Experimental Analysis on Surface Roughness of En-24 Hardened Steel

In this thesis, it is about the machining of the EN-24 hardened steel that involves turning operation of the EN-24 with the help of coated carbide insert of ISO designation CNMG 120408. Analysis of the surface roughness is done experimentally with specific input values of feed, depth of cut and speed and gradually the optimal condition is found out. A relation between the inputs and the output is determined and thereafter, the analysis is done how the inputs affected the output. First using the full factorial composite design a layout of the experiment is made after which it is conducted. The profilometer is used to measure the surface roughness. Here the L27 Taguchi method is used for the determination of the change in surface roughness with respect to the speed, feed and depth of cut. This can be analysed with help of the contour plots, 3-D surface plots and different graphs produced by the MINTAB 16 software. We can easily determine the effects by visualizing the main effect plots and interaction plots also. With the help of ANOVA (Analysis of Variance), the most effective or the optimal parameters for the output are determined. The regression equations are also obtained. All the parameters are found to be significant in determination of the surface roughness and possible conclusions are made at the end

Optimization of cutting parameters using robust design for minimizing energy consumption in turning of AISI 1018 steel with constant material removal rate

Part of: Seliger, Günther (Ed.): Innovative solutions : proceedings / 11th Global Conference on Sustainable Manufacturing, Berlin, Germany, 23rd - 25th September, 2013. - Berlin: Universitätsverlag der TU Berlin, 2013. - ISBN 978-3-7983-2609-5 (online). - http://nbn-resolving.de/urn:nbn:de:kobv:83-opus4-40276. - pp. 149–152.The strategies to reduce energy consumption are obtaining emphasis due to the constant increase in electricity prices, and concern of manufacturing companies and clients about the environmental impact that results from activities related to the production of goods. CNC machine tools, including those that perform turning operations, contribute significantly to the energy consumption in the manufacturing sector. The present work outlines an experimental study to optimize cutting parameters during turning of AISI 1018 steel under roughing conditions and constant material removal rate, in order to get the minimum energy consumption of the machine tool. Robust design is employed to analyze the effects of depth of cut, feed rate and cutting speed on the response variable

Multi-objective optimization of energy consumption and surface quality in nanofluid SQCL assisted face milling

Considering the significance of improving the energy efficiency, surface quality and material removal quantity of machining processes, the present study is conducted in the form of an experimental investigation and a multi-objective optimization. The experiments were conducted by face milling AISI 1045 steel on a Computer Numerical Controlled (CNC) milling machine using a carbide cutting tool. The Cu-nano-fluid, dispersed in distilled water, was impinged in small quantity cooling lubrication (SQCL) spray applied to the cutting zone. The data of surface roughness and active cutting energy were measured while the material removal rate was calculated. A multi-objective optimization was performed by the integration of the Taguchi method, Grey Relational Analysis (GRA), and the Non-Dominated Sorting Genetic Algorithm (NSGA-II). The optimum results calculated were a cutting speed of 1200 rev/min, a feed rate of 320 mm/min, a depth of cut of 0.5 mm, and a width of cut of 15 mm. It was also endowed with a 20.7% reduction in energy consumption. Furthermore, the use of SQCL promoted sustainable manufacturing. The novelty of the work is in reducing energy consumption under nano fluid assisted machining while paying adequate attention to material removal quantity and the product’s surface quality

TAGUCHI BASED OPTIMIZATION OF MACHINING PARAMETERS TO CONTROL SURFACE ROUGHNESS USING TiAlN-COATED TUNGSTEN CARBIDE MILLING CUTTER

Surface roughness is one of the determinant factors that governs the quality of machined surfaces. This paper experimentally studied effects of machining parameters on the surface roughness (Ra) for end milling of AISI 1045 work piece using a TiAlN coated carbide milling cutter. Taguchi optimization method was used to determine the optimal level of three control factors, namely, the feed rate, the spindle speed and the depth of cut. Analysis of variance demonstrates that the feed rate is the most significant parameter and contributes 47% for surface roughness. Finally, the contour plots of these three parameters have been analysed to determine the optimal ranges of control factors

Machinability assessment when turning AISI 316L austenitic stainless steel using uncoated and coated carbide inserts

Austenitic stainless steel AISI 316L is mostly used as an implant material and is customarily applied as impermanent devices in orthopedic surgery because of its low cost, adequate mechanical properties, and acceptable biocompatibility. AISI 316L is an extra-low carbon type 316 (austenitic chromium nickel stainless steel containing molybdenum) that minimizes harmful carbide precipitation at elevated temperature. Machining is part and parcel during the fabrication of implants and medical devices made from stainless steels and thus it is of interest to evaluate the machinability of AISI 316L. In this study, austenitic stainless steel AISI 316L was turned using two commercially available cutting tool inserts at various cutting speeds (90, 150, and 210 m/min) and feeds (0.10, 0.16, and 0.22 mm/rev) and at a constant depth of cut of 0.4 mm. The turning of AISI 316L was implemented in dry cutting. The cutting tools used were an uncoated tungsten carbide-cobalt insert (WC-Co) and a multi coated nano-textured TiCN, nano-textured Al2O3 thin layer, and a TiN outer layer insert. The cutting forces, total power consumption, surface roughness, and tool life were measured/obtained and analyzed. The total power consumption of the turning process was obtained from direct measurements as well as using a combination of theoretical formulas and experimental cutting force data. The machining experiments and their responses were designed and evaluated using the three-level full factorial design and the analysis of variance (ANOVA). It was found that the cutting speed and feed significantly affect the various machining responses observed. The cutting force and total power consumption increased with increasing cutting speed, but the surface roughness and tool life decreased. With increasing feed, surface roughness and tool life decreased but the cutting force and total power consumption increased. The empirical mathematical models of the machining responses as functions of cutting speed and feed developed were statistically valid. Confirmation runs helped to prove the validity of the models within the limits of the factors investigated

Optimizing Machining Parameters during Turning Process

This work presents an experimental investigation of the influence of the three most important machining parameters of depth of cut, feed rate and spindle speed on surface roughness during turning of mild steel. In this study, the design of experiment which is a powerful tool for experimental design is used to optimize the machining parameters for effective machining of the workpiece. Box Behnken experimental design method as well as analysis of variance (ANOVA) is used to analyze the influence of machining parameters on surface roughness height Ra. The individual parameters effect as well as effect of interactions between the machining parameters on the surface roughness height Ra is analyzed using various graphical representations. Using multiple linear regressions, mathematical models correlating the influence of machining parameters on the surface roughness Ra during the machining process were developed. Confirmation results were used to confirm that mathematical models are good enough to effectively represent machining criteria of surface roughness Ra during the study

Analysis of effect of Minimum Quantity Lubrication on different machining parameters Cutting Force, Surface Roughness and Tool Wear by Hard Turning of AISI-4340 Alloy Steel a Review

ABSTRACT This paper deals with the study of various machining process and show the effect of different cutting parameters on the properties of material. There are several important factors in the product quality which are surface finish, cutting temperature, tool life and coolant quality. The use of coolant generally causes life of tools and it also maintains work piece surface properties without damages. There are some negative effects and cutting fluid wastes in industries. In this paper, attention is focused on minimum quantity lubrication and recent work and some outcomes of machining factors from minimum quantity lubrication are presented. The review of the literature suggests that minimal fluid application provides several benefits in machining. It has been found that hardened alloy steel like AISI 4340 is known to be difficult to cut and a little knowledge is available in use of MQL for cooling. The main objective of the study of MQL is to reduce the surface roughness during machining and machining cost of cutting fluid. The minimum quantity lubrication also affects the surface finishing, reduce tool wear and reduce the cutting force. This paper provides a review of present work and some limitations of conventional cutting fluid machining and growing opportunities for development of the next generation MQL in machining operations

Calculating the Power Demand in Turning of AISI 316L Stainless Steel Through the Cutting Forces Data

Abstract—Austenitic stainless steel AISI 316L has been widely used for orthopedic implants due to its mechanical properties, corrosion resistance and biocompatibility. Machining of austenitic stainless steel are often regarded as 'difficult to machine' and classed a single group of steels, based on experience with the most common austenitic types. This paper presents a methodology for practical calculation of power demand based on cutting force that will be compared with experimental results especially turning process. Based on a previously proposed definition, the power demand in metal cutting is the energy required cutting. This paper provides a complete list of mathematical expressions needed for the calculation of power demand and demonstrates their utility for turning operation of austenitic stainless steel using coated and uncoated carbide