Browsing by Author "Tong, LI"

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A neural network-based procedure for the process monitoring of clustered defects in integrated circuit fabrication
(1997-12-01)
Su, CT
;
Tong, LI
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
In integrated circuit (IC) fabrication, a wafer's defects tend to cluster. As the wafer size increases, the clustering phenomenon of the defects becomes increasingly apparent. When the conventional control chart (c chart) is used, the clustered defects frequently cause many false alarms. In this study, we propose a neural network-based procedure for the process monitoring of clustered defects in IC fabrication. The proposed procedure can reduce the phenomenon of the false alarms caused by the clustered defects. A case study is also presented to show the effectiveness of the proposed procedure. (C) 1997 Elsevier Science B.V.
A neural network-based procedure for the process monitoring of clustered defects in integrated circuit fabrication
(1997-12-01)
Su, CT
;
Tong, LI
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
In integrated circuit (IC) fabrication, a wafer's defects tend to cluster. As the wafer size increases, the clustering phenomenon of the defects becomes increasingly apparent. When the conventional control chart (c chart) is used, the clustered defects frequently cause many false alarms. In this study, we propose a neural network-based procedure for the process monitoring of clustered defects in IC fabrication. The proposed procedure can reduce the phenomenon of the false alarms caused by the clustered defects. A case study is also presented to show the effectiveness of the proposed procedure. (C) 1997 Elsevier Science B.V.
An innovative model of multi-project wafer service in the foundry industry
(2005)
Yang, TY
;
Tong, LI
;
Yuan, BJC
;
工業工程與管理學系
;
科技管理研究所
The cost of masks is rising rapidly as semiconductor manufacturing technology advances. This increase in cost is a major issue in the development of new products. This study focuses mainly on the business demands of semiconductor design companies who verify the prototypes and produce small-volume wafers, and analyses the constraints on the current Multi-Project Wafer (MPW) model. A new MPW model is proposed to reduce the mask cost and the unit die cost simultaneously. The proposed MPW model allows customers to find the optimal solution to the mask cost and unit die cost according to the chip size and the number of dice required. This study also compares the current model with the proposed MPW model using 0.13 um technology, as an example. For a purchased quantity of dice from a few thousand to less than a hundred thousand, the proposed MPW model yields the lowest sum of the mask cost and the dice cost. Since this ran-e of dice quantities covers more than half of the dice required for semiconductor products, the proposed MPW model can help the semiconductor industry to resolve the conflict between the mask cost and the unit die cost that is caused by the constraints on the current MPW model. When the technology advances to the 90 nm generation, and requested die quantities increased to more than 100,000, the small-volume MPW model proposed in this study will still yield the lowest mask cost and total dice cost.
Analyzing type II censored data obtained from repetitious experiments
(2006-01-01)
Tong, LI
;
Yang, CH
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Experimental design and Taguchi's parameter design are widely employed by industry to optimize the process/product. However, censored data are often observed in product lifetime testing during the experiments. After implementing a repetitious experiment with type II censored data, the censored data are usually estimated by establishing a complex statistical model. However, using the incomplete data to fit a model may not accurately estimates the censored data. Moreover, the model fitting process is complicated for a practitioner who has only limited statistical training. This study proposes a less complex approach to analyze censored data, using the least square estimation method and Torres's analysis of unreplicated factorials with possible abnormalities. This study also presents an effective method to analyze the censored data from Taguchi's parameter design using least square estimation method. Finally, examples are given to illustrate the effectiveness of the proposed methods.
Bootstrap confidence interval of the difference between two process capability indices
(2003)
Chen, JP
;
Tong, LI
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
The process capability index, C-pk, is extensively used to assess process performance in manufacturing industry. Statistical hypothesis testing or an interval estimation of a single C-pk had been derived under a normally distributed process. However, the difference between two process capabilily indices, C-pk1 - C-pk2, cannot be inferred statistically because of the complexily of the sampling probability theory. This study proposes a bootstrap resampling simulation method to construct the biased corrected percentile bootstrap (BCPB) confidence interval Of (C-pk1 - C-pk2), which can be used to select the better of two suppliers. The various simulation results indicate that the bootstrap confidence interval Of (C-pk1 - C-pk2) can be employed to evaluate effectively the difference between the performance of two suppliers.
Dynamic multiple responses by ideal solution analysis
(2004-07-16)
Tong, LI
;
Wang, CH
;
Chen, CC
;
Chen, CT
;
工業工程與管理學系
High technology industry must continuously improve product quality and multiple correlated product quality characteristics must be assessed simultaneously due to product complexity. While many Taguchi method applications have addressed a state system problem, dynamic multi-response problems have seldom been examined. This study presents a novel optimization procedure for dynamic multiple responses based on Taguchi's parameter design. The signal to noise (SN) ratio and system sensitivity are used to assess the performance of each response. Principal component analysis is then performed on the SN values and system sensitivity values to obtain a set of uncorrelated components. The optimization direction for each component is also determined based on the corresponding variation mode chart. Finally, the relative closeness to the ideal solution resulting from the technique for order preference by similarity to ideal solution is determined as an overall performance index for multiple responses. A case study obtained from biological reduction of an ethyl acetoacetate process demonstrates the effectiveness of the proposed procedure. (C) 2003 Elsevier B.V. All rights reserved.
Incorporating process capability index and quality loss function into analyzing the process capability for qualitative data
(2006-02-01)
Hsieh, KL
;
Tong, LI
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Process capability analysis (PCA) is frequently employed to evaluate a product or a process if it can meet the customer's requirement. In general, process capability analysis can be represented by using the process capability index (PCI). Until now, the PCI was frequently used for processes with quantitative characteristics. However, for process quality with the qualitative characteristic, the data's type and single specification caused limitations of using the PCI. When the product can not meet the target, even if it lies in the specified range, it should lead to the corresponding quality loss. Taguchi developed a quadratic quality loss function (QLF) to address such issues. In this study, we intend to construct a measurable index which incorporates the PCI philosophy and QLF concept to analyze the process capability with the consideration of the qualitative response data. The manufacturers can not only employ the proposed index to self-assess the process capability, but they also can make comparisons with the other competitors .
Manufacturing performance evaluation for IC products
(2006-03-01)
Hsieh, KL
;
Tong, LI
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
As we known, the product diversity and complexity in the production line will gradually increase. When the multiple products were alternately produced at the same line, the manufacturing performance will be difficult to evaluate. In particular, traditional process capability analysis and related process capability indexes cannot be directly employed to the IC manufacturing process. As we know, the yield has a direct effect on the manufacturing cost. Hence, yield is frequently used by most IC manufacturers to evaluate manufacturing performance. The diversity of function will become another analytic consideration due to that the component density, wafer area and product complexity of an IC product rapidly increase. Hence, the diversity of function can be regarded as the evaluated factor. Additionally, the defects on a wafer will begin to cluster as the wafer area gradually increases. Therefore, only using the yield to represent manufacturing performance may not lead to an appropriate judgment. In particular, only using the yield to evaluate the process's stability and the product's maturity can not provide a meaningful resolution. The primary reason is that the inherent features in the processes or products are not included into analyzing. For instance, even though the defect count, defect size and defect distribution are the same, the yield loss of the complicate manufactured product will be less than that of the simple manufactured product. In this study, we propose a simple performance evaluation index to assess the manufacturing performance in the IC manufacturing industry. This evaluation index is constructed according to a modified Poisson yield model, and the related parameters regarding the process or product (e.g., the minimum linewidth, the area of a die, the number of manufactured process or layer, the degree of defect clustering, and so on.) are taken into consideration. In addition, an integrated evaluation procedure is also suggested to evaluate the performance of the manufacturing of multiple IC products. According to the result obtained from the illustrative example, the index and the procedure can overcome the drawback of separately using yield or defect count in the analysis. The rationality and the feasibility of the proposed evaluated index and the procedure can be verified by demonstrating the illustrative example.
Modified process control chart in IC fabrication using clustering analysis
(1997)
Tong, LI
;
Lee, WI
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Monitoring defects in IC fabrication using a hotelling T-2 control chart
(2005-02-01)
Tong, LI
;
Wang, CH
;
Huang, CL
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Monitoring the wafer defects in integrated circuit (IC) fabrication is essential for enhancing wafer yield. However, significant defect clustering occurs when the wafer is large, so the conventional defect control chart, based on the Poisson distribution, is inappropriate. Defect clustering must also be analyzed to monitor effectively defects in ICI fabrication process control. This study developed a novel procedure using the multivariate Hotelling T-2 control chart, based on the number of defects and the defect clustering index (CI) to monitor simultaneously the number of defects and the defect clusters. The CI does,not require any statistical assumptions concerning the distribution of defects and can accurately evaluate the clustering phenomena. A case study of a Taiwanese IC manufacturer demonstrates the effectiveness of the proposed procedure.
Multi-response optimization using principal component analysis and grey relational analysis
(2002-12-01)
Tong, LI
;
Wang, CH
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Taguchi's method is a highly effective means of improving product/process quality for extensive industrial applications. More than one quality characteristic must be simultaneously considered to evaluate the product quality in light of the increasing complexity of product designs. Most Taguchi method practitioners employ engineering judgment to determine the final optimal factor/level combination when several responses are to be optimized. However, this approach is very subjective and always brings some uncertainty to the decision-making process. Furthermore, moderate or strong correlations among multiple responses always exist and these correlations may create serious conflicts when determining the optimal factor/level combination. Additionally, the relative importance among responses must also be considered when employing Taguchi's method to simultaneously optimize multiple responses. This study presents an alternative approach based on Principal Component Analysis (PCA) and Grey Relational Analysis (GRA) to determine an Overall Quality Performance Index (OQPI) for multiple responses. A case study that optimizes the chemical-mechanical polishing of copper (Cu-CMP) thin films from an integrated circuit manufacturer in Taiwan demonstrates the effectiveness of the proposed procedure.
Multi-response robust design by principal component analysis
(1997-12-01)
Su, CT
;
Tong, LI
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Most previous Taguchi method applications have only addressed a single-response problem. However, more than one correlated response normally occurs in a manufactured product. The multi-response problem has received only limited attention. In this work, we propose an effective procedure on the basis of principal component analysis (PCA) to optimize the multi-response problems in the Taguchi method. With the PCA, a set of original responses can be transformed into a set of uncorrelated components. Therefore, the conflict for determining the optimal settings of the design parameters for the multi-response problems can be reduced. Two case studies are evaluated, indicating that the proposed procedure yields a satisfactory result.
Optimization of a multi-response problem in Taguchi's dynamic system
(2005-12-01)
Hsieh, KL
;
Tong, LI
;
Chiu, HP
;
Yeh, HY
;
工業工程與管理學系
Taguchi method was known as an off-line quality control methodology to be used in many industries. Until now, most applications only focus on optimizing a single-response in a static system. Furthermore, due to the increasing complexity of the product design, more than one quality characteristic must be considered simultaneously to improve the production quality. Therefore, there are several studies to address the multi-response problem. In order to satisfy the requirements of the production's design, optimization of a dynamic system been mentioned by Taguchi has received more attentions in the recent years. Hence, optimizing a multi-response problem in a dynamic system becomes an important issue to address the quality improvement. This study proposes a procedure utilizing the statistic regression analysis and desirability function to optimize the multi-response problem with Taguchi's dynamic system consideration. Firstly, the regression analysis is employed to screen out the control factors significantly affecting the quality variation, and the adjustment factors significantly affecting the sensitivity of a Taguchi's dynamic system. Then, the desirability function will be applied to optimize such a multi-response problem. Finally, the effectiveness of the proposed procedure will be demonstrated by an example of a biological reduction of ethyl acetoacetate process experiment project at the Union Chemical Laboratories of the Industrial Technology Research Institute in Taiwan. (c) 2005 Elsevier Ltd. All rights reserved.
Optimization of multiple quality responses involving qualitative and quantitative characteristics in IC manufacturing using neural networks
(2001-08-01)
Hsieh, KL
;
Tong, LI
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
The optimization of product or process quality profoundly influences a manufacturer. Most studies have focused primarily on optimizing a quantitative (or qualitative) quality response, while others have concentrated on optimizing multiple quantitative quality responses. However, optimizing multiple responses involving both qualitative and quantitative characteristics have scarcely been mentioned, largely owing to the inability to directly apply conventional optimization techniques. In this study, we present a novel approach based on artificial neural networks (ANNs) to simultaneously optimize multiple responses including both qualitative and quantitative quality characteristics. Two neural networks are constructed: one for determining the ideal parameter settings and the other for estimating the values of the multiple quality characteristics. In addition, a numerical example from an ion implantation process employed by a Taiwan IC fabrication manufacturer demonstrates the proposed approach's effectiveness. (C) 2001 Published by Elsevier Science B.V.
Optimization of multiple responses using principal component analysis and technique for order preference by similarity to ideal solution
(2005-12-01)
Tong, LI
;
Wang, CH
;
Chen, HC
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Optimizing multi-response problems has become an increasingly relevant issue when more than one correlated product quality characteristic must be assessed simultaneously in a complicated manufacturing process. This study proposes a novel optimization procedure for multiple responses based on Taguchi's parameter design. The signal-to-noise (SN) ratio is initially used to assess the performance of each response. Principal component analysis (PCA) is then conducted on the SN values to obtain a set of uncorrelated components. The optimization direction for each component is determined based on the corresponding variation mode chart. Finally, the relative closeness to the ideal solution resulting from the technique for order preference by similarity to ideal solution (TOPSIS) is determined as an overall performance index (OPI) for multiple responses. Engineers can easily employ the proposed procedure to obtain the optimal factor/level combination for multiple responses. A case study involving optimization of the chemical-mechanical polishing of copper (Cu-CMP) thin films from an integrated circuit manufacturer in Taiwan is also presented to demonstrate the effectiveness of the proposed procedure.
Optimizing multi-response problems in the Taguchi method by fuzzy multiple attribute decision making
(1997-01-01)
Tong, LI
;
Su, CT
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
One of the conventional approaches used in off-line quality control is the Taguchi method. However, most previous Taguchi method applications have only dealt with a single-response problem and the multi-response problem has received only limited attention. The theoretical analysis in this study reveals that Taguchi's quadratic loss function and the indifference curve in the TOPSIS (Technique for order preference by similarity to ideal solution) method have similar features, The Taguchi method deals with a one-dimensional problem and TOPSIS handles multi-dimensional problems. As a result, the relative closeness computed in TOPSIS can be used as a performance measurement index for optimizing multi-response problems in the Taguchi method. Next, an effective procedure is proposed by applying fuzzy set theory to multiple attribute decision making (MADM). The procedure can reduce the uncertainty for determining a weight of each response and it is a universal approach which can simultaneously deal with continuous and discrete data. Finally, the effectiveness of the proposed procedure is verified with an example of analysing a plasma enhanced chemical vapour deposition (PECVD) process experiment. (C) 1997 by John Wiley & Sons, Ltd.
Optimizing multi-response problems in the Taguchi method by fuzzy multiple attribute decision making
(1997-01-01)
Tong, LI
;
Su, CT
;
交大名義發表
;
工業工程與管理學系
;
National Chiao Tung University
One of the conventional approaches used in off-line quality control is the Taguchi method. However, most previous Taguchi method applications have only dealt with a single-response problem and the multi-response problem has received only limited attention. The theoretical analysis in this study reveals that Taguchi's quadratic loss function and the indifference curve in the TOPSIS (Technique for order preference by similarity to ideal solution) method have similar features, The Taguchi method deals with a one-dimensional problem and TOPSIS handles multi-dimensional problems. As a result, the relative closeness computed in TOPSIS can be used as a performance measurement index for optimizing multi-response problems in the Taguchi method. Next, an effective procedure is proposed by applying fuzzy set theory to multiple attribute decision making (MADM). The procedure can reduce the uncertainty for determining a weight of each response and it is a universal approach which can simultaneously deal with continuous and discrete data. Finally, the effectiveness of the proposed procedure is verified with an example of analysing a plasma enhanced chemical vapour deposition (PECVD) process experiment. (C) 1997 by John Wiley & Sons, Ltd.
Optimizing processes based on censored data obtained in repetitious experiments using grey prediction
(2006-02-01)
Tong, LI
;
Wang, CH
;
Hsiao, LC
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
The design of experiment (DOE) has been extensively adopted to increase the efficiency of designing new products and developing manufacturing processes in industry. However, some designed experiments cannot be completed for some uncontrollable reasons, such as cost and time restrictions or power damage during the experiment. Under such circumstances, incomplete data obtained in the experiment are referred to as censored data. Conventional approaches to analyzing censored data are computationally complex and frequently depend on assumptions of the normality of data. This study presents a procedure for analyzing the censored data obtained in repetitious experiments using the grey system theory. The proposed procedure does not make any statistical assumption and is less conceptual and computationally complex than current methods. Two experiments - one conventional experiment with type II censoring and one Taguchi experiment with type I censoring - are performed to demonstrate the effectiveness of the proposed procedure.
Performance assessment of processing and delivery times for very large scale integration using process capability indices
(2002)
Chen, KS
;
Chen, HT
;
Tong, LI
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Process quality and delivery time have received increasing attention in the highly competitive electronics industry. Many studies have proposed process capability indices (PCIs) to assess process effectiveness. However, methods to assess the performance in terms of processing and delivery times of products have seldom been discussed. The conventional PCIs can no longer assess the processing time (PT) and delivery time (DT) performance objectively or identify the relationship between PCIs and the non-conformance rate of PT or the conformance rate of DT. Lacking an effective performance index or an objective testing procedure to assess process/product performance will lead to inefficiency or a high manufacturing management overhead cost. Therefore, this study offers effective performance indices (i.e., PCIs) to assess the PT and DT performance for very large scale integration (VLSI). The uniformly minimum variance unbiased (UMVU) estimators of the proposed PCIs are derived under the assumption of a normal process distribution. The PCI estimators are then employed to construct a one-to-one relationship between the PCIs and the conformance rate of DT or non-conformance rate of PT, respectively. Finally, hypothesis testing procedures for the proposed PCIs are also developed. The testing procedure can be used to determine whether DT or PT can satisfy a customer's requirements.
Quality improvement for dynamic ordered categorical response using grey relational analysis
(2003)
Wang, CH
;
Tong, LI
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Product design is increasingly complicated and some quality characteristics cannot be directly measured. These quality characteristics are generally classified into several categories by visually examining the externals of products and forming an ordered system response. Most studies of quality improvement focus primarily on the quantitative form. Studies of ordered categorical response in a state system have been proposed over recent years. However, cases of an ordered categorical response in a dynamic system have rarely been seen. This study utilises grey relational, analysis, from grey system theory, to develop a procedure for improving the ordered categorical response in a dynamic system, based on Taguchi's parameter design. The proposed procedure can determine effectively the optimal factor level combination for an ordered categorical response in a dynamic system. A case study for improving the uniformity of plating in the lead frame process involved in semiconductor packaging is provided to demonstrate the effectiveness of the proposed procedure.