Statistical Wear Model for Adhesively Bonded Tools

2011 ◽  
Vol 264-265 ◽  
pp. 1802-1811
Author(s):  
S.M. Darwish ◽  
Ali M. Al Samhan ◽  
H.A. Helmy
Keyword(s):  
Statistical Models ◽  
Cutting Speed ◽  
Computer Integrated Manufacturing ◽  
Depth Of Cut ◽  
Data Systems ◽  
Optimum Conditions ◽  
Adhesively Bonded ◽  
Wear Model ◽  
Machinability Data ◽  
Selection Of

Computerized machinability data systems are essential for the selection of optimum conditions during process planning, and they form an important component in the implementation of computer integrated manufacturing (CIM) systems. Since statistical models for adhesively bonded tools are unavailable, the present paper presents a study of the development of a tool life, surface roughness and cutting force models for turning constructional steels, using adhesively bonded tools. These models are developed in terms of cutting speed, federate and depth of cut. These variables are investigated using design of experiments and utilization of response surface methodology (RMS).

Surface Roughness Model for Turning Grey Cast Iron (154 BHN)

1993 ◽  
Vol 207 (1) ◽  
pp. 43-54 ◽  
Author(s):  
M A El Baradie
Keyword(s):  
Surface Roughness ◽  
Cast Iron ◽  
Cutting Speed ◽  
Grey Cast Iron ◽  
Computer Integrated Manufacturing ◽  
Depth Of Cut ◽  
Data Systems ◽  
Roughness Model ◽  
Speed Range ◽  
Grey Cast

Computerized machinability data systems are essential for the selection of optimum cutting conditions during process planning, and they form an important component in the implementation of computer integrated manufacturing (CIM) systems. This paper presents a study of the development of a surface roughness model for turning grey cast iron (154 BHN), using tipped carbide tools under dry conditions and a constant depth of cut. The model is developed in terms of cutting speed, feedrate and nose radius of the cutting tool. These variables were investigated using design of experiments and utilization of the response surface methodology (RSM). A first-order equation covering the speed range 110–350 m/min and a second-order generation equation covering the speed range 80–495 m/min are presented. The results are given in terms of mean values with confidence intervals.

Application of MCDM-based TOPSIS method for the selection of optimal process parameter in turning of pure titanium

2017 ◽  
Vol 24 (7) ◽  
pp. 2009-2021 ◽  
Author(s):  
Akhtar Khan ◽  
Kalipada Maity
Keyword(s):  
Decision Making ◽  
Cutting Force ◽  
Pure Titanium ◽  
Cutting Speed ◽  
Optimal Combination ◽  
Depth Of Cut ◽  
Topsis Method ◽  
Content Type ◽  
Cp Ti ◽  
Selection Of

Purpose The purpose of this paper is to explore a multi-criteria decision-making (MCDM) methodology to determine an optimal combination of process parameters that is capable of generating favorable dimensional accuracy and product quality during turning of commercially pure titanium (CP-Ti) grade 2. Design/methodology/approach The present paper recommends an optimal combination of cutting parameters with an aim to minimize the cutting force (Fc), surface roughness (Ra), machining temperature (Tm) and to maximize the material removal rate (MRR) after turning of CP-Ti grade 2. This was achieved by the simultaneous optimization of the aforesaid output characteristics (i.e. Fc, Ra, Tm, and MRR) using the MCDM-based TOPSIS method. Taguchi’s L9 orthogonal array was used for conducting the experiments. The output responses (cutting force: Fc, surface roughness: Ra, machining temperature: Tm and MRR) were integrated together and presented in terms of a single signal-to-noise ratio using the Taguchi method. Findings The results of the proposed methodology depict that the higher MRR with desirable surface quality and the lower cutting force and machining temperature were observed at a combination of cutting variables as follows: cutting speed of 105 m/min, feed rate of 0.12 mm/rev and depth of cut of 0.5 mm. The analysis of variance test was conducted to evaluate the significance level of process parameters. It is evident from the aforesaid test that the depth of cut was the most significant process parameter followed by cutting speed. Originality/value The selection of an optimal parametric combination during the machining operation is becoming more challenging as the decision maker has to consider a set of distinct quality characteristics simultaneously. This situation necessitates an efficient decision-making technique to be used during the machining operation. From the past literature, it is noticed that only a few works were reported on the multi-objective optimization of turning parameters using the TOPSIS method so far. Thus, the proposed methodology can help the decision maker and researchers to optimize the multi-objective turning problems effectively in combination with a desirable accuracy.

Flank-Wear Model and Optimization of Machining Process and its Control in Turning

1973 ◽  
Vol 187 (1) ◽  
pp. 301-307
Author(s):  
Y. Koren ◽  
J. Ben-Uri
Keyword(s):  
Flank Wear ◽  
Cutting Speed ◽  
The Other ◽  
Machining Process ◽  
Depth Of Cut ◽  
Wear Model ◽  
Speed Change ◽  
Steel Turning ◽  
The One ◽  
Non Linear System

Designing the optimal control for a machine tool necessitates a mathematical model of the cutting process. In the present paper, a flank-wear model was developed for a carbide tool used in steel turning. It yields the relation between the process parameters (cutting speed, feed and depth of cut) on the one hand, and the width of the wear land on the other. In the second stage—the optimization proper—the problem consists of optimizing a non-linear system with the initial, and part of the final, conditions known, and the terminal time not given explicitly. Complexity was reduced by converting from time- to path-derivatives, and the problem was solved using the gradient method, yielding cost differences which are negligible compared with the conventional method. To complete the picture, a motor control system was sought minimizing the error in obeying the speed change command on the one hand, and the path error during simultaneous operation of several feed spindles on the other.

Flank-Wear Model and Optimization of Machining Process and its Control in Turning

1973 ◽  
Vol 187 (1) ◽  
pp. 301-307
Author(s):  
Y. Koren ◽  
J. Ben-Uri
Keyword(s):  
Flank Wear ◽  
Cutting Speed ◽  
The Other ◽  
Machining Process ◽  
Depth Of Cut ◽  
Wear Model ◽  
Speed Change ◽  
Steel Turning ◽  
The One ◽  
Non Linear System

Designing the optimal control for a machine tool necessitates a mathematical model of the cutting process. In the present paper, a flank-wear model was developed for a carbide tool used in steel turning. It yields the relation between the process parameters (cutting speed, feed and depth of cut) on the one hand, and the width of the wear land on the other. In the second stage—the optimization proper—the problem consists of optimizing a non-linear system with the initial, and part of the final, conditions known, and the terminal time not given explicitly. Complexity was reduced by converting from time- to path-derivatives, and the problem was solved using the gradient method, yielding cost differences which are negligible compared with the conventional method. To complete the picture, a motor control system was sought minimizing the error in obeying the speed change command on the one hand, and the path error during simultaneous operation of several feed spindles on the other.

Studies of Machining Parameters of Al Alloy A-390 During Turning

2005 ◽  
Author(s):  
Suresh Dhiman ◽  
Rakesh Sehgal ◽  
S. K. Sharma
Keyword(s):  
Feed Rate ◽  
Cutting Speed ◽  
Casting Process ◽  
Interface Temperature ◽  
Depth Of Cut ◽  
Al Alloy ◽  
Machining Parameters ◽  
Casting Alloy ◽  
Selection Of ◽  
Temperature Surface

Selection of any casting alloy is dependent on a wide variety of factors such as casting process, service requirement and economy of processing viz. weldability, castability and machinability. Out of these, machinability plays an important role in the selection of material for its commercial exploitation. In general, more than 80% of the manufactured parts are machined before they are ready for use. Thus machinability of a material controls significantly its economy in various applications. In this paper, machinabilty is evaluated by studying various data/parameters of Al alloy (A-390) such as cutting forces, tool tip interface temperature, surface finish and power consumption during turning at different cutting speed, depth of cut and feed rate. In this study, Al-Si alloys with different composition were subjected to machinability testing by varying the cutting speed, depth of cut and by keeping feed rate constant.

Parameteric Optimization of Surface Roughness in End Milling of Aluminium Rock Dust Composite

2015 ◽  
Vol 813-814 ◽  
pp. 382-387 ◽  
Author(s):  
K. Soorya Prakash ◽  
S. Sudhagar ◽  
M. Sakthivel ◽  
P.M. Gopal
Keyword(s):  
Surface Roughness ◽  
Particle Size ◽  
High Performance ◽  
End Milling ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Weight Percentage ◽  
Recent Developments ◽  
Selection Of ◽  
Rock Dust

Recent developments in the composite materials with high performance increase its range of application most widely but the major disadvantage of these novel materials is machining. The selection of proper process parameters plays an important role in distinguishing machining quality. This work mainly concentrates on the selection of process parameter for minimizing the surface roughness in end milling operation for the newly developed aluminium rock dust metal matrix composite. Taguchi method is used to design and accordingly L27 orthogonal array with five factors viz particle size, weight percentage, cutting speed, feed and depth of cut each at three levels is employed. The experiments were performed in a CNC vertical machining center and corresponding surface roughness values are measured. From the collected data, ANOVA is performed and observations reveal that feed rate influence more on surface roughness followed by particle size, depth of cut, weight percentage and cutting speed.

Experimental Investigations and Modeling of Machining Titanium Alloy – Ti-6Al-4V

2013 ◽  
Vol 315 ◽  
pp. 562-566
Author(s):  
Kosaraju Satyanarayana ◽  
Anne Venu Gopal ◽  
Popuri Bangaru Babu
Keyword(s):  
Surface Roughness ◽  
Titanium Alloy ◽  
Cutting Force ◽  
Experimental Studies ◽  
Experimental Investigations ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Optimum Conditions ◽  
Proper Selection ◽  
Selection Of

The problem of machining titanium is one of ever-increasing magnitude due to its low thermal conductivity and work hardening characteristic of the titanium alloy. The efficient machining of titanium alloy with coated carbides involves a proper selection of process parameters to minimizing the surface roughness and cutting force. In the present work, experimental studies have been carried out to obtain the optimum conditions for machining titanium alloy. The effect of machining parameters such speed, feed and depth of cut on the cutting force, surface roughness were investigated. The significance of these parameters, on cutting force and surface roughness has been established using the analysis of variance. Mathematical models have also been developed for estimating the cutting force and surface roughness on the basis of experimental results.

scholarly journals Computational Inteligence in Optimization of Machining Operation Parameters of ST-37 Steel

2012 ◽  
Vol 248 ◽  
pp. 456-461
Author(s):  
Abolfazl Golshan ◽  
Danial Ghodsiyeh ◽  
Soheil Gohari ◽  
Ayob Amran ◽  
B.T. Hang Tuah Baharudin
Keyword(s):  
Performance Optimization ◽  
High Performance ◽  
Cutting Speed ◽  
Optimization Procedure ◽  
Cutting Parameters ◽  
Rake Angle ◽  
Depth Of Cut ◽  
Optimal Cutting Parameters ◽  
Machining Characteristics ◽  
Selection Of

Optimal selection of cutting parameters is one of the significant issues in achieving high quality machining. In this study, a method for the selection of optimal cutting parameters during lathe operation is presented. The present study focuses on multiple-performance optimization on machining characteristics of St-37 steel. The cutting parameters used in this experimental study include cutting speed, feed rate, depth of cut and rake angle. Two output parameters, namely, surface roughness and tool life are considered as process performance. A statistical model based on linear polynomial equations is developed to describe different responses. For optimal conditions, the Non-dominated Sorting Genetic Algorithm (NSGA) is employed in achieving appropriate models. The optimization procedure shows that the proposed method has a high performance in problem-solving.

scholarly journals MULTIPLE PERFORMANCE CHARACTERISTICS OPTIMIZATION OF HARD TURNING OPERATIONS USING UTILITY BASED-TAGUCHI APPROACH

2016 ◽  
Vol 45 (2) ◽  
pp. 73-80 ◽  
Author(s):  
K Rahul Varma ◽  
M. Kaladhar
Keyword(s):  
Cutting Speed ◽  
Cutting Parameters ◽  
Performance Characteristics ◽  
Dominant Factor ◽  
Depth Of Cut ◽  
Work Piece ◽  
Taguchi Approach ◽  
Utility Concept ◽  
Cutting Inserts ◽  
Selection Of

In order to sustain in the global competitive scenario, the manufacturing industries have beenpracticing the various tools to achieve the high quality products at lower cost. Selection of appropriate cutting conditions is necessary to improve machinabilty of a work piece material. The present work objective is to find out the optimum cutting parameters in turning of hardened AISI M2 steel using cryogenically treated cutting inserts. The Utility concept coupled with Taguchi approach was employed to optimize both surface roughness and power consumption simultaneously. According to Analysis of variance (ANOVA) results, the feed was the major dominant factor followed by the cutting speed on multiple performance characteristics. The necessary optimum conditions for multiple performance characteristics optimization were obtained as cutting speed of 100 m/min, feed 0.04 mm/rev and depth of cut of 0.2 mm.

scholarly journals Parametric Study on Turning of AISI 1040 Steel

2021 ◽  
pp. 230-236
Author(s):  
Azadar Mehdi ◽  
Aamir
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Parametric Study ◽  
Large Scale ◽  
Input Parameter ◽  
Cutting Speed ◽  
Cutting Process ◽  
Depth Of Cut ◽  
Selection Of

Turning is a most popular cutting process which is widely used in small as well as the large-scale industries. The selection of better combination of the input parameter be means enhancement in productivity. The aim of this paper is to the study effect of ( Cutting Speed, Depth of cut, Feed rate ) on surface roughness and to obtained the data.

Sign in / Sign up

Export Citation Format

Share Document