Predicting Tool Wear Using Linear Response Surface Methodology and Gaussian Process Regression

2020 ◽  
pp. 283-286
Author(s):  
Chandula T. Wickramarachchi ◽  
Timothy J. Rogers ◽  
Wayne Leahy ◽  
Elizabeth J. Cross
Keyword(s):  
Response Surface Methodology ◽  
Tool Wear ◽  
Gaussian Process ◽  
Response Surface ◽  
Linear Response ◽  
Gaussian Process Regression

ASSESSING THE TRIBOLOGICAL PROPERTIES OF VEGETABLE OIL EMULSIONS AND MACHINING PARAMETER OPTIMIZATION USING RESPONSE SURFACE METHODOLOGY

2021 ◽  
Author(s):  
D. K. KARUPANNASAMY ◽  
M. SAMBATHKUMAR ◽  
R. GUKENDRAN ◽  
K. S. K. SASIKUMAR ◽  
N. BAASKARAN ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Tool Wear ◽  
Response Surface ◽  
Surface Finish ◽  
Castor Oil ◽  
Mineral Oil ◽  
Machining Process ◽  
Neem Oil ◽  
Machining Performance ◽  
Oil Emulsions

Bio-degradable lubricants are the need for industries to promote eco-friendly manufacturing process and protect the workers from health hazards. In this paper, the use of oil–water emulsions from the bio-substitute oils have been formulated and its process parameter on a machining process are optimized using response surface methodology. The emulsions are prepared from the vegetable oils such as castor, mahua, palm and neem oil with polysorbate as emulsifying agent. The friction and wear characteristics are studied with a standard pin on disc tribometer for all the emulsions prepared with the base oils namely castor, mahua and palm oil. From the tribological characterization tests, the castor oil emulsions have shown better performance and stability in comparison to other oils. Hence, castor oil emulsions have been tested for its machining performance studies against a conventional mineral oil emulsion in a turning process. Further, an emulsion based on castor oil and neem oil have been tested for tool wear to utilize the antimicrobial properties of neem oil for reducing the bio fouling effects. The machining performance is indicated based on the surface finish and tool wear. Response surface methodology have been used for optimization of the machining parameters, such as cutting velocity, feed rate and depth of cut to achieve an optimal surface finish for a maximum material removal rate. The results show that the castor oil based emulsion can be used as an excellent alternative for mineral oil emulsions.

Gaussian process regression for tool wear prediction

2018 ◽  
Vol 104 ◽  
pp. 556-574 ◽  
Author(s):  
Dongdong Kong ◽  
Yongjie Chen ◽  
Ning Li
Keyword(s):  
Tool Wear ◽  
Gaussian Process ◽  
Gaussian Process Regression ◽  
Wear Prediction ◽  
Tool Wear Prediction
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