Jung-Hwan Ahn

A robust trajectory tracking control of a polishing robot system based on CAM data

Abstract Polishing a die that has free-form surfaces is a time-consuming and tedious job, and requires a considerable amount of high-precision skill. In order to reduce the polishing time and cope with the shortage of skilled workers, a user-friendly automatic polishing system was developed in this research. The polishing system is composed of two subsystems, a three-axis machining center and a two-axis polishing robot. The developed polishing system with five degrees of freedom is able to keep the polishing tool normal to the die surface during operation. A sliding mode control algorithm with velocity compensation is proposed to reduce tracking errors. Trajectory tracking experiments showed that the effect of reducing the tracking error by the proposed sliding mode control is superior to that by the proportional derivative control. The polishing data is generated from computer-aided design (CAD) data or from teaching data by PolyCAM, a computer-aided manufacturing (CAM) system consisting of 4 modules: a geometric modeller, a CAD data exchange module, a polishing data generation module, and a graphic simulator. To evaluate the performance of the polishing robot system, some polishing experiments on a shadow-mask die were performed.

Real-time drill wear estimation based on spindle motor power

Abstract In-process detection of drill wear is one of the most important technologies for unmanned machining systems. This study examines and proposes the method of on-line drill wear estimation based on spindle motor power consumption during the drilling process. Integration of the drilling process model with the spindle drive system model is the key feature of the proposed method. The drilling process model describes the relationship between drill wear and drilling torque, whereas the spindle drive system model describes the relationship between drilling torque applied to motor and spindle motor power. Evaluation tests have shown that the proposed method is a good real-time estimator for drill wear.

Development of a sensor information integrated expert system for optimizing die polishing

Abstract This paper presents a polishing expert system integrated with sensor information which can modify the polishing sequence and conditions initially set by the system using the on-site polishing status detected. A practical system using AE sensors is developed for rotational and curved-surface polishing. A database and a knowledge base for polishing processes are established by using the results of experiments and also experts experience. Evaluations are performed for a die of an automobile headlight lamp by using both the sensor-integrated expert system and the expert system without sensor. The results show that the sensor-integrated expert system provides more optimal polishing conditions since the proposed system takes advantage of the on-line sensor information.

Development of a surface roughness measurement system using reflected laser beam

Abstract The scattered light pattern reflected from a machined surface generally contains much information concerning the surface roughness. This study examines and proposes a surface roughness measurement technique for the on-machine measurement of the roughness of machined surfaces. The technique is based on the measurement of scattered light patterns and the statistical analysis of the light intensity distribution. Scattered light patterns spread out narrowly in a direction vertical to the tiny scratches on the machined surface caused by tools. The deeper the scratch, the more dispersion there is, which indicates a rougher surface. The standard deviation of the scattered light pattern is nearly in proportion to the surface roughness. Measurements obtained using this method are within 10% of those obtained using a common contact method. Therefore, the proposed method is thought to be effective for use when a quick measurement is needed when a workpiece is fixed onto the machine.

Intelligently automated polishing for high quality surface formation of sculptured die

Abstract An intelligent polishing system that improves the surface quality of sculptured die surfaces on a 5-axis polishing machine including a pneumatic polishing head is proposed. In general, a mechanically automated polishing system has the critical drawback of not being able to adjust polishing conditions as adequately as an experienced operator can. One of the main reasons is that the system does not have sensors equal to human fingers that can adapt to the changing conditions of the polished surface. In the proposed system, acoustic emission (AE) sensors are adopted to detect even a tiny change of the polishing status. Based on the on-site status information, polishing conditions such as pressure, feed rate and tool mesh are adjusted in process to achieve better surface quality as fast as possible using an AE-based intelligent monitoring scheme.

Process monitoring of centerless grinding using acoustic emission

Abstract Because grinding is the most complicated of all machining processes, it is difficult for operators to set-up a grinding machine properly and to accurately find abnormal states that may damage products. Abnormalities in the grinding process can be caused by improper set-up or improper dressing/grinding conditions, which are likely to occur without skilled operator’s attention. This study developed an acoustic emission (AE) monitoring system that is able to detect such abnormalities. On-going process states during grinding/dressing are visualized based on sensed AE signals, which machine operators can use to judge whether or not the processes are in good condition. Evaluation tests are performed on centerless grinding machines of both cylindrical and internal type. The developed AE monitoring system was used to monitor the grinding/dressing process states, not only in cylindrical grinding but also in internal grinding, which has a more complicated process than other grinding methods.

Modeling of Eddy Current Sensor using Geometric and Electromagnetic Data

In this paper a new modeling method for an eddy current sensor is presented using geometric and electromagnetic data of a sensor and a measuring target It can predict not only sensor output but also medium behavior related to sensor output The geometric data of a sensor coil and the eddy current generated on a measuring target are simplified to an array of circular loops. And to perform computations of the network circuit between sensor coil loops and eddy current loops using the geometric and electromagnetic data in order to consider all possible interactions, the equivalent network circuit of eddy current sensor’s behavior has been drawn. Because the sensor’s initial value, medium behavior, and final value can be shown quantitatively by the proposed modeling method as the geometric and electromagnetic data varies, it can precisely predict the sensor output depending on the measuring goal and application field. Thus the model can be utilized to improve accuracy, eliminate the need for calibration before use, and produce the best design for any given purpose.

Chip disposal state monitoring in drilling using neural network based spindle motor power sensing

In this study, a monitoring method to detect chip disposal state in drilling system based on neural network was proposed and its performance was evaluated. If chip flow is bad during drilling, not only the static component but also the fluctuation of dynamic component of drilling. Drilling torque is indirectly measured by sensing spindle motor power through a AC spindle motor drive system. Spindle motor power being measured drilling, four quantities such as variance/mean, mean absolute deviation, gradient, event count were calculated as feature vectors and then presented to the neural network to make a decision on chip disposal state. The selected features are sensitive to the change of chip disposal state but comparatively insensitive to the change of drilling condition. The 3 layerd neural network with error back propagation algorithm has been used. Experimental results show that the proposed monitoring system can successfully recognize the chip disposal state over a wide range of drilling condition even though it is trained under a certain drilling condition.

Effects of Synchronizing Errors on Cutting Performance in the Ultra-High-Speed Tapping

Abstract Synchronizing errors between the spindle motor and the z-axis motor directly influences the cutting characteristics in tapping, because the tapping process is accomplished by synchronizing the movement of the z-axis with the revolutionary spindle motion. The excessive synchronizing error can cause tap breakage due to the abrupt increase of cutting torque or damage the thread accuracy by overcutting the already cut threads. This paper describes the effects of the synchronizing errors on the cutting performance in the ultra high-speed tapping and presents a minimum level of synchronizing errors necessary to maintain the quality of the cut thread.

A robust algorithm for roughness laser measurement based on light power regulation against specimen changes

Methods for measuring surface roughness based on light reflectivity have advantages over methods based on light interference or diffraction, especially in in-situ, on-the-machine and inprocess applications. However, measurement inconsistencies caused by changes in the specimen are still a drawback for field applications. In this study, we propose a new feedback-based algorithm to enhance the consistency against changes in the specimen. The algorithm is deduced from simulations based on light reflectance theory with typical modeled surfaces. The proposed method is similar to a digital controller and regulates the power of reflected light. Experiments varying heights and materials, verified the improvements in robustness of the method against measurement disturbances caused by specimen changes.