Experimental study on the surface roughness of dry turning of hardened steel

2011 ◽  
Author(s):  
Xiaoguang Wang ◽  
Junlan Cheng ◽  
Tianyan Ma ◽  
Deping Zhang
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Hardened Steel ◽  
Dry Turning

Surface Roughness Predictive Model of UNS A97075 Aluminum Pieces Obtained by Dry Turning Tests Based on the Cutting Forces

2012 ◽  
Vol 217-219 ◽  
pp. 1628-1635 ◽  
Author(s):  
Beatriz De Agustina ◽  
Eva María Rubio ◽  
Miguel Ángel Sebastián
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Predictive Model ◽  
Cutting Forces ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Dry Turning ◽  
Frequency Domains ◽  
Range Of Values ◽  
Roughness Measurements

The present work shows an experimental study for a first approach of a surface roughness predictive model of UNS A97075 aluminum pieces obtained by dry turning tests based on the cutting forces. In a first step, a design of experiments (DOE) 25 was employed to analyse the influence of the cutting parameters and type of tool on the surface roughness with the objective to find out a combination of cutting conditions that allow obtaining a range of values of surfaces roughness according to the aeronautical specifications requierements. The factors considered for this design were the feed rate, spindle speed, depth of cut, type of tool (nose radious) and machined length (zone of the workpiece where the surface roughness measurements are taken). The obtained data was analysed by means of the analysis of variance (ANOVA) method. And secondly, with the previous selected conditions selected it was developed by multiple regression a model to predict the surface roughness by measuring the cutting forces generated during the dry turning tests of aluminum alloy UNS A97075 pieces. The predictive model of surface roughness obtained includes statistical values calculated from the forces sygnal in time and frequency domains.

Research on the Predicted Model of the Surface Roughness in Dry Turning Hardened Steel

2011 ◽  
Vol 337 ◽  
pp. 363-367 ◽  
Author(s):  
Chun Juan Tu ◽  
Xiao Gu
Keyword(s):  
Surface Roughness ◽  
Cubic Boron Nitride ◽  
Cutting Temperature ◽  
Mathematic Model ◽  
Cutting Parameters ◽  
Pso Algorithm ◽  
Hardened Steel ◽  
Dominant Factor ◽  
Dry Turning ◽  
Roughness Prediction

Researching on the mathematic model of surface roughness in machining hardened steel was to provide the reference for the surface roughness prediction. The contrast experiments of dry turning hardened steel were carried out with ceramic tool (CC6050), cubic boron nitride tool (CB7025) and kentanium tool (GC2025), the surface roughness was measured using 2025 surface roughness tester, the predicted models of the surface roughness were built by Particle Swarm Optimization (PSO) algorithm, the reliability analysis was given out, the shape of chips was observed by scanning electron microscope (SEM). Results proved: the reliability of the predicted models built by PSO was to be verified, it could reflect the relation between the surface roughness and cutting parameters exactly. The feed rate was found out to be dominant factor on the surface roughness in turning with three tools. The saw-tooth chips could decrease the cutting temperature and improve the surface quality.

Experimental Study Of Dry Turning Of UNS A92024-T3 Aluminium Alloy Bars Based On Surface Roughness

2009 ◽  
Author(s):  
A. J. Saá ◽  
B. de Agustina ◽  
M. Marcos ◽  
E. M. Rubio ◽  
Vicente Jesus Segui
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Aluminium Alloy ◽  
Dry Turning

A Comprehensive Study on Surface Roughness in Machining of AISI D2 Hardened Steel

2012 ◽  
Vol 576 ◽  
pp. 60-63 ◽  
Author(s):  
N.A.H. Jasni ◽  
Mohd Amri Lajis
Keyword(s):  
Surface Roughness ◽  
High Speed ◽  
End Milling ◽  
Cutting Speed ◽  
Hardened Steel ◽  
Depth Of Cut ◽  
Feed Speed ◽  
Radial Depth ◽  
Aisi D2 ◽  
Coated Carbide

Hard milling of hardened steel has wide application in mould and die industries. However, milling induced surface finish has received little attention. An experimental investigation is conducted to comprehensively characterize the surface roughness of AISI D2 hardened steel (58-62 HRC) in end milling operation using TiAlN/AlCrN multilayer coated carbide. Surface roughness (Ra) was examined at different cutting speed (v) and radial depth of cut (dr) while the measurement was taken in feed speed, Vf and cutting speed, Vc directions. The experimental results show that the milled surface is anisotropic in nature. Surface roughness values in feed speed direction do not appear to correspond to any definite pattern in relation to cutting speed, while it increases with radial depth-of-cut within the range 0.13-0.24 µm. In cutting speed direction, surface roughness value decreases in the high speed range, while it increases in the high radial depth of cut. Radial depth of cut is the most influencing parameter in surface roughness followed by cutting speed.

Experimental Study on Roughness Effect for Laminar Micro-Channel Gas Flow

2001 ◽  
Author(s):  
Jih-Hsing Tu ◽  
Fangang Tseng ◽  
Ching-Chang Chieng
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Friction Factor ◽  
Gas Flow ◽  
Micro Channel ◽  
Micro Machining ◽  
Roughness Effect ◽  
Relative Roughness ◽  
Smooth Channel ◽  
Micro Channels

Abstract Present study investigates the roughness effect on laminar gas flow for microchannels ranging from 40 to 600 μm with various roughness heights (40–82 nm) by systematical experiments. The micro-channels are manufactured by micro-machining technology and KOH anisotropic etching is employed to achieve various roughness patterns. Experimental results shows that higher product levels of Reynolds number (Reh) and friction factor (f) are obtained for microchannels of larger size and smaller relative roughness and friction factor f approaches to laminar flow theory value f0 for very smooth channel but the ratio of (f/f0) decreases as the surface roughness increases.

Effect of Tightening Speed on the Torque-Tension and Wear Pattern in Bolted Connections

2006 ◽  
Author(s):  
Sayed A. Nassar ◽  
Ramanathan M. Ranganathan ◽  
Saravanan Ganeshmurthy ◽  
Gary C. Barber
Keyword(s):  
Experimental Data ◽  
Experimental Study ◽  
Surface Roughness ◽  
Initial Level ◽  
Zinc Coating ◽  
Optical Microscope ◽  
Wear Pattern ◽  
Highly Sensitive ◽  
Contact Surfaces ◽  
Scanning Electron

This experimental study investigates the effect of tightening speed and coating on both the torque – tension relationship and wear pattern in threaded fastener applications. The fastener torque – tension relationship is highly sensitive to normal variations in the coefficients of friction between threads and between the turning head and the surface of the joint. Hence, the initial level of the joint clamp load and the overall integrity and reliability of a bolted assembly is significantly influenced by the friction coefficients. The effect of repeated tightening and loosening is also investigated using M12, Class 8.8, fasteners with and without zinc coating. The torque – tension relationship is examined in terms of the non-dimensional nut factor K. The wear pattern is examined by monitoring the changes in surface roughness using a WYKO optical profiler and by using a LECO optical microscope. A Hitachi S-3200N Scanning Electron Microscope (SEM) is used to examine the contact surfaces, under the fastener head, after each tightening/loosening cycle. Experimental data on the effect of variables and the tightening speed, fastener coating and repeated tightening on the nut factor are presented and analyzed for M8 and M12, class 8.8, fasteners.

Statistical Study and Multi-Response Optimization of Cutting Parameters for Dry Turning Stainless Steel AISI 316L Using Cermet Tool

2020 ◽  
Vol 36 ◽  
pp. 28-46
Author(s):  
Youssef Touggui ◽  
Salim Belhadi ◽  
Salah Eddine Mechraoui ◽  
Mohamed Athmane Yallese ◽  
Mustapha Temmar
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Aisi 316L ◽  
Cutting Power ◽  
Dry Turning ◽  
Optimization Of Cutting Parameters

Stainless steels have gained much attention to be an alternative solution for many manufacturing industries due to their high mechanical properties and corrosion resistance. However, owing to their high ductility, their low thermal conductivity and high tendency to work hardening, these materials are classed as materials difficult to machine. Therefore, the main aim of the study was to examine the effect of cutting parameters such as cutting speed, feed rate and depth of cut on the response parameters including surface roughness (Ra), tangential cutting force (Fz) and cutting power (Pc) during dry turning of AISI 316L using TiCN-TiN PVD cermet tool. As a methodology, the Taguchi L27 orthogonal array parameter design and response surface methodology (RSM)) have been used. Statistical analysis revealed feed rate affected for surface roughness (79.61%) and depth of cut impacted for tangential cutting force and cutting power (62.12% and 35.68%), respectively. According to optimization analysis based on desirability function (DF), cutting speed of 212.837 m/min, 0.08 mm/rev feed rate and 0.1 mm depth of cut were determined to acquire high machined part quality

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