Surface roughness optimization in laser machining of stainless steel 304 using response surface methodology

Author(s):  
Vikas B. Magdum ◽  
Jayant K. Kittur ◽  
Sachin C. Kulkarni
2017 ◽  
Vol 15 (3) ◽  
pp. 283-296 ◽  
Author(s):  
Aezhisai Vallavi Muthusamy Subramanian ◽  
Mohan Das Gandhi Nachimuthu ◽  
Velmurugan Cinnasamy

2015 ◽  
Vol 15 (3) ◽  
pp. 293-300 ◽  
Author(s):  
Nandkumar N. Bhopale ◽  
Nilesh Nikam ◽  
Raju S. Pawade

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.


Author(s):  
TS Senthilkumar ◽  
R Muralikannan ◽  
T Ramkumar ◽  
S Senthil Kumar

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.


2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Ekhaesomi A Agbonoga ◽  
Oyewole Adedipe ◽  
Uzoma G Okoro ◽  
Fidelis J Usman ◽  
Kafayat T Obanimomo ◽  
...  

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


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