Download or read book Studies on Process Optimization Based on the Cutting Force Prediction Model of an Artificial Neural Network for Five axis Milling written by and published by . This book was released on 2015 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advanced Numerical Methods to Optimize Cutting Operations of Five Axis Milling Machines written by Stanislav S. Makhanov and published by Springer Science & Business Media. This book was released on 2007-04-18 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents new optimization algorithms designed to improve the efficiency of tool paths for five-axis NC machining of sculptured surfaces. The book covers both the structure of the SLAM problem in general and proposes a new extremely efficient approach. It can be used by undergraduate and graduate students and researchers in the field of NC machining and CAD/CAM as well as by corporate research groups for advanced optimization of cutting operations.
Download or read book Machining Dynamics and Parameters Process Optimization written by Gorka Urbicain and published by MDPI. This book was released on 2021-03-19 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: As we move further into the 21st century, despite the fact that new technologies have emerged, machining remains the key operation to achieve high productivity and precision for high-added value parts in several sectors, but recent advances in computer applications should close the gap between simulations and industrial practices. This book, “Machining Dynamics and Parameters Process Optimization”, is oriented toward the different strategies and paths when it comes to increasing productivity and reliability in metal removal processes. The topics include the dynamic characterization of machine tools, experimental dampening techniques, and optimization algorithms combined with signal monitoring.
Download or read book Advanced Virtual Simulation for Optimal Cutting Parameters Control in Five Axis Milling written by Hendriko and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study presents a simple method to define the Cutter Workpiece Engagement (CWE) during sculptured surface machining in five-axis milling. The instantaneous CWE was defined by determining two engagement points, lowermost engagement (LE)-point and uppermost engagement (UE)-point. LE-point was calculated using a method called grazing method. Meanwhile the UE-point was calculated using a combination of discretization and analytical method. During rough milling and semi-finish milling, the workpiece surface was represented by vertical vector. The method called Toroidal-boundary was employed to obtain the UE-point when it was located on cutting tool at toroidal side. On the other hand, the method called Cylindrical-boundary was used to calculate the UE-point for flat-end cutter and cylindrical side of toroidal cutter. For a free-form workpiece surface, a hybrid method, which is a combination of analytical method and discrete method, was used. All the CWE models proposed in this study were verified and the results proved that the proposed method were accurate. The efficiency of the proposed model in generating CWE was also compared with Z-mapping method. The result confirmed that the proposed model was more efficient in term of computational time. The CWE model was also applied for supporting the method to predict cutting forces. The test results showed that the predicted cutting force has a good agreement with the cutting force generated from the experimental work.
Download or read book Modern Optimization Techniques for Advanced Machining written by Imhade P. Okokpujie and published by Springer Nature. This book was released on 2023-07-21 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced manufacturing via computer numerical machining is the art of producing mechanical components employed in aerospace, automobile, and industrial applications where a high level of accuracy is needed. This book focuses on the nano-machining of aluminum alloy and its optimization. The application of aluminum alloy in the manufacturing industry has increased tremendously due to its lightweight to high strength ratio and high-level resistance to corrosion. However, aluminum alloy has some challenges during the machining and manufacturing stage in order to solve real-life manufacturing challenges in advanced machining operation for sustainable production processes. Therefore, it is a need for the implementation of a general algebraic modeling system (GAMS) and other metaheuristic techniques for problem solving and to effectively develop mathematical models for high accuracy prediction and optimization under nano-lubrication machining conditions. This book discusses majorly on the major three responses in machining such as surface roughness, cutting force, and material removal rate, which will give an excellent guide to undergraduate and postgraduate students, senior research fellows in academia, operational, and strategic staff in manufacturing industries.
Download or read book Virtual Three axis Milling Process Simulation and Optimization written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The ultimate goal in the manufacturing of a part is to achieve an economic production plan with precision and accuracy in the first attempt at machining. A physics-based comprehensive modeling of the machining processes is a fundamental requirement in identifying optimal cutting conditions which result in high productivity rates without violating accuracy throughout the part production process. This thesis presents generalized virtual simulation and optimization strategies to predict and optimize performance of milling processes up to 3-axis. Computationally efficient mathematical models are introduced to predict milling process state variables such as chip load, force, torque, and cutting edge engagement at discrete cutter locations. Process states are expressed explicitly as a function of helical cutting edge - part engagement, cutting coefficient and feedrate. Cutters with arbitrary geometries are modeled parametrically, and the intersection of helical cutting edges with workpiece features are evaluated either analytically or numerically depending on geometric complexity. The dynamics of generalized milling operations are modeled and the stability of the process is predicted using both time and frequency domain based models. These algorithms enable rapid simulation of milling operations in a virtual environment as the part features vary. In an effort to reduce machining time, a constraint-based optimization scheme is proposed to maximize the material removal rate by optimally selecting the depth of cut, width of cut, spindle speed and feedrate. A variety of user defined constraints such as maximum tool deflection, torque/power demand, and chatter stability are taken into consideration. Two alternative optimization strategies are presented: pre-process optimization provides allowable depth and width of cut during part programming at the computer aided manufacturing stage using chatter constraint, whereas the post-process optimization tunes only feedrate and spindl.
Download or read book Simulation and Tool Path Optimization for the Hexapod Milling Machine written by Shangjian Du and published by Vulkan-Verlag GmbH. This book was released on 2005 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: To fully exploit the advantages of multi-axis machining in a modern production environment, new types of parallel kinematic machines (PKM) and new processing technologies such as those using high speed cutting (HSC) are needed. However, the machining accuracy and hence the process reliability of PKM are still not satisfactory when using today's CAM systems due to the complexity of the dynamic behavior of machine axes. A hybrid simulation method for optimizing tool paths that overcomes the limits of today's CAM systems is presented in this work. Two major independent simulations were performed, to examine the influences on the quality of the final product. It is shown that the kinematics, the dynamics and the stiffness are important factors affecting the accuracy of PKM. These factors can be taken into account, to obtain an accurate modeling of PKM-behavior.
Download or read book Machining Recent Advances Applications and Challenges written by Luis Norberto L´opez de Lacalle and published by MDPI. This book was released on 2019-08-26 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Special Issue Machining—Recent Advances, Applications and Challenges is intended as a humble collection of some of the hottest topics in machining. The manufacturing industry is a varying and challenging environment where new advances emerge from one day to another. In recent years, new manufacturing procedures have retained increasing attention from the industrial and scientific community. However, machining still remains the key operation to achieve high productivity and precision for high-added value parts. Continuous research is performed, and new ideas are constantly considered. This Special Issue summarizes selected high-quality papers which were submitted, peer-reviewed, and recommended by experts. It covers some (but not only) of the following topics: High performance operations for difficult-to-cut alloys, wrought and cast materials, light alloys, ceramics, etc.; Cutting tools, grades, substrates and coatings. Wear damage; Advanced cooling in machining: Minimum quantity of lubricant, dry or cryogenics; Modelling, focused on the reduction of risks, the process outcome, and to maintain surface integrity; Vibration problems in machines: Active and passive/predictive methods, sources, diagnosis and avoidance; Influence of machining in new concepts of machine–tool, and machine static and dynamic behaviors; Machinability of new composites, brittle and emerging materials; Assisted machining processes by high-pressure, laser, US, and others; Introduction of new analytics and decision making into machining programming. We wish to thank the reviewers and staff from Materials for their comments, advice, suggestions and invaluable support during the development of this Special Issue.
Download or read book Prediction of Cutting Forces in Five axis Micro ball End Milling written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machining Simulation and Cutting Force Prediction with GPGPU written by Balázs Tukora and published by LAP Lambert Academic Publishing. This book was released on 2012 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the use of general-purpose graphics processing units (GPGPU) for material removal simulation and cutting force prediction of multi-axis machining processes. A research is presented in this subject that has two main goals. The first is to create a material removal simulation technique for 5-axis machining that enjoys the benefits of the highly parallel program execution on general-purpose graphics processing units, the newest generation of graphics hardware. This means the minimizing of the CPU intervention in data conversion, data representation and processing, and visualization. The second part of the work focuses on the applicability and feasibility questions of the mechanistic cutting force model. It has been assumed that two main objectives must be fulfilled to make the model more effective in practice. First of all, the way of force-calculation must be reconstructed to fit the requirements of the real-time multi-axis simulation. Secondly, the method of determining the coefficients - which play an important role in the force equations - must be fastened and simplified. The book presents the way these aims have been reached with the use of GPGPU.
Download or read book A New Geometric and physics Model of Milling and an Effective Approach to Medial Axis Transforms of Free form Pockets for High Performance Machining written by Quiang Fu and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Milling Simulation written by Weihong Zhang and published by John Wiley & Sons. This book was released on 2016-06-15 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reliable scheduling in cutting conditions is very important in machining processes, and this requires thorough understanding of the physical behaviors of the machining process, which cannot be achieved without understanding the underlying mechanism of the processes. The book describes the mechanics and dynamics together with the clamping principles in milling processes, and can be used as a guideline for graduate students and research engineers who wish to be effective manufacture engineers and researchers. Many books have focused on common principles, which are suitable for general machining processes, e.g., milling, turning and drilling, etc. This book specifically aims at exploring the mechanics and dynamics of milling processes. Original theoretical derivations and new observations on static cutting force models, dynamic stability models and clamping principles associated with milling processes are classified and detailed. The book is indented as a text for graduate students and machining engineers who wish to intensively learn milling mechanism and machine tool vibration.
Download or read book A Neural Networks based In process Adaptive Surface Roughness Control NN IASRC System in End milling Operations written by Po-Tsang Bernie Huang and published by . This book was released on 2002 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this research, the neural networks-based in-process adaptive surface roughness control (NN-IASRC) system employing multiple cutting tools was successfully developed for end-milling operations. The dynamometer sensor was used to monitor the uncontrolled cutting tool conditions to increase the accuracy of the surface roughness control. An empirical approach was applied to discover the proper cutting force signals, the average resultant peak force in XY plane (F[Subscript ap]) and the absolute average force in the Z direction (F[Subscript az]). These two forces were employed to represent the uncontrollable cutting tool conditions for surface roughness control. A statistical method was employed to verify that the cutting tools could influence the surface roughness, and obtain the correlation between surface roughness and the cutting force signals for the preparation of constructing the NN-IASRC system. A neural networks theorem was successfully applied to build the NN-IASRC system. The neural networks associated with sensing technology were applied as a decision-making technique to control the surface roughness for a wide range of machining parameters. The NN-IASRC system consisted of two subsystems. One was the in-process neural networks based surface roughness prediction (INN-SRP) system, which was employed to predict the surface roughness. The other was the neural networks based adaptive machining parameters control (NN-APMC) system, which was utilized to adjust the adaptive degree of feed rate when the quality of predicted surface roughness did not fit the desired one. The accuracy of the INN-SRP system was 93%, and 100% for the NN-IASRC system. The high accuracy of results within a wide range of machining parameters indicates that the system can be practically applied in industry.
Download or read book AI Based Modelling and Optimization of Turning Process written by Ruturaj Jayant Kulkarni and published by . This book was released on 2012 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, Artificial Neural Network (ANN) technique is used to model and simulate the Turning Process. Significant machining parameters (i.e. spindle speed, feed rate, and, depths of cut) and process parameters (surface roughness and cutting forces) are considered. It is shown that Multi-Layer Back Propagation Neural Network is capable to perform this particular task. Design of Experiments approach is used for efficient selection of values of parameters used during experiments to reduce cost and time for experiments. The Particle Swarm Optimization methodology is used for constrained optimization of machining parameters to minimize surface roughness as well as cutting forces. ANN and Particle Swarm Optimization, two computational intelligence techniques when combined together, provide efficient computational strategy for finding optimum solutions. The proposed method is capable of handling multiple parameter optimization problems for processes that have non-linear relationship between input and output parameters e.g. milling, drilling etc. In addition, this methodology provides reliable, fast and efficient tool that can provide suitable solution to many problems faced by manufacturing industry today.
Download or read book Technical Digest written by and published by . This book was released on 2000 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Metals Abstracts written by and published by . This book was released on 1995 with total page 1302 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Development of the Analysis and Optimization Strategies for Prediction of Residual Stresses Induced by Turning Processes written by Morteza Sadeghifar and published by . This book was released on 2017 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: Difficult-to-machine materials are widely used in the aerospace and automotive industries including landing gears of aircrafts, drive-shafts of automobiles, and high strength bolts and frame parts of airplanes and motorsports due to their high toughness, less sensitivity to heat, and high resistance to fatigue and corrosion. Machining these materials is accompanied by high cutting temperatures and forces, which cause high residual stresses. It is known that high temperature leads to inaccuracies in component dimensions and causes phase transformation in the material. High cutting forces also raise the power consumption of turning machines and result in an excessive deflection and consequently breakage of the tool. Also, both large cutting temperatures and forces cause high tool wear. Most importantly, machining-induced tensile residual stresses have detrimental effects on the performance of components due to having the tendency to open tiny cracks and speed up crack propagation, which subsequently results in decreasing the resistance to fatigue and corrosion. In contrast, high compressive residual stresses have beneficial effects as they tend to close cracks and slow down crack propagation, which consequently increases the fatigue life considerably. The machining process is required to be efficient by removing as large amount of material as possible, meaning to have a high material removal rate. Machining forces, temperature, residual stresses, and material removal rate depend highly on machining parameters including cutting conditions and tool geometry. Therefore, a thorough optimization study is required to be conducted to identify optimal machining parameters including cutting speed, feed rate, edge radius, rake angle, and clearance angle to improve response variables specially residual stresses, which will be highly desirable and of paramount importance to the industry. More particularly, when the optimization is carried out based on Finite Element Method (FEM), by which the expensive, time-consuming process of experimental tests is avoided, the outcome will be more economical for the industry.Finite Element (FE) modeling of orthogonal turning is considered as an open-ended subject as most of the phenomena involved in the orthogonal turning, which also exist in other machining operations, are not fully understood. In the present research work, first, a predictive high-fidelity finite element model is developed using Abaqus software to obtain response variables of cutting temperature, machining forces, and residual stresses induced by orthogonal turning 300M Steel. The validity of the developed FE model is then verified by comparing the predicted machining forces, chip thickness, and residual stresses with those of experimental tests obtained in turn using a piezoelectric dynamometer, a digital micrometer, and ‘X-Ray diffraction apparatus, electropolishing equipment, and a profilometer machine’. The FE model is then utilized to systematically derive response functions (Meta or surrogate models) for desired FE outputs using D-optimal Design of Experiment (DoE) and Response Surface Method (RSM). The derived response functions explicitly relate the desired responses to identified design parameters, and therefore, can be effectively utilized for design optimization problems without using the FE model. Finally, multi-criteria optimization problems are formulated to reduce superficial residual stresses individually and improve a combination of residual stresses, cutting temperature, cutting and thrust forces, and material removal rate by obtaining optimum values of machining parameters including cutting speed, feed rate, edge radius, rake angle, and clearance angle. Special attention is devoted to minimizing the machining-induced residual stresses. Optimization is conducted using a hybrid method of Genetic Algorithm (GA) and Sequential Quadratic Programming (SQP) technique in order to accurately capture the global optimum values of machining parameters and response variables. The optimization results show considerable improvement in the total objective function and especially residual stresses. Since there are no research studies on the finite element simulation, experimental test, and most importantly, constrained and unconstrained multi-performance optimization of machining characteristics and residual stresses for radial turning of 300M steel, the results of the present research can be utilized as a reference for future works along this field.
