machining titanium alloys because of the high heat generated during cutting processes which adversely affects the product quality and process performance in general. Thus, optimization of the machining conditions while machining such alloys is necessary. In this work, an experimental investigation into the influence of different cutting parameters (i.e., depth of cut, cutting length, feed rate, and cutting speed) on surface roughness (Rz), flank wear (VB), power consumption as well as the material removal rate (MRR) during high-speed turning of Ti-6Al-4V alloy is presented and discussed. In addition, a backpropagation neural network (BPNN) along with the technique for order of preference by similarity to ideal solution (TOPSIS)-fuzzy integrated approach was employed to model and optimize the overall cutting performance. It should be stated that the predicted values for all machining outputs demonstrated excellent agreement with the experimental values at the selected optimal solution. In addition, the selected optimal solution did not provide the best performance for each measured output, but it achieved a balance among all studied responses.

Hard Turning of Hot Work Steel X38CRMOV5-3: Evaluation of Surface Roughness and Current Values Using Cutting Parameters

2020 ◽  
Author(s):  
Ali Kemal Cakir
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Feed Rate ◽  
Hard Turning ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Dry Machining ◽  
Motor Current ◽  
Design Factors

This study evaluates the surface roughness and current values using cutting parameters in the turning of AISI H11 being hot work tool steel under dry machining conditions. The selected design factors are the depth of cut, feed rate, cutting speed. A design of experiments was used to carry out this research. The obtained results were analyzed to determine the effects of input parameters on the resultant surface roughness, current using the analysis of variance (ANOVA) and the Response Surface Methodology (RSM). The experimental results showed that increasing feed rate increased the surface roughness, and current values. The most effective cutting parameter on all the output parameters was found to be the feed rate on the surface roughness. Also, the motor current values were influenced by the 38,48% depth of cut, 23,98% cutting speed, 25,52% feed rate, respectively.

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