H.A. Kishawy

NC end milling optimization using evolutionary computation

Abstract Typically, NC programmers generate tool paths for end milling using a computer-aided process planner but manually schedule “conservative” cutting conditions. In this paper, a new evolutionary computation technique, particle swarm optimization (PSO), is proposed and implemented to efficiently and robustly optimize multiple machining parameters simultaneously for the case of milling. An artificial neural networks (ANN) predictive model for critical process parameters is used to predict the cutting forces which in turn are used by the PSO developed algorithm to optimize the cutting conditions subject to a comprehensive set of constraints. Next, the algorithm is used to optimize both feed and speed for a typical case found in industry, namely, pocket-milling. Machining time reductions of up to 35% are observed. In addition, the new technique is found to be efficient and robust.

Surface Integrity of Die Material in High Speed Hard Machining, Part 1: Micrographical Analysis

The effects of cutting conditions and tool wear on chip morphology and surface integrity during high speed machining of D2 tool steel (60-62 Hrc) are investigated experimentally and analytically in this paper. Polycrystalline Cubic Boron Nitride (PCBN) tools are used in this investigation. The chips and the subsurface of the workpiece are examined using optical and scanning electron microscopy. Microhardness measurements are performed on the surface and subsurface of the workpiece. The X-ray diffraction technique is used to measure the residual stresses induced in the machined surface. The paper is divided into two parts. Part 1 presents the results obtained from the micrographical analysis of the chips and the surfaces produced. Part 2 deals with microhardness and residual stresses of the machined surface. The micrographical analysis of the chips produced shows that different mechanisms of chip formation exist depending on the magnitude of the cutting pressure and tool wear. Saw toothed chips are produced during the machining of D2 tool steel if the cutting pressure exceeds approximately 4000 MPa. The metallographic analysis of the surface produced illustrates the damaged surface region that contains geometrical defects and changes in the subsurface metallurgical structure. The types of surface damage are dependent on the cutting conditions, tool geometry and the magnitude of the wear lands.

An Energy Based Analytical Force Model for Orthogonal Cutting of Metal Matrix Composites

Abstract The machining of metal matrix composite (MMC) presents a significant challenge to the industry. The hard and abrasive nature of the reinforcement causes rapid tool wear and high machining cost. Cracking and debonding of the reinforcement particles are the significant damage modes that directly affect the tool performance. This paper presents, an energy based analytical force model that has been developed for orthogonal cutting processes. The total specific energy for deformation has been estimated along with the energy consumed for debonding as a function of volume fraction and material properties. Orthogonal cutting tests were carried out for a range of different feeds on different matrix materials and volume fractions. The results showed good agreement between the predicted and measured cutting forces.

Surface Integrity of Die Material in High Speed Hard Machining, Part 2: Microhardness Variations and Residual Stresses

The main objective of this paper is to investigate the quality and integrity of the surface produced during high speed hard machining (HSHM) of D2 tool steel in its hardened state (60-62 HRc). Polycrystalline Cubic Boron Nitride (PCBN) tools are used in this study. The results obtained from the micro-graphical analysis of the surface produced are presented in Part 1 of this paper. In Part 2 micro-hardness and residual stress analyses are presented. Microhardness measurements are conducted beneath the machined surface. X-ray diffraction analysis is performed to obtain the residual stress distribution beneath the surface. Analytically, a 3-D thermo-elasto-plastic finite element model is developed to predict the residual stresses induced in the workpiece surface. In the model the cutting zone is specified based on the tool condition (i.e., sharp or worn). The finite element analysis demonstrates the significant effect of the heat generated during cutting on the residual stress distribution. The results illustrate the possibility of minimizing the high tensile residual stresses produced in the workpiece surface, by selecting the appropriate depth of cut. A good correlation between the analytical and predicted residual stress is obtained.

Tool wear and chip formation during hard turning with self-propelled rotary tools

Abstract This paper presents a performance assessment of rotary tool during machining hardened steel. The investigation includes an analysis of chip morphology and modes of tool wear. The effect of tool geometry and type of cutting tool material on the tool self-propelled motion are also investigated. Several tool materials were tested for wear resistance including carbide, coated carbide, and ceramics. The self-propelled coated carbide tools showed superior wear resistance. This was demonstrated by evenly distributed flank wear with no evidence of crater wear. The characteristics of temperature generated during machining with the rotary tool are studied. It was shown that reduced tool temperature eliminates the diffusion wear and dominates the abrasion wear. Also, increasing the tool rotational speed shifted the maximum temperature at the chip–tool interface towards the cutting edge.

Analytical Modeling of Tool Wear Progression During Turning Particulate Reinforced Metal Matrix Composites

This paper presents an analytical model for the prediction of tool flank wear progression during bar turning of particulate reinforced metal matrix composites. In this paper, a methodology for analytically predicting the wear progression as function of tool/workpiece properties and cutting parameters is presented. According to this approach, the wear volume due to two body and three body abrasion is formulated. Then, the flank wear rate is formulated by considering the tool geometry in 3D turning. Turning tests were carried out for a range of cutting speeds, tool nose radius and volume fraction of particles. The results showed good agreement between predicted and measured tool wear progression.

Flank Wear Progression During Machining Metal Matrix Composites

The machining of composites present a significant challenge to the industry. The abrasive reinforcements cause rapid tool wear and increases the machining cost. The results from machining metal matrix composites (MMCs) with conventional tools show that the main mechanism of tool wear includes two-body abrasion and three-body abrasion. A more flexible method that can be considered as a cost-saving technique is therefore sought for studying the machinability characteristics of these materials. In the previous paper, a methodology for predicting the tool flank wear progression during bar turning of MMCs was presented (Kishawy, Kannan, and Balazinski, Ann. CIRP, 54/1, pp. 55-59). In the proposed model, the wear volume due to two-body and three-body abrasion mechanisms was formulated. Then, the flank wear rate was quantified by considering the tool geometry in three-dimensional (3D) turning. Our main objective in this paper is to validate the proposed model by conducting extensive bar turning experiments under a wide range of cutting conditions, tool geometries, and composite material compositions. The cutting test results showed good agreement between predicted and measured tool wear progression.

Modelling of Material Side Flow in Hard Turning

In this paper an attempt has been made to model the material side flow generated during hard turning operation. A three dimensional thermo elasto-viscoplastic finite element model is presented. The model incorporates cutting tools with different nose radii and cutting conditions. The model was also used to investigate the effect of different process parameters on the extent of material side flow. The predicted results revealed that more side flow is generated when higher nose radius is used. A similar observation is noted when lower feed is used. The simulated results agreed well with the experimentally examined machined surface, viewed with a scanning electron microscope.

AN EXPERIMENTAL EVALUATION OF CUTTING TEMPERATURES DURING HIGH SPEED MACHINING OF HARDENED D2 TOOL STEEL

This paper investigates experimentally the effects of different process parameters on the cutting edge temperature during high speed machining of D2 tool steel using polycrystalline cubic boron nitride (PCBN) tools. The cutting edge temperature is measured using thermocouples. The process parameters considered are cutting speed, feed rate, nose radius, rake angle, and tool wear. The effects of different edge preparations including sharp, honed and chamfered are also investigated. The results show that increasing cutting speed and feed rate increases the cutting temperature while increasing nose radius reduces the cutting edge temperature. In addition, there is an optimum rake angle value at which minimum cutting temperature is generated.

Global adaptive slicing of NURBS based sculptured surface for minimum texture error in rapid prototyping

Purpose – This paper aims to propose a global adaptive direct slicing technique of Non-Uniform Rational B-Spline (NURBS)-based sculptured surface for rapid prototyping where the NURBS representation is directly extracted from the computer-aided design (CAD) model. The imported NURBS surface is directly sliced to avoid inaccuracies due to tessellation methods used in common practice. The major objective is to globally optimize texture error function based on the available range of layer thicknesses of the utilized rapid prototyping machine. The total texture error is computed with the defined error function to verify slicing efficiency of this global adaptive slicing algorithm and to find the optimum number of slices. A variety of experiments are conducted to study the accuracy of the developed procedure, and the results are compared with previously developed algorithms. Design/methodology/approach – This paper proposes a new adaptive algorithm which globally optimizes a texture error function produced by ...