Zone-Ching Lin

Evaluation of machine selection by the AHP method

Abstract This paper is concerned with the development of a model using the analytic hierarchy process (AHP) for the selection of the most suitable machine, from a range of machines available for the manufacture of particular types of part. A typical example of the application of the model is presented.

An investigation of a coupled analysis of a thermo-elastic-plastic model during warm upsetting

Abstract The primary purpose of this paper is to construct a thermo-elastic-plastic model which can be utilized in the simulation of a more realistic metal forming process under a warm forming condition. In this model flow stress is taken as a function of strain, strain rate and temperature. The finite element method and the finite difference method are adopted to simulate the whole forming process. The strain is taken by a Taylors series expansion and is associated with its corresponding convergent criterion, an available scheme for the calculation of the strain rate is thus evolved. Furthermore, the strain rate and temperature effect during the warm upsetting process are also investigated. The temperature predicted in the proposed model for the upsetting process agrees quite well with Pohls experimental data.

Effect of thermal load and mechanical load on the residual stress of a machined workpiece

Abstract A method for calculating the residual stress in a machined workpiece is developed in this paper. The concept of particle flow and a thermo-elasto-plastic finite element program are used in this method. The residual displacement in the subsurface layer of the machined workpiece is also found by integrating the residual strain with respect to the depth of plastic deformation under the machined surface. The computed result for the residual displacement is then compared with the experimental results of Stevenson and Oxley.

A study of cutting with a CBN tool

Abstract The objective of this paper is to study the various cutting characteristics of a CBN tool when it is used in cutting hardened steel, BZN tool inserts of the General Electric Company being used to cut 52100 bearing steel (HRc 64) in the cutting experiments. Based on the resulting experimental data, certain cutting characteristics when a CBN tool is used for cutting this type of hardened material, such as tool life, cutting forces, surface roughness and tool wear, are analyzed. Finally, regressive equations are developed within the experimental applications.

Cost-tolerance analysis model based on a neural networks method

The purpose of tolerance design in product components is to produce a product with the least manufacturing cost possible, while meeting all functional requirements of the product. The product designer and process planner must fully understand the process accuracy and manufacturing cost of all kinds of manufacturing process to perform a good process plan job. Usually, the cost-tolerance model is constructed by a linear or non-linear regression analysis based on the data of the cost-tolerance experiment and to derive the correlation curve between the two. Though these correlation curves can show the relationship between manufacturing cost and tolerance, a fitting error is inevitable. In particular, there is considerable discrepancy in terms of the non-experimental data. A cost-tolerance analysis model based on a neural networks method is proposed. The cost-tolerance experimental data are used to set the training sets to establish a cost-tolerance network. Three representation modes of the cost-tolerance relationship are presented. First, the cost-tolerance relationship is derived from the grid points setting by the required tolerance accuracy. Second, a reasonable manufacturing cost of an unknown cost-tolerance experimental pair can be derived by the simulation of a cost-tolerance network. Third, an inference model based on a networks output is proposed to express the scope of the cost variation of various tolerances by means of a cost band. Comparison is also made with the high-order polynomial power function and exponential function cost-tolerance curves adopted by Yeo et al . Analytical results prove that the application of the cost-tolerance analysis model based on neural networks yields better performance in controlling the average fitting error than all conventional fitting models. The representation model using a cost band can identify precisely the possible cost variation range and reduce the chances of error in the tolerance design and cost estimation. It can thus provide important references for tolerance designers and process planners.

A thermoelastic-plastic large deformation model for orthogonal cutting with tool flank wear—Part I: Computational procedures

Abstract A coupled model of a thermoelastic-plastic material undergoing large deformation during orthogonal cutting with a pre-honed land simulating tool flank wear is constructed. A coupled method in which deformation is analysed using the finite element method and transient heat transfer with a finite difference method including special numerical techniques is developed. The cutting tool is incrementally advanced forward in a step-by-step process from the incipient stage of tool-workpiece engagement to a steady state of chip formation. A chip separation criterion based on the critical value of the strain energy density is introduced into the analytical model and a scheme of twin node processing is presented for chip formation in this model. A numerical technique of gradually reducing displacement was developed to deal with the generation of new nodes of contact with the tool flank. Convergence criteria and techniques are also developed in this paper.

Design of the cooling channels in nonrectangular plastic flat injection mold

Abstract The complex variables and parameters with respect to the design of cooling channels in nonrectangular plastic flat injection mold are investigated. Vector and simple mathematical calculations were used to solve problems related the deployment of cooling channels caused by different geometric dimensions of molded products. Furthermore, the basic geometry characteristic surface symbols and database were established. Next, the basic geometry characteristic surface was used to compose and present the shapes of molded product on the basis of a rectangular plastic flat. The conversion concept of equivalent area was also introduced to simplify the selection of model and deployment of cooling channels for nonrectangular plastic flat containing milder changes in shape. The optimization of cooling time in the first stage is based on the energy balance. A concise formula was used, with empirical algorithm as the constraint of optimization design, to locate the optimal cooling time and the required optimal geometric factor constraints. Then, the optimization of channel deployment was derived to achieve the requirement of fast and uniform cooling of the mold. The method proposed in this paper is capable of handling a nonrectangular plastic flat product through the conversion to an equivalent rectangular area. This method simplifies the channel deployment problem of a molded product caused by nonuniform distribution of heat source and reduces the instances of trial and error. Furthermore, the method proposed for the system framework is capable of completing the optimization faster than conventional finite difference method, which saves the time spent in designing the cooling channels and achieves fast and uniform cooling of finished products.

An investigation of an expert system for shearing cut progressive die design

The purpose of this paper is to develop an expert system for shearing cut progressive die, with the aim of enhancing the design of shearing cut progressive dies. This study is different from previous research on shearing cut die design by the author in that the design of one station was extended into a progressive die design. The major research objectives achieved in this study can be summarised as follows:1.This study presents a pattern recognition method called the new combined structural approach to let the user interpret blanks by a better and more direct method, thereby achieving the goal of communicating with this expert system.2.The layout of the strip can affect the material cost shared by the press-worked pieces. This study presents the near optimal method for seeing a better layout of the strip in order to save material.3.Owing to the great variety of blank shapes which cause the variations in pressing procedures, this study proposes a matching combination learning method, which is a learning conscious system for pressing procedures, in order to obtain the optimal number of operation stations in shearing cut progressive die design.4.The establishment of the knowledge-base system for shearing cut progressive die should improve the efficiency for die design problems.

The study of ultra-precision machining and residual stress for NiP alloy with different cutting speeds and depth of cut

Abstract The non-electrolytic NiP alloy is a special material developed to improve the machinability of nickel for ultra-precision cutting. The application of the coupled thermo-elastic–plastic model in a new cutting material often lacks the flow stress function. To overcome this problem, the data from an uni-axial tension experiment were used in this study to regress the flow stress and obtain the stress function. The simulation process achieved through the large deformation finite element method is used to analyze the distribution changes of the cutting force, strain and stress of the NiP workpiece under different orthogonal cutting conditions. The chip formation, the distribution of the temperature field of the workpiece and chip and the residual stress of the workpiece generated after cutting can all be obtained to determine the effect of these cutting conditions on the processing of the workpiece.

Application of fuzzy set theory and back-propagation neural networks in progressive die design

Abstract Fuzzy set theory is introduced to process the design details of the uncertainty portion of die design and assist the designer in transforming design items with fuzziness into definite and reasonable design attributes. For design parameters in die design that possess intermediate features, fuzzy cluster analysis is used to obtain design attributes. For theoretical or empirical formulas possessing uncertainty coefficients ranges or preference design parameters, the fuzzy weighted average method is adopted to obtain the feature parameters that conform to die design requirements. For the design of uncertain operation stations, such as the installation of an idle station, the linguistic fuzziness or linear membership function is matched with the network recall value and learning pattern through neural network learning, and then the designer can decide whether it is necessary to install such an operation station. Finally, this study establishes an expert system prototype to combine the uncertainty problems in three kinds of die design and help the designer obtain a definite design strategy while faced with uncertain design items.