The objective of this paper is to present a methodology for automatically balancing multi-cavity injection molds with the aid of flow simulation. After the runner and cavity layout has been designed, the methodology adjusts runner and gate sizes iteratively based on the outputs of flow analysis. This methodology also ensures that the runner sizes in the final design are machinable. To illustrate this methodology, an example is used wherein a 3-cavity mold is modeled and filling of all the cavities at the same time is achieved. Based on the proposed methodology, a multicavity mold with identical cavities is balanced to minimize overall unfilled volume among various cavities at discrete time steps of the molding cycle. The example indicates that the described methodology can be used effectively to balance runner systems for multi-cavity molds.

Research during the past several years has established the effectiveness of acoustic emission (AE)-based sensing methodologies for machine condition analysis and process. AE has been proposed and evaluated for a variety of sensing tasks as well as for use as a technique for quantitative studies of manufacturing process. STD11 has been known as difficult-to-cut materials. The micro-grooving machine was developed for this study and the experiments were performed using CBN blade for machining STD11. Evaluating the machining conditions, frequency spectrum analysis of acoustic emission (AE) signals according to each conditions were applied. Fuzzy clustering method for associating the preprocessor outputs with the appropriate decisions was followed by frequency spectrum analysis. FFT is used to decompose AE signal into different frequency bands in time domain, the root mean square (RMS) values extracted from the decomposed signal of each frequency band were used as features.

In this study, an experimental research of grinding characteristics using super-abrasives for surface carburized and heat treated SCM415 materials, which were usually used to make a linear motion guide block and were comparatively hard-to-machine materials, was carried out. In order to conduct a high efficiency and a accuracy grinding of such materials, grinding processes using CBN (Cubic boron nitride) and 38P grinding wheels have been attempted on a surface grinding machine. The grindability according to each grinding conditions was evaluated by means of a grinding force, a surface roughness and a residual stress. The experimental methods and results were presented in this paper. And also, from a proposed truing method the CBN wheels that combined a copper and a break truer gave a full scope to the wheel's performance.

This paper suggests a systematic methodology to predict chip forms using the experimental design technique and the neural network. Significant factors determined with ANOVA analysis are used as input variables of the neural network back-propagation algorithm. It has been shown that cutting conditions and cutting tool shapes have distinct effects on the chip forms, so chip breaking. Cutting tools are represented using the Z-map method, which differs from existing methods using some chip breaker parameters. After training the neural network with selected input variables, chip forms are predicted and compared with original chip forms obtained from experiments under same input conditions, showing that chip forms are same at all conditions. To verify the suggested model, one tool not used in training the model is chosen and input to the model. Under various cutting conditions, predicted chip forms agree well with those obtained from cutting experiments. The suggested method could reduce the cost and time significantly in designing cutting tools as well as replacing the“trial-and-error”design method.

The exit burrs in the micro-drilling of precision miniature holes are of interest, especially for ductile materials. As burrs from this process can be difficult to remove, it is important to acquire the way of predicting burr types as well as optimal cutting conditions which minimize the burrs. In this paper, an artificial neural network was used for the prediction of burr formation in micro-drilling. First, the influence of cutting conditions including cutting speed, feed and drill diameter on the exit burr characteristics, such as burr size and type, were observed and analyzed. Then. the burr types were classified by using the influential experimental data as input parameters to the neural nets.

In this paper, we propose a multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using multi-ultrasonic sensor. Instead of using “sensor fusion” method which generates the trajectory of a robot based upon the environment model and sensory data, “command fusion” method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as experiments with IRL-2002. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

When the driver suddenly depresses the brake pedal under critical conditions, the desired trajectory of the vehicle can be changed. In this study, the vehicle dynamics and fuzzy logic controller are used to control the vehicle trajectory. The dynamic vehicle model consists of the engine, the rotational wheel, chassis, tires and brakes. The engine model is derived from the engine experimental data. The engine torque makes the wheel rotate and generates the angular velocity and acceleration of the wheel. The dynamic equation of the vehicle model is derived from the top-view vehicle model using Newton's second law. The Pacejka tire model formulated from the experimental data is used. The fuzzy logic controller is developed to compensate for the trajectory error of the vehicle. This fuzzy logic controller individually acts on the front right, front left, rear right and rear left brakes and regulates each brake torque. The fuzzy logic controlling each brake works to compensate for the trajectory error on the split - $\mu$ road conditions follows the desired trajectory.

This paper represents a disturbance compensation control for attenuating disturbance responses. In the consideration of the requirements on the model accuracy in the model based compensator designs, an experimental feed forward compensator design based on adaptive estimation by Filtered-x least mean square (FXLMS) algorithm is proposed. The convergence properties of the FXLMS algorithm are discussed and its conditions for the asymptotic convergence are derived theoretically. The effectiveness of the proposed method and the theoretical proof are verified by computer simulation.

In this paper, based on the concept of solid particles' sediment problem the working formula determining the bowl length of a Decanter-type centrifuge were derived. Assuming that particles are uniformly distributed along the vertical line of the liquid inlet position, it was possible to derive a constant value k used for determining the bowl length. It was shown from the sample calculations that the bowl length should be increased as the particle size to be removed from the liquid is decreased. The length also should be increased for the same particle size as the bowl diameter is decreased. To help the engineers choose a reasonable bowl diameter, the statistical relationship between the bowl diameter and the capacity of the international products is obtained and presented.

GA(genetic algorithm) has a powerful searching ability and is comparatively easy to use and to apply as well. By that reason, GA is in the spotlight these days as an optimization skill for mechanical systems.$^1$However, GA has a low efficiency caused by a huge amount of repetitive computation and an inefficiency that GA meanders near the optimum. It also can be shown a phenomenon such as genetic drifting which converges to a wrong solution.$^{8}$ These defects are the reasons why GA is not widdy applied to real world problems. However, the low efficiency problem and the meandering problem of GA can be overcomed by introducing parallel computation$^{7}$ and gray code$^4$, respectively. Standard GA(SGA)$^{9}$ works fine on small to medium scale problems. However, SGA done not work well for large-scale problems. Large-scale problems with more than 500-bit of sere's have never been tested and published in papers. In the result of using the SGA, the powerful searching ability of SGA doesn't have no effect on optimizing the problem that has 96 design valuables and 1536 bits of gene's length. So it converges to a solution which is not considered as a global optimum. Therefore, this study proposes ExpGA(experience GA) which is a new genetic algorithm made by applying a new probability parameter called by the experience value. Furthermore, this study finds the solution throughout the whole field searching, with applying ExpGA which is a optimization technique for the structure having genetic drifting by the standard GA and not making a optimization close to the best fitted value. In addition to them, this study also makes a research about the possibility of GA as a optimization technique of large-scale design variable problems.

Pin-on-disk and hardness tests using mechanical components of M-20J aircraft braking system were performed to identify the friction and wear characteristics. The intention of this work was also to analyze a 5-year term maintenance record of an M-20J aircraft. used for flight training at Hankook Aviation University, and to determine the reliability of the brake system of an M-20J aircraft. The mean wear coefficients of the lining sliding against the brake disk were compared between the test and reliability estimation to obtain a predictive wear model.

An industrial product is designed and fabricated, followed by the inspection process in order to check whether it is dimensionally tolerable or not. The machining process produces a part such as a mold or die, in which the three-dimensional coordinate might be measured by a CMM (Coordinate Measuring Machine) for assessment of its dimension. It is not ignorable, however, that a CMM measurement requires a lot of operating time and cost, which has led to many studies on the OMM system. The OMM system can be categorized into contact and non-contact types, and each of which has its own strengths and weaknesses. Non-contacting types generally utilize structured lights, sounds or magnetic fields. Though they show rather poor performance in positional accuracy, the measuring speed is faster than the contacting probes. This paper presents the development of an OMM system based on a non-contacting laser displacement sensing apparatus and CAD model. The system is composed of software modules of center-aligning and measuring, which has been operated and verified on a NC machining center on a shop floor.

Domain switching effect on crack growth in ferroelectric ceramics under combined electric and mechanical loading is investigated. The shape and size of the switching zone is shown to depend strongly on the relative magnitude between the applied electric field and stress field as well as on the ratio of the coercive electric field to the yield electric field. The toughening mechanism is thought to be ferroelectric domain switching leading to the development of a process zone around the crack. Crack-tip stress intensity factor induced by domain switching for the steady state crack growth is numerically obtained.

In this paper, the large deformation of hollow silicon rubber gasket is treated. The frictional contact occurs between groove and the outer part of hollow gasket, and the frictional self-contact exists in the inner parts of hollow gasket. The silicon rubber has the nonlinear elastic behavior and its material property is approximately incompressible. Hence, the stress analysis requires an existence of a strain energy function, which is usually defined in terms of invariants or stretch ratio such as generalized Mooney-Rivlin and Ogden model. Considering large compressive deformation and friction, Mooney-Rivlin 3rd model and Coulomb's friction model are assumed. The numerical analysis is obtained by the commercial finite element program MARC. But, due to large deformation, the elements degenerate in the inner parts of hollow gasket. This means that the analysis of subsequent increments is carried out with a very poor mesh. In order to continue the analysis with a sufficient accuracy, it is necessary to use new finite element modeling by remesh. Experiments are also performed to show the validity of present method. As a conclusion, numerical results by this research have good agreements with experiments.

A specific experimental method, the Split Hopkinson pressure bar (SHPB) technique has been widely used to determine the dynamic material properties under the impact compressive loading conditions with strain rate of the order of 10$^3$/s∼l0$^4$/s. In this paper, dynamic deformation behaviors of rubber materials widely used for the isolation of vibration from structure under varying dynamic loading are determined by using plastic SHPB technique. A transition point to scope with the dynamic deformation behavior of rubber-like material is defined in this paper and used to characterize the specifics of the dynamic deformation of rubber materials.

Contouring errors are important especially for high speed and precision machining. In this study, contouring errors along contours having inflection points are studied. When a table of a machine tool moves along a circular path, acceleration acts toward the center of the circle. Thus, at inflection points, acceleration as well as inertia force changes its direction abruptly. The effect of inertia force on the contouring error is investigated in this study. It is found that the contouring error at an inflection point is proportional to the acceleration. This result can be useful in determining contouring errors along general paths.

This paper presents a rehabilitation exercise system which utilizes a 6 DOF robot as a motion generator. This system was proposed for a stroke patient or a patient who has hemiplegia. A master-slave system was designed to exercise either paralysis or abnormal limb by using normal limb motion. The study on the human body was applied to calculate the motion range of elbows and shoulders. In addition, a force-torque sensor was applied to the slave robot to estimate the rehabilitation extent of the patient. Therefore, the stability of the rehabilitation robot could be improved. By using the rehabilitation robot. the patients could exercise by themselves without assistance. In conclusion, the proposed system was verified by computer simulations and system experiment.

A CAD-based seamless design system for MEMS named DS/MEMS was developed which performs coupled-field analysis, optimal and robust design. DS/MEMS has been developed by means of integrating commercial codes and inhouse code-SolidWorks, FEMAP, ANSYS and CA/MEMS. This strategy results in versatility that means to include various analysis model, corresponding analyses and approximated design sensitivity analysis and user friendliness that design variables are taken to be selectable directly from a CAD model, that the problem is formulated under a window environment and that the manual job during optimization process is almost eliminated. DS/MEMS works on a parametric CAD platform, integrating CAD modeling, analysis, and optimization. Nonlinear programming algorithms, the Taguchi method, and response surface method are made available for optimization. One application problem is taken to illustrate the proposed methodology and show the feasibility of DS/MEMS as a practical tool.

To predict changes in biomechanical parameters such as intradiscal pressure, and the shock absorbing mechanism in the spinal motion segment under different impact duration/loading rates, a three dimensional L3/L4 motion segment finite element model was modified to incorporate the poroelastic properties of the motion segment. The results were analyzed under variable impact duration for normal and degenerated discs. For short impact duration and a given maximum compressive force, relatively high cancellous pore pressure was generated as compared with a case of long impact duration, although the amount of impulse was increased. In contrast relatively constant pore pressure was generated in the nucleus. Disc degeneration increased pore pressure in the disc and decreased pore pressure in the cancellous core, which is more vulnerable to compressive fracture compared with intact case.