Yung C. Shin

Radial basis function neural network for approximation and estimation of nonlinear stochastic dynamic systems

This paper presents a means to approximate the dynamic and static equations of stochastic nonlinear systems and to estimate state variables based on radial basis function neural network (RBFNN). After a nonparametric approximate model of the system is constructed from a priori experiments or simulations, a suboptimal filter is designed based on the upper bound error in approximating the original unknown plant with nonlinear state and output equations. The procedures for both training and state estimation are described along with discussions on approximation error. Nonlinear systems with linear output equations are considered as a special case of the general formulation. Finally, applications of the proposed RBFNN to the state estimation of highly nonlinear systems are presented to demonstrate the performance and effectiveness of the method.

Optimization of machining conditions with practical constraints

This paper presents a model for the optimization of machining conditions in a multi-pass turning operation. Both rough cutting and finishing cutting are considered in the model and dual optimization of cost functions for each subproblem is pursued. The preventive tool replacement strategy used in practice is incorporated. Machining idle time is also regarded as a variable. After practical constraints are established, optimization is carried out using the dynamic programming method. An example illustrates the formulation of the problem and the optimization procedure

Experimental Investigation of Thermo-Mechanical Characteristics in Laser-Assisted Machining of Silicon Nitride Ceramics

Laser-assisted machining (LAM) of silicon nitride (Si 3 N 4 ) is evaluated for its potential to become an economically viable process in fabricating precision ceramic parts. On-line measurements of cutting force and workpiece temperature are performed, and tool wear and surface integrity are examined. Tool wear characteristics are determined as a function of workpiece temperature, which is measured on-line using a laser pyrometer Tool wear/failure mechanisms are characterized using optical microscopy while application of scanning electron microscopy to heated and machined surfaces, as well as to chips, is used to infer material removal mechanisms and the extent of damage caused by LAM. The sub-surface damage of parts produced by LAM is compared with that of typical ground parts.

Transient, three-dimensional heat transfer model for the laser assisted machining of silicon nitride: I. Comparison of predictions with measured surface temperature histories

Abstract Laser assisted machining (LAM), in which the material is locally heated by an intense laser source prior to material removal, provides an alternative machining process with the potential to yield higher material removal rates, as well as improved control of workpiece properties and geometry, for difficult-to-machine materials such as structural ceramics. To assess the feasibility of the LAM process and to obtain an improved understanding of governing physical phenomena, experiments have been performed to determine the thermal response of a rotating silicon nitride workpiece undergoing heating by a translating CO 2 laser and material removal by a cutting tool. Using a focused laser pyrometer, surface temperature histories were measured to determine the effect of the rotational and translational speeds, the depth of cut, the laser-tool lead distance, and the laser beam diameter and power on thermal conditions. The measurements are in excellent agreement with predictions based on a transient, three-dimensional numerical solution of the heating and material removal processes. The temperature distribution within the unmachined workpiece is most strongly influenced by the laser power and laser-tool lead distance, as well as by the laser/tool translational velocity. A minimum allowable operating temperature in the material removal region corresponds to the YSiAlON glass transition temperature, below which tool fracture may occur. In a companion paper [1] , the numerical model is used to further elucidate thermal conditions associated with laser assisted machining.

Experimental Evaluation of the Laser Assisted Machining of Silicon Nitride Ceramics

To assess the feasibility of the laser assisted machining (LAM) process for the machining of difficult-to-machine materials such as structural ceramics, experiments were performed on silicon nitride workpieces for a wide range of operating conditions. Data for cutting forces and surface temperatures indicate that the lower bound of the material removal temperature for avoidance of cutting tool and/or workpiece fracture corresponds to the YSiAlON glass transition temperature (920-970°C). As temperatures near the cutting tool increase to values above the glass transition temperature, the glassy phase softens, facilitating visco-plastic flow and, correspondingly, the production of semi-continuous or continuous chips. The silicon nitride workpiece machined had a surface roughness of R a =0.39 μm at the nominal LAM operating condition. Examination of the machined surfaces and chips reveals no detectable sub-surface cracking or significant changes in | microstructure, respectively. Relative to grinding, the most significant advantage of LAM is its ability to achieve much larger material removal rates with high workpiece surface quality and reasonable levels of tool wear.

Hybrid machining of Inconel 718

Abstract A new approach for machining of Inconel 718 is presented in this paper. It combines traditional turning with cryogenically enhanced machining and plasma enhanced machining. Cryogenically enhanced machining is used to reduce the temperatures in the cutting tool, and thus reduces temperature-dependent tool wear to prolong tool life, whereas plasma enhanced machining is used to increase the temperatures in the workpiece to soften it. By joining these two non-traditional techniques with opposite effects on the cutting tool and the workpiece, it has been found that the surface roughness was reduced by 250%; the cutting forces was decreased by approximately 30–50%; and the tool life was extended up to 170% over conventional machining.

A comprehensive chatter prediction model for face turning operation including tool wear effect

This paper presents a three-dimensional mechanistic frequency domain chatter model for face turning processes, that can account for the effects of tool wear including process damping. New formulations are presented to model the variation in process damping forces along nonlinear tool geometries such as the nose radius. The underlying dynamic force model simulates the variation in the chip cross-sectional area by accounting for the displacements in the axial and radial directions. The model can be used to determine stability boundaries under various cutting conditions and different states of flank wear. Experimental results for different amounts of wear are provided as a validation for the model.

A comprehensive dynamic cutting force model for chatter prediction in turning

Abstract This paper presents a model of the dynamic cutting force process for the three-dimensional or oblique turning operation. To obtain dynamic force predictions, the mechanistic force model is linked to a tool–workpiece vibration model. Particular attention was paid to the inclusion of the cross-coupling between radial and axial vibrations in the force model. The inclusion of this cross-coupling facilitates prediction of the unstable–stable chatter phenomenon which usually occurs in certain cases of finish turning due to process non-linearity. The dynamic force model developed was incorporated into a computer program to obtain time-saving chatter predictions. Experimental tests were performed on AISI 4140 steel workpieces to justify the chatter predictions of the dynamic cutting process model in both the finishing and roughing regimes. Experimental results corroborate the unstable–stable chatter predictions of the model for different cases of finish machining. In addition, experimental results also confirmed the accuracy of chatter predictions for various cases of rough turning.

Laser-Assisted Machining of Magnesia-Partially-Stabilized Zirconia

Laser-assisted machining (LAM) of magnesia-partially-stabilized zirconia (PSZ) is investigated to determine the effect of heating on machinability, as determined by tool wear, cutting energy, surface integrity, and material removal mechanisms. It is found that PSZ can be successfully machined with a polycrystalline cubic boron nitride tool and that tool life increases with material removal temperature up to a maximum of 121 minutes. The benefit of laser-assistance in material removal is also demonstrated by the 2.5 fold decrease in the specific cutting energy with increased temperature. It is shown surface roughness varies significantly with tool wear with little dependence on cutting temperature unlike in LAM of other ceramics. Evidence of mixed brittle and ductile material removal mechanisms is presented, and the optimum condition within the test matrix is established.

Analysis on high-speed face-milling of 7075-T6 aluminum using carbide and diamond cutters

This research is concerned with the analytical and experimental study on the high-speed face milling of 7075-T6 aluminum alloys with a single insert fly-cutter. The results are analyzed in terms of cutting forces, chip morphology, and surface integrity of the workpiece machined with carbide and diamond inserts. It is shown that a high cutting speed leads to a high chip flow angle, very low thrust forces and a high shear angle, while producing a thinner chip. Chip morphology studies indicate that shear localization can occur at higher feeds even for 7075-T6, which is known to produce continuous chips. The resultant compressive residual stresses are shown for the variation of cutting parameters and cutting tool material. The analysis of the high-speed cutting process mechanics is presented, based on the calculation results using extended oblique machining theory and finite element simulation.