scholarly journals Methods of comparison of surface texture based on fractal dimension and Hotelling’s T2 test

2019 ◽  
Vol 19 (4) ◽  
pp. 82-90
Author(s):  
Damian GOGOLEWSKI
Keyword(s):  
Fractal Dimension ◽  
Surface Texture ◽  
Statistical Tests ◽  
Milling Process ◽  
Face Milling ◽  
Machining Parameters ◽  
Hotelling's T2 ◽  
Hotelling’S T2 ◽  
Machine Parts ◽  
Hotelling’S T2 Test

Comparative analysis of the surface texture of machine parts can be successfully carried out using statistical tests. The paper presents a methodology of method used to compare the surface texture by applying Hotelling’s T2 test as well as a method used to evaluate surface topography by applying fractal dimension. The tests were carried out on samples produced with the use of face milling process for four types of materials. The following types of steel were used: 40HM, C45, NC6 and WCL. For each type of material, four areas were machined with the same machining parameters. Based on these results a decision was made whether the surfaces, despite the same machining conditions, were significantly different from each other. Furthermore, the analysis indicated that the fractal dimension enabled to characterise signal irregularities in quantitative and qualitative way.

High Definition Metrology-Based Quality Improvement of Surface Texture in Face Milling of Workpieces with Discontinuous Surfaces

2021 ◽  
pp. 1-38
Author(s):  
Guilong Li ◽  
Shichang Du ◽  
Bo Wang ◽  
Jun Lv ◽  
Yafei Deng
Keyword(s):  
Quality Improvement ◽  
Surface Texture ◽  
Mechanical Performance ◽  
Processing Parameters ◽  
Milling Process ◽  
Face Milling ◽  
Measurement Instruments ◽  
High Definition ◽  
Tool Marks

Abstract In face milling process, the quality of surface texture is vital for mechanical performance of workpieces. The quality of surface texture, especially for waviness, is directly affected by tool marks, a commonly observed phenomenon in face milling. However, appropriate approaches for evaluation and modeling of tool marks are absent to date. Limited to the resolution as well as the efficiency of conventional measurement instruments, the height data of tool marks is hard to be entirely obtained, leading to valuable information omission. Besides, most existing models of tool marks are established for general workpieces with regular geometry and continuous surfaces. Since the cutter-workpiece engagement mode has a significant impact on the generation of tool marks, current models could be inaccurate or invalid when dealing with workpieces with discontinuous surfaces. To overcome this shortage, a novel approach is proposed in this paper, aimed at quality improvement of surface texture in face milling of workpieces with discontinuous surfaces. Firstly, the evaluation indexes for tool marks are defined based on the recently developed high definition metrology (HDM). Secondly, the physical modeling of tool marks is presented, taking the face milling mechanism into account. Thirdly, the physical-informed optimization model is developed to search for the optimal processing parameters for surface quality improvement. At last, the effectiveness of the proposed approach is verified by a face milling experiment on the engine blocks.

scholarly journals Research and Optimization of Surface Roughness in Milling of SLM Semi-Finished Parts Manufactured by Using the Different Laser Scanning Speed

Materials ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 9 ◽  
Author(s):  
Andrzej Matras
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Laser Scanning ◽  
Cutting Tool ◽  
Scanning Speed ◽  
Milling Process ◽  
Face Milling ◽  
Machining Parameters ◽  
The Face ◽  
Laser Scanning Speed

The paper studies the potential to improve the surface roughness in parts manufactured in the Selective Laser Melting (SLM) process by using additional milling. The studied process was machining of samples made of the AlSi10Mg alloy powder. The simultaneous impacts of the laser scanning speed of the SLM process and the machining parameters of the milling process (such as the feed rate and milling width) on the surface roughness were analyzed. A mathematical model was created as a basis for optimizing the parameters of the studied processes and for selecting the sets of optimum solutions. As a result of the research, surface with low roughness (Ra = 0.14 μm, Rz = 1.1 μm) was obtained after the face milling. The performed milling allowed to reduce more than 20-fold the roughness of the SLM sample surfaces. The feed rate and the cutting width increase resulted in the surface roughness deterioration. Some milled surfaces were damaged by the chip adjoining to the rake face of the cutting tool back tooth.

A Study of Multivariate Permutation Tests Which May Replace Hotelling's T2 Test in Prescribed Circumstances

1994 ◽  
Vol 29 (2) ◽  
pp. 141-163 ◽  
Author(s):  
R. Clifford Blair ◽  
James J. Higgins ◽  
Walt Karniski ◽  
Jeffrey D. Kromrey
Keyword(s):  
Permutation Tests ◽  
Hotelling's T2 ◽  
Hotelling’S T2 ◽  
Hotelling’S T2 Test

scholarly journals Heteroscedasticity in a two-factors design model

2013 ◽  
Vol 23 (3) ◽  
pp. 14-19
Author(s):  
Oscar Alejandro Martínez Jaime ◽  
José Antonio Díaz García
Keyword(s):  
Confidence Intervals ◽  
Real Life ◽  
Design Model ◽  
Simultaneous Confidence Intervals ◽  
Hotelling's T2 ◽  
Two Factors ◽  
Hotelling’S T2 ◽  
Main Effects ◽  
Hotelling’S T2 Test

This paper studies the two-factors design model when the heteroscedasticity of variance is present in errors. As can be observed, testing of hypothesis based on the main effects for this design model can be performed using Hotelling's T2 test. Simultaneous confidence intervals are also proposed. Finally, the proposed methodology is applied to a real-life example.

Evaluation of Face Milling Operation Parameters on Surface Roughness of Crankcase Housing by Two Level Factorial Design with Center Points

2018 ◽  
Vol 780 ◽  
pp. 105-110
Author(s):  
Ukrit Thanasuptawee ◽  
Chamrat Thakhamwang ◽  
Somsak Siwadamrongpong
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Milling Process ◽  
Face Milling ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Significance Level ◽  
Machining Center ◽  
Semi Solid

In this study, there are three machining parameters consist of spindle speed, feed rate and depth of cut which were conducted through full factorial with four center points to determine the effect of machining parameters on the surface roughness and verify whether there is curvature in the model for CNC face milling process in an automotive components manufacturer in Thailand. The workpieces used semi-solid die casted ADC12 aluminum alloy crankcase housing which they were performed by the ARES SEIKI model R5630 3-axis CNC vertical machining center and face milling cutter with diameter of 63 millimeters. The surface roughness of face-milled was measured by the surface roughness tester. It was found that the greatest main effect influence to surface roughness was spindle speed, followed by feed rate and depth of cut at significance level of 0.05.

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