Effects of high speed in the drilling of glass whisker-reinforced polyamide composites (PA66 GF30): statistical analysis of the roughness parameters

2010 ◽  
Vol 45 (13) ◽  
pp. 1395-1402 ◽  
Author(s):  
J. Campos Rubio ◽  
T.H. Panzera ◽  
A.M. Abrao ◽  
Paulo E. Faria ◽  
J. Paulo Davim
Author(s):  
Muataz Al Hazza ◽  
Khadijah Muhammad

High speed machining has many advantages in reducing time to the market by increasing the material removal rate. However, final surface quality is one of the main challenges for manufacturers in high speed machining due to the increasing of flank wear rate. In high speed machining, the cutting zone is under high pressure associated with high temperature that lead to increasing of the flank wear rate in which affect the final quality of the machined surface. Therefore, one of the main concerns to the manufacturer is to predict the flank wear to estimate and predict the surface roughness as one of the main outputs of the machining processes. The aim of this study is to determine experimentally the optimum cutting parameters: depth of cut, cutting speed (Vc) and feed rate (f) that maintaining low flank wear (Vb). Taguchi method has been applied in this experiment. The Taguchi method has been universally used in engineering analysis.  JMP statistical analysis software is used to analyse statically the development of flank wear rate during high speed milling of hardened steel AISI D2 to 60 HRD. The experiment was conducted in the following boundaries: cutting speed 200-400 m/min, feed rate of 0.01-0.05 mm/tooth and depth of cut of 0.1-0.2 mm. Analysis of variance ANOVA was conducted as one of important tool for statistical analysis. The result showed that cutting speed is the most influential input factors with 70.04% contribution on flank wear.


2019 ◽  
Vol 973 ◽  
pp. 166-169
Author(s):  
Sergey I. Agapov ◽  
Yuriy I. Sidyakin ◽  
Oleg F. Korpelyanskiy

This article investigates the impact that the rake and rear faces of the drill made from high-speed steels of grade P6M5 and grinded by ultrasonic techniques imposes on the roughness of the holes being machined. The experiment showed that microgeometry of the tool sharpened by transmitting ultrasonic impulses into the zone of regrinding featured lower roughness; moreover, roughness parameters of the drilled holes were also improved.


2017 ◽  
Vol 6 (3) ◽  
pp. 16-22 ◽  
Author(s):  
Satish K. Mandlik ◽  
Nisharani S. Ranpise

The present study investigated the implementation of 32 factorial design of experiment and statistical analysis for the optimization of chitosan nanoparticles containing zolmitriptan an antimigraine drug. The influence of chitosan concentration (X1) and sodium tripoly phosphate (X2) on responses namely nanoparticle size (Y1), and entrapment efficiency (Y2), was studied. As per design, nine runs of nanoparticles were prepared by modified ionic gelation method using high speed vortex mixing. The particle size was found in the range of 151-880 nm and entrapment efficiency was 72.3-81.2%. A statistical analysis was performed using licensed design expert software V.8.0 with respect to ANOVA, regression analysis. The contour plots and response surface plots showed visual representation of relationship between the experimental responses and the set of independent variables. Regression model equations were validated by a numerical and graphical optimization method. Further, optimized drug loaded nanoparticles showed +23.7mV zeta potential indicating storage stability, electron micrograph reflects spherical shape and mixed type of drug release followed by Fickian diffusion (n=0.266) was observed. Thus, using systematic factorial design approach, desirable goals can be achieved in shortest possible time with lesser number of experiments which was proven to be an effective tool in quality by design.Mandlik and Ranpise, International Current Pharmaceutical Journal, February 2017, 6(3): 16-22http://www.icpjonline.com/documents/Vol6Issue3/01.pdf


Materials ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 617 ◽  
Author(s):  
Ireneusz Zagórski ◽  
Jarosław Korpysa

Surface roughness is among the key indicators describing the quality of machined surfaces. Although it is an aggregate of several factors, the condition of the surface is largely determined by the type of tool and the operational parameters of machining. This study sought to examine the effect that particular machining parameters have on the quality of the surface. The investigated operation was the high-speed dry milling of a magnesium alloy with a polycrystalline diamond (PCD) cutting tool dedicated for light metal applications. Magnesium alloys have low density, and thus are commonly used in the aerospace or automotive industries. The state of the Mg surfaces was assessed using the 2D surface roughness parameters, measured on the lateral and the end face of the specimens, and the end-face 3D area roughness parameters. The description of the surfaces was complemented with the surface topography maps and the Abbott–Firestone curves of the specimens. Most 2D roughness parameters were to a limited extent affected by the changes in the cutting speed and the axial depth of cut, therefore, the results from the measurements were subjected to statistical analysis. From the data comparison, it emerged that PCD-tipped tools are resilient to changes in the cutting parameters and produce a high-quality surface finish.


2010 ◽  
Vol 158 (4) ◽  
pp. 71-83
Author(s):  
Adam DRYHUSZ ◽  
Kazimierz KOWALSKI

The maintenance system of high-speed military tracked vehicles and the graphic original interpretation of maintenance activity (mainly maintenance) are described. A modification of the maintenance system of the above-mentioned vehicles based on dependability-oriented maintenance (Reliability Cantered Maintenance – RCM) is proposed. Additionally, the use of the statistical analysis of maintenance cases and the development of Computerised Maintenance Management System – CMMC are proposed as well.


Sedimentology ◽  
2008 ◽  
Vol 55 (2) ◽  
pp. 461-470 ◽  
Author(s):  
DAWEI WANG ◽  
YUAN WANG ◽  
BIN YANG ◽  
WEI ZHANG

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