Ching-Chih Tai

The effective factors in the warpage problem of an injection-molded part with a thin shell feature

Abstract Communication and electronic products have been developing towards the design concept of being light, thin, short, and small. To acquire the maximal internal space for parts to be packed closely into the product, one way is to reduce the wall thickness of the housing components. Therefore, the production technique of plastic injection molding of a part with a thin shell feature is becoming increasingly more important. Many factors lead to the defects of parts, such as warpage, shrinkage, sink marks, residual stress, and so on. This research used the experimental design of Taguchi method to determine the injection molding conditions, and the injection processes were simulated using the commercial software C-MOLD™. Both molding conditions and factors were discussed regarding the degree of warpage of a thin shell part. The results showed that the packing pressure had the greatest influence on the warpage, followed by mold temperature, melt temperature, and packing time. However, the warpage was only slightly influenced by the gate dimension and the filling time in thin shell injection molding. In addition, applying the experimental design of Taguchi method is a quite effective method to deduce the optimum set of effective factors in injection molding to produce plastic parts with minimum warpage.

The processing of data points basing on design intent in reverse engineering

The purpose of this paper is to describe an approach to process the data points, measured from existing objects, for feature-curve fitting in reverse engineering. In the field of reverse engineering, the major problem is that the original measured points with irregular format, and unequal distribution, and lack of appropriate segmentation are difficult to fit into a curve in CAD systems. Therefore, the technology of restoring and segmenting data points is greatly needed to construct the model of an existing object. The proposed approach has been developed to process the measured points with designer interaction to segment and regenerate the data points with the format, in which the points meet the requirements fitting into a B-spline curve with good shape and high quality. This approach consists of five steps: (1) sampling data points; (2) regressing the sampled points into an explicit non-parametric equation; (3) filtering the unwanted points with pre-determined tolerance; (4) regressing the residual points; and (5) regenerating data points from the second-time regressed equation. The proposed approach has been implemented by using an example for practical application, and the result proves the viability of the proposed approach integrating with the current commercial CAD systems.

The prediction of cutting forces in the ball-end milling process

Abstract This paper presents the development and verification of a predictive model for the force system in ball-end milling. The force model is essentially derived from metal cutting theory and for the geometric relations of the ball-end milling process. A concise method for characterizing the complex geometry of a ball-end mill is first determined. This method of generation not only simplifies the description of the geometry of the cutting edge, but also provides the basis for the determination of all geometric parameters to an accuracy commensurate with that needed for the oblique cutting process. The force model developed in able to deal with many of the process variables, including changes in the axial and radial depths of cut and in the feed-rate, as well as the eccentricity (run-out) inevitably found in practice. As a result, the predicted cutting forces show a fairly good agreement with the values from the verification experiments.

A predictive force model in ball-end milling including eccentricity effects

Abstract In this study, a new predictive force model in ball-end milling has been derived from a metal cutting theory and for the geometric relations of the ball-end milling process. It was necessary initially to define the cutting edge shape and then to determine the tool geometry of each cutting edge element by simple geometric procedures. The cutting edge on a ball-end mill can be considered as the curve of an intersection of a spherical surface with a skew plane. The advantage of this method is that the effects of the various parameters concerning the oblique cutting process can be readily calculated. The force model developed considers many of the process variables as well as the eccentricity (run-out) inevitably found in practice. The predicted and experimental results show good correlation and highlight the importance of the eccentricity on the forces and their fluctuations.

Model for cutting forces prediction in ball-end milling

Abstract This paper presents the development and verification of a predictive model for the force system in ball-end milling. The force model is essentially derived from metal cutting theory and for the geometric relations of the ball-end milling process. A concise method for characterizing the complex geometry of a ball-end mill is first determined. This method of generation not only simplifies the description of the geometry of the cutting edge, but also provides the basis for the determination of all geometric parameters to an accuracy commensurate with that needed for the oblique cutting process. The force model developed is able to deal with many of the process variables, including changes in the axial and radial depths of cut and in the feedrate, as well as the eccentricity (runout) inevitably found in practice. As a result, the predicted cutting forces show a fairly good agreement with the values from the verification experiments.

A runner-optimization design study of a die-casting die

Abstract Die casters usually carry out a die casting test before producing new castings. At the die-casting test stage, the runner part is always repeatedly corrected, which leads to a lengthened processing time and increased processing cost. In order to solve this problem, research studies of the runner and die body parts have been performed separately during the present experiments. For the runner part, different insert runner blocks have been made and a die-casting teat was designed according to the experiment design method. In addition, an abductive network for the modeling of die casting has been built. The abductive network is composed of a number of functional nodes. Once the die-casting parameters (high-speed injector position, runner injection angle, runner sectional ratio) are given, the die-casting performance (runner residual stress and temperature of the point near the die cavity surface) can be predicted accurately by this network. The optimal die-casting parameters can be searched for by a simulation annealing optimization algorithm with a performance index.

The optimal position for the injection gate of a die-casting die

Abstract This study explores a computer integrated system application in the design of a die-casting mold, in order to enable accurate and fast determination of the optimal position for the material injection gate. Finite elements are used to find the deformation of various sizes of thin shell piece, after which a deformation learning prediction is made with an adductive network. A simulation annealing (SA) optimization algorithm with a performance index is then applied to the neural network in order to search for the optimal position of the injection gate, with quite satisfactory results being obtained. The system is capable of being applied on the die, in order to reduce wastage on the cost trials of the die.

The optimisation deep-draw clearance design for deep-draw dies

In this paper, the modelling of deep-drawing processing using neural networks is established. The relationships between process parameter (material thickness, punch diameter, die-cavity diameter and materials-clearance ratio) and deep-drawing performance (the dimensional error of diameter and cylinder) are created, based on a neural network. A simulated annealing (SA) optimisation algorithm with a performance index is then applied to the neural network to search for the optimal design parameters of the drawing-die. Experimental results have shown that deep-drawing performance can be enhanced by using this approach.

The optimization accuracy control of a die-casting product part

Abstract The accurate prediction of die-casting performance is essential for the design of die-casting dies, the main purpose being to produce an accurate part, but the effecting factors in a good design are the decision of the mold-surface, the runner shape and operating conditions. In order to understand the practical conditions in die casting, this research studies the runner part and the die-body parts separately during the process of experiment. A die-casting and mold-milling test has been designed according to the experimental methods. A finite element method was used to obtain the displacement and deformation from the measurement of the temperature in the cavity or by simulation in order to be able to find the optimum gate position of the design-mold. An abductive network for the modeling of the die casting and milling process, and the results of the finite element method, has been built. The abductive network is composed of a number of functional nodes. Once the die-casting parameters (the high-speed injection position, the runner injection angle, the runner sectional ratio, and gate position) or milling parameters (the spindle speed, the feed rate, and the milling angle) are given, the die-casting performance (the mold accuracy and the accuracy of the product part) can be predicted accurately by this developed network. A simulation annealing optimization algorithm with a performance index to obtain a perfect part can search for the optimal die-casting design parameters.

The runner optimisation design of a die-casting die and the part produced

The accurate prediction of die-casting performance is essential for the design of die-casting dies. The main purpose of die design is to produce an accurate part, but a key role in a good design is also the design of the runner. In order to understand the practical conditions in die casting, this paper studies the runner part and die body parts which have been considered separately during the experiment. A die-casting test has been designed according to experimental methods and the runners have a total of 23 sets of tests.A finite-element method was used to obtain the displacement from the measurement of the temperature in the cavity, and an abductive network has been built for modelling the diecasting process. The abductive network is composed of a number of functional nodes. Once the die-casting parameters (high-speed injected position, runner injected angle, runner sectional ratio) are given, the die-casting performance (the displacement) can be accurately predicted by this network. The optimal die-casting parameters can be searched for by a simulation annealing optimisation algorithm using a performance index to obtain a perfect part.