scispace - formally typeset
Search or ask a question
Author

Tuğrul Özel

Bio: Tuğrul Özel is an academic researcher from Rutgers University. The author has contributed to research in topics: Machining & Tool wear. The author has an hindex of 42, co-authored 120 publications receiving 7998 citations. Previous affiliations of Tuğrul Özel include Ohio State University & Cleveland State University.


Papers
More filters
Journal ArticleDOI
TL;DR: In this paper, the authors provide an overview of machining induced surface integrity in titanium and nickel alloys and conclude that further modeling studies are needed to create predictive physics-based models that is in good agreement with reliable experiments.
Abstract: Titanium and nickel alloys represent a significant metal portion of the aircraft structural and engine components. When these critical structural components in aerospace industry are manufactured with the objective to reach high reliability levels, surface integrity is one of the most relevant parameters used for evaluating the quality of finish machined surfaces. The residual stresses and surface alteration (white etch layer and depth of work hardening) induced by machining of titanium alloys and nickel-based alloys are very critical due to safety and sustainability concerns. This review paper provides an overview of machining induced surface integrity in titanium and nickel alloys. There are many different types of surface integrity problems reported in literature, and among these, residual stresses, white layer and work hardening layers, as well as microstructural alterations can be studied in order to improve surface qualities of end products. Many parameters affect the surface quality of workpieces, and cutting speed, feed rate, depth of cut, tool geometry and preparation, tool wear, and workpiece properties are among the most important ones worth to investigate. Experimental and empirical studies as well as analytical and Finite Element modeling based approaches are offered in order to better understand machining induced surface integrity. In the current state-of-the-art however, a comprehensive and systematic modeling approach based on the process physics and applicable to the industrial processes is still missing. It is concluded that further modeling studies are needed to create predictive physics-based models that is in good agreement with reliable experiments, while explaining the effects of many parameters, for machining of titanium alloys and nickel-based alloys.

986 citations

Journal ArticleDOI
TL;DR: In this article, the state-of-the-art in predictive performance models for machining operations is presented, and a critical assessment of the relevant modelling techniques and their applicability and/or limitations for the prediction of the complex machining operation performed in industry.

622 citations

Journal ArticleDOI
TL;DR: In this paper, the authors used neural network models to predict surface roughness and tool flank wear over the machining time for variety of cutting conditions in finish hard turning of hardened AISI 52100 steel.
Abstract: In machining of parts, surface quality is one of the most specified customer requirements. Major indication of surface quality on machined parts is surface roughness. Finish hard turning using Cubic Boron Nitride (CBN) tools allows manufacturers to simplify their processes and still achieve the desired surface roughness. There are various machining parameters have an effect on the surface roughness, but those effects have not been adequately quantified. In order for manufacturers to maximize their gains from utilizing finish hard turning, accurate predictive models for surface roughness and tool wear must be constructed. This paper utilizes neural network modeling to predict surface roughness and tool flank wear over the machining time for variety of cutting conditions in finish hard turning. Regression models are also developed in order to capture process specific parameters. A set of sparse experimental data for finish turning of hardened AISI 52100 steel obtained from literature and the experimental data obtained from performed experiments in finish turning of hardened AISI H-13 steel have been utilized. The data sets from measured surface roughness and tool flank wear were employed to train the neural network models. Trained neural network models were used in predicting surface roughness and tool flank wear for other cutting conditions. A comparison of neural network models with regression models is also carried out. Predictive neural network models are found to be capable of better predictions for surface roughness and tool flank wear within the range that they had been trained. Predictive neural network modeling is also extended to predict tool wear and surface roughness patterns seen in finish hard turning processes. Decrease in the feed rate resulted in better surface roughness but slightly faster tool wear development, and increasing cutting speed resulted in significant increase in tool wear development but resulted in better surface roughness. Increase in the workpiece hardness resulted in better surface roughness but higher tool wear. Overall, CBN inserts with honed edge geometry performed better both in terms of surface roughness and tool wear development. q 2004 Elsevier Ltd. All rights reserved.

599 citations

Journal ArticleDOI
TL;DR: In this article, the effect of material constitutive models and elastic-viscoplastic finite element formulation on serrated chip formation for modeling of machining Ti-6Al-4V titanium alloy is investigated.
Abstract: Titanium alloys present superior properties such as high strength-to-weight ratio and resistance to corrosion but, possess poor machinability. In this study, influence of material constitutive models and elastic–viscoplastic finite element formulation on serrated chip formation for modeling of machining Ti–6Al–4V titanium alloy is investigated. Temperature-dependent flow softening based modified material models are proposed where flow softening phenomenon, strain hardening and thermal softening effects and their interactions are coupled. Orthogonal cutting experiments have been conducted with uncoated carbide (WC/Co) and TiAlN coated carbide cutting tools. Temperature-dependent flow softening parameters are validated on a set of experimental data by using measured cutting forces and chip morphology. Finite Element simulations are validated with experimental results at two different rake angles, three different undeformed chip thickness values and two different cutting speeds. The results reveal that material flow stress and finite element formulation greatly affects not only chip formation mechanism but also forces and temperatures predicted. Chip formation process for adiabatic shearing in machining Ti–6Al–4V alloy is successfully simulated using finite element models without implementing damage models.

409 citations

Journal ArticleDOI
Tuğrul Özel1
TL;DR: In this article, an updated Lagrangian finite element formulation is used to simulate continuous chip formation process in orthogonal cutting of low carbon free-cutting steel, and the effects of tool-chip interfacial friction models on the finite element simulations are investigated.
Abstract: In the analysis of orthogonal cutting process using finite element (FE) simulations, predictions are greatly influenced by two major factors; a) flow stress characteristics of work material at cutting regimes and b) friction characteristics mainly at the tool-chip interface. The uncertainty of work material flow stress upon FE simulations may be low when there is a constitutive model for work material that is obtained empirically from high-strain rate and temperature deformation tests. However, the difficulty arises when one needs to implement accurate friction models for cutting simulations using a particular FE formulation. In this study, an updated Lagrangian finite element formulation is used to simulate continuous chip formation process in orthogonal cutting of low carbon free-cutting steel. Experimentally measured stress distributions on the tool rake face are utilized in developing several different friction models. The effects of tool-chip interfacial friction models on the FE simulations are investigated. The comparison results depict that the friction modeling at the tool-chip interface has significant influence on the FE simulations of machining. Specifically, variable friction models that are developed from the experimentally measured normal and frictional stresses at the tool rake face resulted in most favorable predictions. Predictions presented in this work also justify that the FE simulation technique used for orthogonal cutting process can be an accurate and viable analysis as long as flow stress behavior of the work material is valid at the machining regimes and the friction characteristics at the tool-chip interface is modeled properly.

361 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: In this paper, a critical review on some experimental results and constitutive descriptions for metals and alloys in hot working, which were reported in international publications in recent years, is presented.

1,071 citations

Journal ArticleDOI
TL;DR: In this paper, the authors provide an overview of machining induced surface integrity in titanium and nickel alloys and conclude that further modeling studies are needed to create predictive physics-based models that is in good agreement with reliable experiments.
Abstract: Titanium and nickel alloys represent a significant metal portion of the aircraft structural and engine components. When these critical structural components in aerospace industry are manufactured with the objective to reach high reliability levels, surface integrity is one of the most relevant parameters used for evaluating the quality of finish machined surfaces. The residual stresses and surface alteration (white etch layer and depth of work hardening) induced by machining of titanium alloys and nickel-based alloys are very critical due to safety and sustainability concerns. This review paper provides an overview of machining induced surface integrity in titanium and nickel alloys. There are many different types of surface integrity problems reported in literature, and among these, residual stresses, white layer and work hardening layers, as well as microstructural alterations can be studied in order to improve surface qualities of end products. Many parameters affect the surface quality of workpieces, and cutting speed, feed rate, depth of cut, tool geometry and preparation, tool wear, and workpiece properties are among the most important ones worth to investigate. Experimental and empirical studies as well as analytical and Finite Element modeling based approaches are offered in order to better understand machining induced surface integrity. In the current state-of-the-art however, a comprehensive and systematic modeling approach based on the process physics and applicable to the industrial processes is still missing. It is concluded that further modeling studies are needed to create predictive physics-based models that is in good agreement with reliable experiments, while explaining the effects of many parameters, for machining of titanium alloys and nickel-based alloys.

986 citations

Journal ArticleDOI
TL;DR: A three-year study by the CIRP's Collaborative Working Group on Surface Integrity and Functional Performance of Components as discussed by the authors reported recent progress in experimental and theoretical investigations on surface integrity in material removal processes.

769 citations

Journal ArticleDOI
TL;DR: A comprehensive understanding of the interrelation between the various aspects of the subject, as this is essential to demonstrate credibility for industrial needs, is presented in this paper, which highlights some key topics requiring attention for further progression.

761 citations

Journal ArticleDOI
TL;DR: In this paper, the authors review and identify the materials known as difficult-to-machine and their properties and major health and environmental concerns about their usage in material cutting industries are defined.
Abstract: Machining difficult-to-machine materials such as alloys used in aerospace, nuclear and medical industries are usually accompanied with low productivity, poor surface quality and short tool life. Despite the broad use of the term difficult-to-machine or hard-to-cut materials, the area of these types of materials and their properties are not clear yet. On the other hand, using cutting fluids is a common technique for improving machinability and has been acknowledged since early 20th. However, the environmental and health hazards associated with the use of conventional cutting fluids together with developing governmental regulations have resulted in increasing machining costs. The aim of this paper is to review and identify the materials known as difficult-to-machine and their properties. In addition, different cutting fluids are reviewed and major health and environmental concerns about their usage in material cutting industries are defined. Finally, advances in reducing and/or eliminating the use of conventional cutting fluids are reviewed and discussed.

658 citations