This paper introduces non-manifold offsetting operations, which add or remove a uniform thickness from a given non-manifold model. Since these operations can be applied to not only solids but also wireframe or sheet objects, they are potentially useful for pipeline modeling, sheet metal and plastic part modeling, tolerance analysis, clearance checking, constant-radius rounding and filleting of solids, converting of abstracted models to solids, HC too1 path generation and so on. This paper describes mathematical properties and algorithms for non-manifold offsetting. In this algorithm, a sufficient set of tentative faces are generated first by offsetting all or a subset of the vertices, edges and faces of the non-manifold model. And then they are merged into a model using the Boolean operations. Finally topological entities which are within offset distance are removed. The partially modified offsetting algorithms for wireframes or sheets are also discussed in order to provide more practical offset models.

Several adaptive and direct slicing methods have been developed to make the slice data for RP parts with better accuracy and speed. This research deals with a new adaptive slicing algorithm that shows drastic improvement in computing time for calculating the slices of a part. First, it uses less number of sampling points fur each slice in determining the thickness of the next slice. Secondly, the idea of contour map is utilized to determine the optimal sampling point on each slice. Thirdly, the calculation efficiency is further improved by introducing vertical character lines of the given part. The results in terms of accuracy and speed are compared with the existing methods.

The deflection yoke (DY) controls the direction of the electron beam that falls on the screen of the television monitor. Its quality depends on the shape and density of coils wound around the DY coil separator. Winding frames are used to make these coils, and therefore, their shapes are essential in making quality coils. A reverse engineering(RE) is applied to create the 3D model of the winding frame. It considerably shortens the design verification time and shows the level of accuracy that is feasible in the production mode. The paper explains each step of the reverse engineering process in detail.

This paper deals with a development of the system that implements a collaborative design environment with some intelligent agents on the m. Intelligent agents can design collaboratively trough an interchange of messages in their special domains. Such a collaborative design of agents is achieved on the WWW. In this paper, we propose special agents named intercessor and DCM (Dynamic Connection Manager) and suggest new connection architecture using these agents in the WWW in order to improve the pre-existed agent connection architecture. The proposed agents are developed using Java language and JATLite API. We apply the these agents to the new architecture and show some possibilities that the agent connection architecture can be extended in the WWW Agents interchange messages with others using KOML (Knowledge Query and Manipulation Language), agent communication protocol and language, and deal with message autonomously according to their rule base. Agents register and connect dynamically trough the intercessor agent, and infer from their.

Recently, the various driving simulator have been used widely to analyze the handling performance of vehicle and to verify the motion control algorithm of vehicle. In this study, a virtual driving simulator based on the 20-DOF vehicle model is realized to estimate the handling performance and stability of a 4WS (Four-wheel-steering) and/or 4n(Four-wheel-driving) vehicle. Especially the DC motor controlled 4WS actuator is modelled in order to reflect the effect of the responsiveness of actuator on the handling performance and stability. And the realized simulator can be applied to develope a real time simulation system for designing and testing the real vehicles.

Finite element analysis is very important in the design and analysis of mechanical engineering. The process of FEA encompasses shape modeling, mesh generation, matrix solving and post-processing. Some of these processes can be tightly integrated with the current software architectures and data sharing mode. However, complete integration of all the FEA process itself and the integration to the manufacturing processes is almost impossible in the current practice. The barriers to this problem are inconsistent data format and the enterprise-wise software integration technology. In this research, the information model based on STEP AP209 was chosen for handling finite element analysis data. The international standard for the FEA data can bridge the gap between design, analysis and manufacturing processes. The STEP-based FEA system can be further tightly integrated to the distributed software and database environment using CORBA technology. The prototype FEA system DICESS is implemented to verify the proposed concepts.

Genetic programming (GP) is an extension of a genetic algoriths paradigm, deals with tree structures representing computer programs as individuals. In recent, there have been many research activities on applications of GP to various engineering problems including system identification, data mining, function approximation, and so forth. However, standard GP suffers from the lack of the estimation techniques for numerical parameters of the GP tree that is an essential element in treating various engineering applications involving real-valued function approximations. Unlike the other research activities, where nonlinear optimization methods are employed, I adopt the use of a weighted linear associative memory for estimation of these parameters under GP algorithm. This approach can significantly reduce computational cost while the reasonable accurate value for parameters can be obtained. Due to the fact that the GP algorithm is likely to fall into a local minimum, the GP algorithm often fails to generate the tree with the desired accuracy. This motivates to devise a group of additive genetic programming trees (GAGPT) which consists of a primary tree and a set of auxiliary trees. The output of the GAGPT is the summation of outputs of the primary tree and all auxiliary trees. The addition of auxiliary trees makes it possible to improve both the teaming and generalization capability of the GAGPT, since the auxiliary tree evolves toward refining the quality of the GAGPT by optimizing its fitness function. The effectiveness of this approach is verified by applying the GAGPT to the estimation of the principal dimensions of bulk cargo ships and engine torque of the passenger car.

Solid modeling refers to techniques for unambiguous representations of three-dimensional objects. Feature recognition is a sub-discipline focusing on the design and implementation of algorithms for detecting manufacturing information such as holes, slots, etc. in a solid model. Automated feature recognition has been an active research area in stolid modeling for many years, and is considered to be a critical component for CAD/CAM integration. This paper gives a technical overview of the state of the art in feature recognition research. Rather than giving an exhaustive survey, I focus on the three currently dominant feature recognition technologies: graph-based algorithms, volumetric decomposition techniques, and hint-based geometric reasoning. For each approach, I present a detailed description of the algorithms being employed along with some assessments of the technology. I conclude by outlining important open research and development issues.