Papers by Keyword: Cutting Parameters

Abstract: In laser cutting processes, the removal of material is achieved without the application of external force, distinguishing it from traditional machining methods. An additional advantage of laser cutting is the ability to achieve desired surface quality in a single step, eliminating the need for additional finishing processes to smoothen and clean the cutting surface. To ensure the quality of the resulting cuts, a comprehensive understanding of the thermal behavior of the cut parts, influenced by the movement of the laser beam, is essential. The article focuses on the numerical simulation of the laser cutting process of the AISI 304 steel sheets with a thickness of 2 mm to investigate the impact of laser cutting parameters on transient thermal fields and the quality of the resulting cuts. A simulation model was developed and verified through temperature measurements during an experimental laser cutting process using the Bystronic Bysprint 3015 CO₂ Laser Cutting Machine. Numerical simulations in ANSYS software were used to design a working diagram showing the relationship between laser power and cutting kerf width for three different cutting speeds: 2000 mm.min^-1, 4000 mm.min^-1, and 5000 mm.min^-1.

Abstract: Electrostatic Discharge is a phenomenon that results from separating two dissimilar solid surfaces that were in contact. It results from the transfer of electrons from one surface to the other. Hence, one of the surfaces is positively charged, while the other surface becomes negatively charged. This phenomenon takes place during single point diamond turning of contact lenses polymers such as ONSI-56. Since higher electrostatic discharge adversely affects surface roughness, there is need to optimize electrostatic discharge machining parameters. The aim of this study is to develop an electrostatic discharge model and optimize the electrostatic discharge machining parameters during single point diamond turning of ONSI-56. Multiple regression has been utilized for model development and Genetic Algorithm (GA) has been used to optimize the model parameters. The GA toolbox in MATLAB is used for optimization in this study. In this study, cutting speed, depth of cut and feed rate are the model variables, while electrostatic discharge is the response variable. The regression model’s effectiveness has been evaluated by the R² value method. The model has an R² value of 88.29%, indicating that there is a strong collective significant effect among the control and response variables. Additionally, the results indicated that cutting speed and feed rate are the most significant predictors, while depth of cut is a slightly less significant predictor. The optimization process yields the following optimal values for cutting speed, feed rate, depth of cut and ESD, respectively: 200 rpm, 12 mm/min, 10 µm and 1,28 kV. An assessment of population size against objective function execution time has revealed that a population size of 500 has the shortest execution time of 14.23 seconds. The results have revealed that the optimization technique (GA) is efficient in ESD process optimization during single point diamond turning of ONSI-56.

Abstract: Traditional manufacturing and finishing operations of crystal products use intensive specialized labour resulting in high cycle times and production costs. It is intended to investigate the applicability of automated finishing technology, namely grinding in a CNC machining centre, with consideration of material’s characteristics and geometric variability to crystal processing. A case study will be presented, involving cutting tools development, cutting parameters optimization, CAM programming of machining strategies and toolpaths, product clamping systems and finally product machining and quality control that is being implemented at Vista Alegre Atlantis company.

Abstract: The adaptive control of metal cutting processes is a logical extension of the CNC systems. In CNC systems of metal-cutting processes the machining variables (e.g., the cutting speed and feedrate) are prescribed by the part programmer. The determination of these variables depends on experience and knowledge regarding the workpiece and tool materials, coolant conditions, and other factors.The determination of these operating parameters depends on experience and knowledgeregarding the workpiece and tool materials, coolant conditions, and other factors. By contrast,the main idea in adaptive control is the improvement of the production rate, or the reductionof machining costs, by calculation and setting of the optimal operating parameters duringmachining itself. This calculation is based upon measurements of process variables in real time and is followed by a subsequent on-line adjustment of the machining variables subject to constraints with the objective to optimize the performance of the overall system.The adaptive control is basically a feedback system, in which the operatingparameters automatically adapt themselves to actual condition of the process. AC system formachine tools can be classified into two categories:1.Adaptive control with optimization(ACO);2.Adaptive control with constraints(ACC);ACO refers to systems in which a given performance index (usually an economicfunction) is extremized subject to process and system constraints. With ACC, the machiningparameters are maximized within a prescribed region bounded by process and systemconstraints, such as maximum torque or power. ACC systems, however, do not use aperformance index. In both systems an adaptation strategy is used to vary the operatingparameters in real time cutting progresses. Although there has been considerable research onthe development of ACO systems, few, if any, of these systems are used in practice. The major problems with such systems have been difficulties in defining realistic indexes of performance and the lack of suitable sensors which can reliably measure on-line thenecessary parameters in a production environment. The objective of most AC systems isimprovement in productivity, which is achieved by increasing the metal removal rate (MRR)during rough cutting operations. The increases in productivity range from approximately 20 to 80 percent and clearly depend on the material being machined and the complexity of the part tobe produced.

Abstract: Pure titanium and its alloys are widely used in automotive industry, due to their high specific strength (strength/density) and excellent corrosion resistance, despite of their high cost. From point of view of machining, turning experiments of the pure titanium involve few input parameters (cutting speed, feed rate or depth of cut) and investigation of their influence on the response parameters of the cutting process (temperature in this case). Objectives of this study are to find the optimal combination of the input parameters, so that the temperature in turning of pure titanium to be minimum. In order to use a small number of experiments, two major tools, signal-to-noise (one of the three characteristic: nominal is the best, smaller the better or larger is better) and orthogonal array as statistical method can be used. For this study, a L₉ (3⁴) orthogonal array was considered adequate, so nine experiments was conducted using each factor (speed, feed and depth of cut) at three different levels.

Abstract: In order to control the temperature during milling process of aluminum alloys and keeping as minimum as possible, the choice of the cutting parameters and their optimization is very important, both for the tool wear but also for the surface quality of machined surface. The main purpose of this paper is to find the optimum values of the milling parameters (rotational speed and depth of cut) so that the minimum value for the temperature to be obtained. Using adequate experimental conditions with contact measurements techniques (thermocouple K-type) carried out on the some types of aluminum alloys and the appropriate statistical instruments, the most influencing cutting parameters and their values on the cutting temperature can be found. The results are presented both analytical and graphical.

Abstract: . An understanding of the dynamic characteristics of a CNC machine is a vital element in the control of the machine which has a direct effect on the machining precision. The ways in which energy is dissipated, such as friction and damping, have a significant effect on the dynamic behavior and spindle vibration of a CNC machine. The paper presents kinetic analysis of the CNC machine damper system, effect of the damper and the cutting parameters such as feed rate, cutting speed, and cutting depth on the dynamic behavior and spindle vibration of a CNC machine. Experimental results have established a second-order regression equation that demonstrates the effect of three parameters such as feed rate, cutting speed, and cutting depth on the vibration amplitude of the spindle. In addition, the comparison results show that the spindle head vibration amplitude of the machine using the damper is smaller than the spindle head vibration amplitude of the machine not using the damper.

Abstract: A technique and supporting software were designed to select optimal conditions for turning of ductile materials. Selection of optimal cutting parameters is based on a number of process requirements, including achieving the favourable chip form.

Abstract: Contact lens manufacture requires high accuracy and surface integrity. Surface roughness an important response because it has direct influence toward the part performance and the production cost. Hence, choosing optimal cutting parameters will not only improve the quality measure but also the productivity. This research work is therefore aimed at developing a predictive surface roughness model and investigate a finish cutting conditions of ONSI-56 contact lens polymer with a monocrystalline diamond cutting tool. In this work, a novel surface roughness prediction model, in which the feed rate, cutting speed and depth of cut are considered is developed. This combined process was successfully modeled using a Box–Behnken design (BBD) with response surface methodology (RSM). The effects of feed rate, cutting speed and depth of cut were investigated. Analysis of variance (ANOVA) showed that the proposed quadratic model effectively interpreted the experimental data with coefficients of determination of R² = 0.89 and adjusted R² = 0.84. The worse surface value was obtained at high feedrate and low spindle speed.

Abstract: The present work develops a learning methododology based on experiments related to the cutting temperature concept in turning processes. This proposal allows students to measure the temperature actually reached during a typical turning operation with a semi-automatic lathe. Temperature data are collected by a thermographic camera, which implies acquiring competences in this technique. The different tests involved in the practical experiment are defined for various cutting speeds and feed rates, and for a constant depth of cut. Two different materials are considered to point out the influence of turning parameters on cutting temperature.