Co-Kriging Method for Form Error Estimation Incorporating Condition Variable Measurements

2015 ◽  
Vol 138 (4) ◽  
Author(s):  
Shichang Du ◽  
Lan Fei
Keyword(s):  
Spatial Correlation ◽  
Spatial Statistics ◽  
Error Estimation ◽  
Surface Form ◽  
Form Error ◽  
Machining Processes ◽  
Machining Conditions ◽  
Machining Errors ◽  
Part Surface ◽  
Cross Variogram

The form error estimation under various machining conditions is an essential step in the assessment of product surface quality generated in machining processes. Coordinate measuring machines (CMMs) are widely used to measure complicated surface form error. However, considering measurement cost, only a few measurement points are collected offline by a CMM for a part surface. Therefore, spatial statistics is adopted to interpolate more points for more accurate form error estimation. It is of great significance to decrease the deviation between the interpolated height value and the real one. Compared to univariate spatial statistics, only concerning spatial correlation of height value, this paper presents a method based on multivariate spatial statistics, co-Kriging (CK), to estimate surface form error not only concerning spatial correlation but also concerning the influence of machining conditions. This method can reconstruct a more accurate part surface and make the estimation deviation smaller. It characterizes the spatial correlation of machining errors by variogram and cross-variogram, and it is implemented on one of the common features: flatness error. Simulated datasets as well as actual CMM data are applied to demonstrate the improvement achieved by the proposed multivariate spatial statistics method over the univariate method and other interpolation methods.

scholarly journals Form Error Estimation Using Spatial Statistics

1999 ◽  
Vol 122 (1) ◽  
pp. 262-272 ◽  
Author(s):  
Tai-Hung Yang ◽  
John Jackman
Keyword(s):  
Error Estimates ◽  
Statistical Methods ◽  
Spatial Statistics ◽  
Error Estimation ◽  
Manufacturing Processes ◽  
Form Error ◽  
Essential Step ◽  
Large Sets ◽  
Uniform Sample ◽  
Estimate Form

Form error estimation is an essential step in the assessment of product geometry created through one or more manufacturing processes. We present a new method using spatial statistics to estimate form error. Using large sets of uniform sample points measured from five common machined surfaces, we compare the form error estimates using individual points and fitted surfaces obtained through spatial statistical methods. The results show that spatial statistics can provide more accurate estimates of form error under certain conditions. [S1087-1357(00)01701-9]

scholarly journals Experimental Study on the Influence of Machining Conditions on the Quality of Electrical Discharge Machined Surfaces of aluminum alloy Al5052

Machines ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 12 ◽  
Author(s):  
Angelos P. Markopoulos ◽  
Emmanouil-Lazaros Papazoglou ◽  
Panagiotis Karmiris-Obratański
Keyword(s):  
Aluminum Alloy ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
White Layer ◽  
Machining Parameters ◽  
Machining Processes ◽  
Machining Conditions ◽  
Pulse On Time ◽  
Machined Surfaces

Although electrical discharge machining (EDM) is one of the first established non-conventional machining processes, it still finds many applications in the modern industry, due to its capability of machining any electrical conductive material in complex geometries with high dimensional accuracy. The current study presents an experimental investigation of ED machining aluminum alloy Al5052. A full-scale experimental work was carried out, with the pulse current and pulse-on time being the varying machining parameters. The polishing and etching of the perpendicular plane of the machined surfaces was followed by observations and measurements in optical microscope. The material removal rate (MRR), the surface roughness (SR), the average white layer thickness (AWLT), and the heat affected zone (HAZ) micro-hardness were calculated. Through znalysis of variance (ANOVA), conclusions were drawn about the influence of machining conditions on the EDM performances. Finally, semi empirical correlations of MRR and AWLT with the machining parameters were calculated and proposed.

scholarly journals Theoretical Study of Path Adaptability Based on Surface Form Error Distribution in Fluid Jet Polishing

2018 ◽  
Vol 8 (10) ◽  
pp. 1814 ◽  
Author(s):  
Yanjun Han ◽  
Lei Zhang ◽  
Cheng Fan ◽  
Wule Zhu ◽  
Anthony Beaucamp
Keyword(s):  
Material Removal ◽  
Bulk Material ◽  
Critical Evaluation ◽  
Error Distribution ◽  
Residual Error ◽  
Polished Surface ◽  
Surface Form ◽  
Optimization Strategy ◽  
Form Error ◽  
The Difference

In the technology of computer-controlled optical surfacing (CCOS), the convergence of surface form error has a close relationship with the distribution of surface form error, the calculation of dwell time, tool influence function (TIF) and path planning. The distribution of surface form error directly reflects the difference in bulk material removal depth across a to-be-polished surface in subsequent corrective polishing. In this paper, the effect of path spacing and bulk material removal depth on the residual error have been deeply investigated based on basic simulation experiments excluding the interference factors in the actual polishing process. With the relationship among the critical evaluation parameters of the residual error (root-mean-square (RMS) and peak-to-valley (PV)), the path spacing and bulk material removal depth are mathematically characterized by the proposed RMS and PV maps, respectively. Moreover, a variable pitch path self-planning strategy based on the distribution of surface form error is proposed to optimize the residual error distribution. In the proposed strategy, the influence of different bulk material removal depths caused by the distribution of surface form error on residual error is compensated by fine adjustment of the path spacing according to the obtained path spacing optimization models. The simulated experimental results demonstrate that the residual error optimization strategy proposed in this paper can significantly optimize the overall residual error distribution without compromising the convergence speed. The optimized residual error distribution obtained in sub-regions of the polished surface is more uniform than that without optimization and is almost unaffected by the distribution of parent surface form error.

Machining Conditions Effect to Machining Temperature and Forces in Orthogonal Machining of Bone

2013 ◽  
Vol 658 ◽  
pp. 223-226 ◽  
Author(s):  
Denni Kurniawan ◽  
N. Jiawkok ◽  
M.Y. Noordin
Keyword(s):  
Analytical Study ◽  
Cutting Speed ◽  
Tool Geometry ◽  
Depth Of Cut ◽  
Machining Processes ◽  
Allowable Limit ◽  
Machining Conditions ◽  
Orthogonal Machining ◽  
Dental Implantation ◽  
Cutting Direction

Bone machining processes are often performed in orthopaedic surgery and dental implantation, yet its analytical study is lacking. Towards contributing analysis on bone machining, this study reviews available references on orthogonal machining of bones. Considering the allowable limit in temperature and duration during bone machining to avoid thermal necrosis, machining temperature and forces are the machining responses of interest. Machining conditions (cutting speed, depth of cut, cooling method, tool geometry, and cutting direction) are analyzed in term of their effect to those machining responses.

Surface Texture and Machining Conditions. Part 1: Model Building Logic in View of Process Control

1983 ◽  
Vol 105 (4) ◽  
pp. 259-263 ◽  
Author(s):  
A. Villa ◽  
S. Rossetto ◽  
R. Levi
Keyword(s):  
Process Control ◽  
Surface Texture ◽  
Model Building ◽  
Surface Profile ◽  
Cutting Parameters ◽  
Tool Geometry ◽  
Machining Processes ◽  
Tool Marks ◽  
Machining Conditions ◽  
Cutting Processes

Surface texture generation in machining processes is examined in view of establishing a model building procedure capable of linking surface finish parameters to machining conditions. In the first part of the paper, with reference to cutting processes with defined tool geometry, a model capable of describing a surface profile as an ordered sequence of tool marks is developed. The use of such a model for process control is also discussed. In the second part, the identification procedure of a model describing profile generation in face milling versus cutting parameters is presented.

Optimal Tool Orientation for Five-Axis Tool-End Machining by Swept Envelope Approach

2004 ◽  
Author(s):  
John C. J. Chiou ◽  
Yuan-Shin Lee
Keyword(s):  
Tool Path ◽  
Tool Orientation ◽  
Error Sources ◽  
Part Geometry ◽  
Machining Errors ◽  
Nc Simulation ◽  
Part Surface ◽  
Tool Motion ◽  
Five Axis ◽  
Cutting Direction

This paper presents a swept envelope approach to determining the optimal tool orientation for five-axis tool-end machining. The swept profile of the cutter is determined based on the tool motion. By analyzing the swept profile against the part geometry, four types of machining errors (local gouge, side gouge, rear gouge, and global collision) are identified. The tool orientation is then corrected to avoid such errors. The cutter’s swept envelope is further constructed by integrating the intermediate swept profiles, and can be applied to NC simulation and verification. This paper presents the explicit solution for the swept profile of a general cutter in five-axis tool-end machining. The relation of the swept profile, the part geometry, the tool motion, and the machining errors is developed. Therefore, the error sources can be detected early and prevented during tool path planning. The analytical results indicate that the optimal tool orientation occurs when the curvature of the cutter’s swept profile matches with the curvature of the local part surface. In addition, the optimal cutting direction generally follows the minimum curvature direction. Computer illustrations and example demonstrations are shown in this paper. The results reveal the developed method can accurately determine the optimal tool orientation and efficiently avoid machining errors for five-axis tool-end machining.

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