Chi-Hao Yeh

Automated visual inspection for microdrills in printed circuit board production

The rapid growth in printed circuit board production has led to the growing importance of microdrilling. Owing to the trend for high-density circuits on printed circuit boards, the diameter of a microdrill has to be much finer than ever before. The inspection for microdrills becomes more difficult and the detection of defects is harder. An automated visual inspection scheme for detecting the major defects of microdrills is proposed. The colour images of microdrills are first derived, and the boundary of the lip relief plane is extracted. A robust K-curvature corner detection algorithm is then used to detect the corners on the blade boundaries and to split boundaries into segments. The least-squares linear regression method is used to fit the segments into linear equations. With the fitted equations, the intersections on the boundaries of two facets are located and their distances (gap or overlap) are measured. In addition, the defects of taper and flare are identified by comparing the angle measurements with predefined specifications. Two types of microdrills are used to verify the proposed inspection process. Experimental results show that the proposed scheme reliably achieves precise inspection.

A Wavelet-Based Approach in Detecting Visual Defects on Semiconductor Wafer Dies

The objective of this paper is to implement a two-dimensional wavelet transform (2-D WT) approach for detecting visual defects such as particles, contamination, and scratches on semiconductor wafer dies. The gray image of 1/20 of a wafer die is initially processed by smooth and high-pass filters. Then, it is decomposed directly by 2-D WT at multiple scales and different wavelet bases. The interscale ratio from the wavelet transform modulus sum (WTMS) across adjacent decomposition levels (scales) for suspicious pixels on a wafer die is calculated. Since irregular edges in a small domain preserve much more wavelet energy, an edge pixel potentially belongs to a visual defect if its interscale ratio is less than a predefined threshold. The proposed approach is template-free and is easy to implement, so it is suitable for more product varieties and small-batch production. Real wafer dies with synthetic defects are used as testing samples to evaluate the performance of proposed approach. Experimental results from a small amount of testing samples show that the proposed method is able to identify particle, contamination, and scratch defects without missed detection and false alarm by appropriate choice of wavelet bases, scale, and image resolution. The proposed inspection approach could be considered as a potentially precise and low detection error method for further large amounts of inspections in a real environment.

A comparative study on optimization methods for experiments with ordered categorical data

When conducting experiments, the selected quality characteristic should as far as possible be a continuous variable and be easy to measure. Due to the inherent nature of the quality characteristic or the convenience of the measurement technique and cost-effectiveness, the data observed in many experiments are ordered categorical. To analyze ordered categorical data for optimizing factor settings, there are three widely accepted approaches: Taguchis accumulation analysis, Nairs scoring scheme and Jengs weighted probability scoring scheme. In this paper, a simpler method named the weighted SN ratio method for analyzing ordered categorical data is introduced. A case study involving optimizing the polysilicon deposition process for minimizing surface defects and achieving the target thickness in a very large-scale integrated circuit can demonstrate the four approaches. Finally, comparative analyses of efficiency for employing the four approaches to optimize factor settings are presented according to simulated experimental data that are normally, Weibull and Gamma distributed. From the results, it is obvious that the weighted SN ratio method has the properties of easy computation and uses one-step optimization to obtain the optimal factor settings. Its efficiency is slightly less than that of the scoring scheme, better than that of the accumulation analysis and the weighted probability-scoring scheme.

Validation and evaluation for defect-kill-rate and yield estimation models in semiconductor manufacturing

This study evaluates the accuracy of two alternative models for the kill rate of different visual defects and the yield estimation by using large amount of practical inspection data (140 6-inch wafers containing 70 560 dies) in semiconductor manufacturing. One model assumed that the visual defects are randomly distributed on a wafer die; another model considered that clustering visual defects may occur on a wafer die. The results show that two models are both capable of predicting the yield precisely. The results also suggest that the model assuming clustering visual defects on a die is more accurate based on the analysis of Taguchis signal-to-noise (SN) ratio. The same practices can be implemented with other types of wafer such as 8 inch and 12 inch. Precise prediction for the kill rate of different types of visual defects and the yield in the long supply of semiconductor industry is critical since the requirement of material and the reserved capacity can be largely reduced.

The synergy of QFD and TRIZ design practice — A case study for medical care bed

The aim of this research is to integrate QFD and TRIZ theories into innovative principles of the medical care bed design. The use of QFD matrix expansion and its importance for evaluation and analysis to build the front-end preventive design process that will meet customer needs, the evaluation is based on the order of importance, the quality characteristics of the target specifications and quality characteristics of correlation matrix. The analytical data can be used to assist in resolving the conflicts of the TRIZ innovative principles to solve engineering problems and developing new concepts to meet customers specific demands, and then apply TRIZ to define the points on anti-bedsore, perform ideality analysis and find useful resources. After doing the Table of Contradictions, TRIZ 40-principle and single characteristic principle are good to find solutions on improving anti-bedsore design. They can also provide the medical care bed design staff with more effective ways to accelerate the product development and to increase market competitiveness.

Robust design of nonlinear dynamic problem

Taguchis robust design is a popular methodology utilized within many different industries in order to improve product quality and process performance at low cost. The robust design of dynamic system is used to find the optimal control factor settings so that the measured response is closest to the ideal function. Although Taguchis robust design was effective in improving performance of products or processes, the statisticians pointed to inefficiencies in the method for highly nonlinear problems and complexity of the parameter design. This paper proposes a general model for optimizing the robust design of dynamic system parameter based on the quality loss function. The objective is to minimize the average quality loss instead of maximizing SN ratio suggested by Taguchi. The example of high-precision positioning device is provided to demonstrate the implementation and effectiveness of the proposed method.

An Image Enhancement Technique in Inspecting Visual Defects of Polarizers in TFT-LCD Industry

This study develops an image-processing filter to enhance the visual defects such as particles, stains, and uneven intensity on polarizers in TFT-LCD industry. Each pixel in the subimage of a polarizer is initially processed to calculate its standard deviation (SD) of gray level, which is sampled by its neighbors within a window. The gray level of each pixel is re-scaled by the maximal and minimal SD values on entire subimage to determine its new gray level. Real polarizers with visual defects are tested in this study. Experimental results show that the proposed filter achieves better performance than conventional image enhancement filters do. Moreover, the proposed image enhancement scheme provides more information for potential defect detection and classification alternatives. The proposed filter is simple, straightforward, and requiring no high-resolution image. Therefore, it is practically suitable for large-polarizer manufacturers to increase inspection speed.

Boundary-based passive component inspection approach using eigenvalues of covariance matrices

A boundary-based scheme to inspect basic dimensions and surface defects on solder plates (terminations) of passive components by using the eigenvalues of covariance matrices was developed. The image of the passive component was initially processed to show only two terminations. The eigenvalues of covariance matrices for boundary points, which are equivalent to curvature measurements, then generate a one-dimensional representation describing the angle variations on termination boundaries. Since a single corner (intersection of two boundary edges) and jagged corners (a surface defect) are local deviations on termination boundaries, their locations will be represented as highly fluctuating eigenvalue waveforms. By setting an appropriate threshold on the eigenvalues, the surface defects and single corners on the termination boundaries can be identified. The basic dimensions of a passive component are determined simply by the distances between the detected single corners. Real passive components (0805 MLCCs) are testing samples to evaluate the performance of the proposed approach. Experimental results show that the proposed approach achieves precise identification for surface defects and measurement for the basic dimensions. The proposed approach is precise, rotation invariant and template free. Therefore, it is especially suitable for small batch production of various types of passive components.

Robust design of unlinearized dynamic system

Reducing the variations in manufacturing processes and minimizing the quality loss of products are the fundamental elements of robust design. The robust design of dynamic system is used to find the optimal control factor settings so that the measured response is closest to the ideal function. Although Taguchis robust design was effective in improving performance of products or processes, the statisticians pointed to inefficiencies in the method for highly nonlinear dynamic systems and complexity of the parameter design. This paper proposes a general model for optimizing the robust design of multiple nonlinear dynamic systems based on the quality loss function and minimizing error variance while keeping the response on target. The example of unbalanced automobile drive shafts is provided to demonstrate the implementation and effectiveness of the proposed method.

Validation of kill-rate and yield model for clustering visual defects in semiconductor manufacturing

This paper validates the kill rate for different types of visual defects and resulting yield by using large amount of real inspection data in semiconductor manufacturing. Visual defects are assumed to be distributed in cluster. The results of this estimation model is slightly different from real inspection data. Therefore, this model is feasible to estimate the kill rate and the yield of mature product. However, since the corresponding manufacturing process for a new product may often result in multiple visual defects on a die. That can be verified by incorporating real inspection data of new product and this estimation model as well