Computer Vision Based Non-contact Surface Roughness Assessment Using Wavelet Transform and Response Surface Methodology

2005 ◽  
Vol 17 (3) ◽  
pp. 435-451 ◽  
Author(s):  
Shing I. Chang ◽  
Jayakumar S. Ravathur
Keyword(s):  
Computer Vision ◽  
Surface Roughness ◽  
Response Surface Methodology ◽  
Wavelet Transform ◽  
Response Surface ◽  
Contact Surface ◽  
Roughness Assessment

scholarly journals Assessment of cutting force and surface roughness in LM6/SiC p using response surface methodology

2017 ◽  
Vol 15 (3) ◽  
pp. 283-296 ◽  
Author(s):  
Aezhisai Vallavi Muthusamy Subramanian ◽  
Mohan Das Gandhi Nachimuthu ◽  
Velmurugan Cinnasamy
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Cutting Force ◽  
Response Surface

Parameter Optimization of Ball End Milling Process on Inconel 718 Using RSM and TLBO Algorithm

2015 ◽  
Vol 15 (3) ◽  
pp. 293-300 ◽  
Author(s):  
Nandkumar N. Bhopale ◽  
Nilesh Nikam ◽  
Raju S. Pawade
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Surface Integrity ◽  
Inconel 718 ◽  
Tool Path ◽  
End Milling ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Ball End Milling

AbstractThis paper presents the application of Response Surface Methodology (RSM) coupled with Teaching Learning Based Optimization Technique (TLBO) for optimizing surface integrity of thin cantilever type Inconel 718 workpiece in ball end milling. The machining and tool related parameters like spindle speed, milling feed, axial depth of cut and tool path orientation are optimized with considerations of multiple response like deflection, surface roughness, and micro hardness of plate. Mathematical relationship between process parameters and deflection, surface roughness and microhardness are found out by using response surface methodology. It is observed that after optimizing the process that at the spindle speed of 2,000 rpm, feed 0.05 mm/tooth/rev, plate thickness of 5.5 mm and 15° workpiece inclination with horizontal tool path gives favorable surface integrity.

Studies of kerf width and surface roughness using the response surface methodology in AA 4032–TiC composites

2021 ◽  
pp. 095440892110414
Author(s):  
TS Senthilkumar ◽  
R Muralikannan ◽  
T Ramkumar ◽  
S Senthil Kumar
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Matrix ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Kerf Width ◽  
Wire Electrical Discharge Machining ◽  
Box Behnken Design ◽  
Pulse On Time

A substantially developed machining process, namely wire electrical discharge machining (WEDM), is used to machine complex shapes with high accuracy. This existent work investigates the optimization of the process parameters of wire electrical discharge machining, such as pulse on time ( Ton), peak current ( I), and gap voltage ( V), to analyze the output performance, such as kerf width and surface roughness, of AA 4032–TiC metal matrix composite using response surface methodology. The metal matrix composite was developed by handling the stir casting system. Response surface methodology is implemented through the Box–Behnken design to reduce experiments and design a mathematical model for the responses. The Box–Behnken design was conducted at a confident level of 99.5%, and a mathematical model was established for the responses, especially kerf width and surface roughness. Analysis of variance table was demarcated to check the cogency of the established model and determine the significant process. Surface roughness attains a maximum value at a high peak current value because high thermal energy was released, leading to poor surface finish. A validation test was directed between the predicted value and the actual value; however, the deviation is insignificant. Moreover, a confirmation test was handled for predicted and experimental values, and a minimal error was 2.3% and 2.12% for kerf width and surface roughness, respectively. Furthermore, the size of the crater, globules, microvoids, and microcracks were increased by amplifying the pulse on time.

scholarly journals Effect of Process Parameters on the Surface Roughness and Kerf Width of Mild Steel during Plasma Arc Cutting Using Response Surface Methodology

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Ekhaesomi A Agbonoga ◽  
Oyewole Adedipe ◽  
Uzoma G Okoro ◽  
Fidelis J Usman ◽  
Kafayat T Obanimomo ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Analysis Of Variance ◽  
Process Parameters ◽  
Cutting Speed ◽  
Gas Pressure ◽  
Kerf Width ◽  
Plasma Arc ◽  
Plasma Arc Cutting

This study investigated the effects of process parameters of plasma arc cutting (PAC) of low carbon steel material using analysis of variance. Three process parameters, cutting speed, cutting current and gas pressure were considered and experiments were conducted based on response surface methodology (RSM) via the box-Behnken approach. Process responses viz. surface roughness (Ra) and kerf width of cut surface were measured for each experimental run. Analysis of Variance (ANOVA) was performed to get the contribution of process parameters on responses. Cutting current has the most significant effect of 33.43% on the surface roughness and gas pressure has the most significant effect on  kerf width of  41.99% . For minimum surface roughness and minimum kerf width, process parameters were optimized using the RSM. Keywords: Cutting speed, cutting current, gas pressure,   surface roughness, kerf width

Experiment and Surface Roughness Prediction Model for Ti-6Al-4V in Abrasive Belt Grinding

2016 ◽  
Vol 1136 ◽  
pp. 42-47 ◽  
Author(s):  
Ya Xiong Chen ◽  
Yun Huang ◽  
Gui Jian Xiao ◽  
Gui Lin Chen ◽  
Zhi Wu Liu ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Great Influence ◽  
Grinding Force ◽  
Work Piece ◽  
Belt Grinding ◽  
Abrasive Belt ◽  
Belt Speed ◽  
Feeding Speed

In abrasive belt grinding, abrasive belt granularity, abrasive belt speed,feeding speed and grinding force have a great influence on the surface roughness. In order to predicate the surface roughness of Ti-6Al-4V,a response surface methodology are used to build the model to predict surface roughness,and the influence of various parameters on surface roughness was analysed. The research shows that with the abrasive belt granularity and abrasive belt speed increasing,the work piece surface roughness decreases;with the grinding force and feeding speed increasing,the work piece surface roughness increases. Through the test,the response surface methodology with high prediction accuracy,provides a theoretical basis for the reasonable selection of abrasive belt grinding parameters.

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