Influence of tool path strategies on machining time, tool wear, and surface roughness during milling of AISI X210Cr12 steel

2022 ◽  
Author(s):  
Mahir Uzun ◽  
Üsame Ali Usca ◽  
Mustafa Kuntoğlu ◽  
Munish Kumar Gupta
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Tool Path ◽  
Machining Time

scholarly journals Using uniform design and regression methodology of turning parameters study of nickel alloy

2021 ◽  
Author(s):  
Shao-Hsien Chen ◽  
Chih-Hung Hsu
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Nickel Alloy ◽  
Design Methodology ◽  
Cutting Tool ◽  
Uniform Design ◽  
Machining Time ◽  
Variable Parameters ◽  
Cutting Test ◽  
Set Up

AbstractThe nickel alloy has good mechanical strength and corrosion resistance at high temperature; it is extensively used in aerospace and biomedical and energy industries, as well as alloy designs of different chemical compositions to achieve different mechanical properties. However, for high mechanical strength, low thermal conductivity, and surface hardening property, the nickel alloy has worse cutting tool life and machining efficiency than general materials. Therefore, how to select the optimum machining parameters will influence the workpiece quality, cost, and machining time. This research will be using a new experimental design methodology to the cutting parameter planning for nickel-based alloy cutting test, and used the uniform design methodology to cutting test to reduce the number of experiments. Three independent variable parameters are set up, including cutting speed, feed rate, and cutting depth, and four dependent variable parameters are set up, including cutting tool wear, surface roughness, machining time, and cutting force. A nickel alloy turning parameter model is built by using regression analysis to further predict the I/O relationship among various combinations of variables. The errors between actual values and prediction values are validated. When the cutting tool wear (VB) is 2.72~6.18%, the surface roughness (Ra) is 4.10~7.72%, the machining time (T) is 3.75~8.82%, and the cutting force (N) is 1.54~7.42%; the errors of various dependent variables are approximately less than 10%, so a high precision estimation model is obtained through a few experiments of uniform design method.

scholarly journals Automated Unsupervised 3D Tool-Path Generation Using Stacked 2D Image Processing Technique

2019 ◽  
Vol 3 (4) ◽  
pp. 84
Author(s):  
Tadele Belay Tuli ◽  
Andrea Cesarini
Keyword(s):  
Tool Wear ◽  
Tool Path ◽  
Closed Form Solution ◽  
Tool Path Generation ◽  
Image Processing Technique ◽  
Depth Of Cut ◽  
Path Generation ◽  
Machining Parameters ◽  
Machining Time ◽  
G Code

Tool-path, feed-rate, and depth-of-cut of a tool determine the machining time, tool wear, power consumption, and realization costs. Before the commissioning and production, a preliminary phase of failure-mode identification and effect analysis allows for selecting the optimal machining parameters for cutting, which, in turn, reduces machinery faults, production errors and, ultimately, decreases costs. For this, scalable high-precision path generation algorithms requiring a low amount of computation might be advisable. The present work provides such a simplified scalable computationally low-intensive technique for tool-path generation. From a three dimensional (3D) digital model, the presented algorithm extracts multiple two dimensional (2D) layers. Depending on the required resolution, each layer is converted to a spatial image, and an algebraic analytic closed-form solution provides a geometrical tool path in Cartesian coordinates. The produced tool paths are stacked after processing all object layers. Finally, the generated tool path is translated into a machine code using a G-code generator algorithm. The introduced technique was implemented and simulated using MATLAB® pseudocode with a G-code interpreter and a simulator. The results showed that the proposed technique produced an automated unsupervised reliable tool-path-generator algorithm and reduced tool wear and costs, by allowing the selection of the tool depth-of-cut as an input.

Evaluation and comparison of lubrication methods in finish machining of hardened steel mould inserts

2015 ◽  
Vol 231 (14) ◽  
pp. 2458-2467 ◽  
Author(s):  
Yuk Lun Chan ◽  
Xun Xu
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Minimum Quantity Lubrication ◽  
Hardened Steel ◽  
Depth Of Cut ◽  
Machining Time ◽  
Minimum Quantity ◽  
Step Over ◽  
Steel Mould

Traditionally, metal cutting fluid or lubricant is used in finishing operations of high-speed machining process to reduce the rate of tool wear, which in turn will improve surface quality. In automobile and aerospace industries, minimum quantity lubrication technique is considered to provide the same level of performance as the flood coolant method and offers financial benefits by saving coolant direct and associated costs. However, scant research work has been done on minimum quantity lubrication applications in the die and mould manufacturing industry. In this study, the effects of dry, flood and minimum quantity lubrication machining on surface roughness, tool wear, dimensional accuracy and machining time of hardened steel mould inserts were compared. The results revealed that there were no significant differences between these three lubrication methods. More in-depth experimental study of dry and minimum quantity lubrication machining was then carried out using the design of experiments technique. In terms of surface roughness and tool wear, there were again no significant differences. Nevertheless, minimum quantity lubrication machining produced more accurate results than dry machining in dimensional deviation. The regression models show that feed-rate ( fz) has a larger effect on surface roughness and machining time than step-over ( ae), while depth of cut ( ap) has no significant effect on surface roughness. Based on the test piece shape, a shortest possible machining time of 3.55 h and a good surface finish of 0.28 µm can be achieved using a small feed-rate (0.03 mm/tooth), a large step-over (0.1 mm) and a large depth of cut (0.2 mm). This work shows that when combining the minimum quantity lubrication technique with the right cutting conditions in modern die and mould manufacturing, machining time and polishing time can be saved, which leads to an overall saving in production cost. Using the dry and minimum quantity lubrication techniques for different finish machining situations can therefore be a good economical solution.

scholarly journals Numerical Control Machine Optimization Technologies through Analysis of Machining History Data Using Digital Twin

2021 ◽  
Vol 11 (7) ◽  
pp. 3259
Author(s):  
Eunyoung Heo ◽  
Namhyun Yoo
Keyword(s):  
Tool Wear ◽  
Tool Path ◽  
Tool Material ◽  
Numerical Control ◽  
Path Optimization ◽  
Machining Time ◽  
Tool Path Optimization ◽  
Digital Twin ◽  
Opposite Case ◽  
Nc Data

In numerical control (NC)-based machining, NC data-based tool paths affect both quality and productivity. NC data are generated according to cutting conditions. However, NC data causing excessive cutting load can accelerate tool wear and even result in tool damage. In the opposite case, increasing machining time can affect productivity. NC data can influence surface quality from the perspective of cutting dynamics according to machine tool–material-tool combination. There have been a lot of studies on tool-path optimization. However, it is impossible to perfectly predict cutting dynamics such as tool wear, material non-uniformity, chatter, and spindle deformation. In fact, such prediction-based tool-path optimization can cause errors. Therefore, this study attempts to synchronize spindle load and NC data and uniformize the machining load through the analysis of stored data using digital-twin technology, which stores and manages machining history. Uniformizing machining load can reduce rapid traverse in the event of no load, feed rate in an overload area, and shock on a tool when the tool and material are met by adding approach feed. Analyzing results of the attempts proposed in this paper, the chatter was completely removed in the machining with D100 and D16, although some chatter remained in the machining with D25 and D16R3 tools. In addition, the processing time could be reduced from a minimum of 7% to a maximum of 50% after optimization.

scholarly journals Using Uniform Design Methodology of Turning Parameters Study of Nickel Alloy

2021 ◽  
Author(s):  
Shao Hsien Chen ◽  
Chih-Hung Hsu
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Nickel Alloy ◽  
Cutting Tool ◽  
Design Method ◽  
Uniform Design ◽  
Machining Time ◽  
Variable Parameters ◽  
Set Up ◽  
Uniform Design Method

Abstract The nickel alloy has good mechanical strength and corrosion resistance at high temperature, it is extensively used in aerospace, biomedical and energy industries, as well as alloy designs of different chemical compositions to achieve different mechanical properties. However, for high mechanical strength, low thermal conductivity and surface hardening property, the nickel alloy has worse cutting tool life and machining efficiency than general materials. Therefore, how to select the optimum machining parameters will influence the workpiece quality, cost and machining time. For the selection of nickel alloy turning parameters, this paper uses uniform design method to design cutting test to reduce the number of experiments. Three independent variable parameters are set up, including cutting speed, feed motion and cutting depth, and four dependent variable parameters are set up, including cutting tool wear, surface roughness, machining time and cutting force. A nickel alloy turning parameter model is built by using regression analysis to further predict the I/O relationship among various combinations of variables. The errors between actual values and prediction values are validated. When the cutting tool wear (VB) is 2.72~6.18%, the surface roughness (Ra) is 4.10~7.72%, the machining time (T) is 3.75~8.82%, and the cutting force (N) is 1.54~7.42%, the errors of various dependent variables are approximately less than 10%, so a high precision estimation model is obtained through a few experiments of uniform design method.

Assessment of tool path strategies for milling complex surfaces in hardened H13 steel

2018 ◽  
Vol 233 (3) ◽  
pp. 834-849 ◽  
Author(s):  
Laurence Colares Magalhães ◽  
Joao Carlos Espindola Ferreira
Keyword(s):  
Surface Roughness ◽  
Tool Path ◽  
Complex Geometry ◽  
Complex Surface ◽  
Cutting Conditions ◽  
H13 Steel ◽  
Machining Time ◽  
Tool Paths ◽  
Geometric Precision ◽  
Geometric Deviations

In this work, parts with complex geometry were machined in hardened H13 steel using different tool path strategies for roughing and finishing, seeking to evaluate how the tool paths and cutting conditions influence machining time, surface roughness, and geometric precision. The results showed a reduction of up to 7.8% in roughing time and 25% reduction in finishing time among the evaluated tool paths. The roughness of the complex surface depends significantly on the tool path used and is significantly impaired by the increase in the feed per tooth. The geometric deviations varied from 0.02 to 0.23 mm depending on the adopted tool path.

Relationship of Pocket Geometry and Tool Path Strategy with 2 1/2-D Milling Parameters: Machining Time, Cutting Forces and Surface Roughness

2014 ◽  
Vol 797 ◽  
pp. 78-83
Author(s):  
Pablo Eduardo Romero ◽  
Ruben Dorado ◽  
Francisco Alberto Díaz Garrido ◽  
Eva María Rubio
Keyword(s):  
Surface Roughness ◽  
Cutting Forces ◽  
Tool Path ◽  
Machining Time ◽  
Milling Parameters ◽  
Relationship Of ◽  
The Relationship

2 1/2-D pocketing is an important operation in aeronautic and automotive industries. In the present paper, it is studied the relationship among the pocket geometry and the tool path strategy chosen with interesting parameters as: machining time, cutting forces and surface roughnes. The pocketing tests have been performed on UNS A96063, an increasingly frequent alloy in such industries.

scholarly journals EFFECT OF AIR JET COOLING ON SURFACE ROUGHNESS AND TOOL WEAR

2012 ◽  
Vol 1 (2) ◽  
Author(s):  
Paryanto Rusnaldy Dan Tony S. Utomo
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Machining Process ◽  
Turning Process ◽  
Machining Time ◽  
Jet Cooling ◽  
Air Jet ◽  
Increase Surface Roughness ◽  
Cooling Effects ◽  
Selection Of

The main goal of this work is to investigate the use of air jet cooling on machining process. Surface roughnessand tool are chosen as parameter to analyze of air jet cooling effects; and turning process with AISI 1010 materialused in the experimental study. Surface roughness was measured for several air jet pressures and in two air jetpositions. Every five minutes of machining time, tool wear was measured until reach 30 minutes. Initial resultsshow that the use of air jet cooling with proper selection of position and pressure; possible to reduce tool wear andto increase surface roughness.

Effect of SiC-Cu Electrode on Material Removal Rate, Tool Wear and Surface Roughness in EDM Process

2020 ◽  
Vol 38 (9A) ◽  
pp. 1406-1413
Author(s):  
Yousif Q. Laibia ◽  
Saad K. Shather
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
304 Stainless Steel ◽  
Tool Electrode ◽  
Pulse Time ◽  
Edm Process

Electrical discharge machining (EDM) is one of the most common non-traditional processes for the manufacture of high precision parts and complex shapes. The EDM process depends on the heat energy between the work material and the tool electrode. This study focused on the material removal rate (MRR), the surface roughness, and tool wear in a 304 stainless steel EDM. The composite electrode consisted of copper (Cu) and silicon carbide (SiC). The current effects imposed on the working material, as well as the pulses that change over time during the experiment. When the current used is (8, 5, 3, 2, 1.5) A, the pulse time used is (12, 25) μs and the size of the space used is (1) mm. Optimum surface roughness under a current of 1.5 A and the pulse time of 25 μs with a maximum MRR of 8 A and the pulse duration of 25 μs.

scholarly journals Deep Learning Approach for Vibration Signals Applications

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3929
Author(s):  
Han-Yun Chen ◽  
Ching-Hung Lee
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Parameters Optimization ◽  
Frequency Spectra ◽  
Vibration Signals ◽  
Bearing Faults ◽  
Time Frequency ◽  
And Performance ◽  
The One ◽  
Short Time

This study discusses convolutional neural networks (CNNs) for vibration signals analysis, including applications in machining surface roughness estimation, bearing faults diagnosis, and tool wear detection. The one-dimensional CNNs (1DCNN) and two-dimensional CNNs (2DCNN) are applied for regression and classification applications using different types of inputs, e.g., raw signals, and time-frequency spectra images by short time Fourier transform. In the application of regression and the estimation of machining surface roughness, the 1DCNN is utilized and the corresponding CNN structure (hyper parameters) optimization is proposed by using uniform experimental design (UED), neural network, multiple regression, and particle swarm optimization. It demonstrates the effectiveness of the proposed approach to obtain a structure with better performance. In applications of classification, bearing faults and tool wear classification are carried out by vibration signals analysis and CNN. Finally, the experimental results are shown to demonstrate the effectiveness and performance of our approach.

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