Ruey-Shan Guo

Age-based double EWMA controller and its application to CMP processes

In the originally proposed run-by-run control scheme, the EWMA statistic is used as an estimate of the process deviation from its target. However, the controller based on the EWMA statistic is not sufficient for controlling a wearing out process. The PCC controller has been thus proposed to enhance the run-by-run controller capability. In this paper, we first reexamine the fundamentals of the PCC formulations and propose an adjustment that is advantageous in controlling processes subject to both random shifts and drifts. The adjusted PCC controller is then further refined to take into account the process age. This age-based double EWMA scheme is then applied to the CMP process, which is known in the semiconductor industry to be rather unstable.

Process control system for VLSI fabrication

A modular framework for the implementation of process control in VLSI fabrication is described. The system integrates existing approaches to process control with new methodologies in order to achieve online optimization and control of unit processes with consideration of preceding and following process steps. The process control system is based on three core modules. The flexible recipe generator determines an initial operating point in response to a new product design. The run-by-run controller tunes the recipe between runs based on feedback from postprocess and in situ measurements. The real-time controller further modifies the equipment settings during a process step based on in situ measurements. The algorithmic bases of these modules are described. The flexible recipe generator was used to optimize the LPCVD (low-pressure chemical vapor deposition) of polysilicon. The run-by-run controller was used to locally optimize and control a simulation of the LPCVD of polysilicon. >

Modeling, optimization and control of spatial uniformity in manufacturing processes

Spatial uniformity, or the uniformity of product output characteristics at different locations in a batch of product is modeled, optimized, and controlled using a methodology called multiple response surfaces, which may be used to characterize the results of an experimental design. Multiple, low-order polynomial models are used to model the output characteristics at each of several sites within a batch of product. The uniformity model is then obtained by manipulating these multiple models. The approach is compared to the traditional method of fitting a single high-order polynomial to the calculated uniformity. Experimental results confirm that similar or improved modeling accuracy is obtained with fewer data points using the new method due to the use of low-order models. Characteristics of the approach are examined both analytically and in application to plasma etching, silicon epitaxy, tungsten chemical vapor deposition (CVD) and the simulation of polysilicon low-pressure CVD (LPCVD). >

Decision tree based control chart pattern recognition

This paper presents a new approach to classify six anomaly types of control chart patterns (CCP), of systematic pattern, cyclic pattern, upward shift, downward shift, upward trend, and downward trend. Current CCP recognition methods use either unprocessed raw data or complex transformed features (via principal component analysis or discrete wavelet transform) as the input representation for the classifier. The objective of using selected features is not only for dimension reduction of input representation, but also implies the process of data compression. In contrast, using raw data is often computationally inefficient while using transformed features is very tedious in most cases. Therefore, owing to its computational advantage, using appropriate features of CCP to achieve good classification accuracy becomes more promising in real process implementation. In this study, using three features of CCP shows quite a competitive performance in terms of classification accuracy and computational loading. More importantly, the proposed method presented here has potential to be generalized to medical, financial, and other application of temporal data.

Improved customer satisfaction with a hybrid dispatching rule in semiconductor back-end factories

On-time delivery is a vital factor for customer satisfaction in the competitive semiconductor manufacturing industry, and to optimize on-time delivery manufacturers must continuously improve their management of work-in-progress (WIP). However, in undertaking to optimize WIP, managers are also concerned with short cycle times, high throughput, and high utilization. In an attempt to find the most satisfactory solution to these potentially conflicting requirements with regard to WIP, the present study employs fuzzy analytic hierarchy process (AHP) to determine an appropriate set of acceptable WIP deviation levels (AWDLs). These AWDLs are then used in a proposed hybrid dispatching rule to determine the operational priorities of jobs. A simulation model using real-world data is then constructed to examine the proposed mechanism for improving customer satisfaction. The findings of the study confirm that the proposed mechanism is capable of simultaneous consideration of various goals and the achievement of enhanced performances with respect to due-date delivery from semiconductor back-end processes.

A cost-effective methodology for a run-by-run EWMA controller

In this paper, we present a cost-effective methodology for a run-by-run EWMA controller. This controller is an integrated approach that combines the advantages of statistical process control and feedback control. It adjusts the equipment settings only when the control chart detects an abnormal trend. Using simulations, we take into consideration the control sensitivity, robustness, and adjustment number required to determine an optimal weight for a minimum cost. As the simulation results demonstrate, the cost-effective run-by-run controller is able to keep drifting process outputs close to the target with only few runs of adjustment.

SHEWMA: an end-of-line SPC scheme using wafer acceptance test data

In this paper, an end-of-line quality control scheme based on wafer acceptance test (WAT) data is presented. Due to the multiple-stream and sequence-disorder effects typically present in the WAT data, an abnormal process shift caused by one machine at an in-line step may become vague for detection using end-of-line WAT data. A methodology for generating robust design parameters for the simultaneous application of Shewhart and EWMA control charts to WAT data is proposed. This SHEWMA scheme is implemented in a foundry environment and its detection and diagnosis-enhancing capabilities are validated using both numerical derivations and fab data. Results show that the SHEWMA scheme is superior to the current practices in detection speed. Its use is complementary to the existing in-line SPC for process integration.

A real-time equipment monitoring and fault detection system

In semiconductor fabrication processes, real-time equipment monitoring and fault detection become critical as most problems reveal themselves first on the equipment performance and much later on the wafer quality. The sooner we can detect the problem, the lower the production loss. The goal of this paper is to present an integrated equipment monitoring approach for a PECVD tool. The approach will include: (1) simultaneous monitoring scheme: a dartboard display of real-time data that provides an easy reading of the equipments overall status, (2) system health index: an index that evaluates the equipments overall health, and (3) analysis functions that include various charting functions, real-time SPC, run-to-run SPC, and other advanced SPC functions. The system has been implemented in TSMC FAB IV for testing. The preliminary results show that the proposed system is an effective tool for real-time monitoring and fault detection.

Optimal supply chain configurations in semiconductor manufacturing

As a semiconductor supply chain becomes widespread and the competition pressure is very fierce, the detrimental effects of increasing varieties and variations are magnified in the supply chain. But many important issues, such as different service priorities, adaptability, controllability and scalability of performance metrics, have not been addressed in the literature. Conventional modelling techniques of supply chain operations are no longer effective for supply chain configuration. Therefore, a proposed empirical model was first built to catch up the relationship between supply-chain configuration and metrics under the influence of the variability sources. Next, an optimal supply chain configuration model is formulated as a polynomial goal programming model to accommodate different goal objectives. Finally, an efficient solution methodology is further developed to find out the optimal supply chain configuration. Our results show that our proposed approach can easily be adapted to the practices in semiconductor supply chain, and the solution methodology developed in this paper is truly promising.

Run-to-run control schemes for CMP process subject to deterministic drifts

During IC fabrication, the chemical-mechanical polishing (CMP) process usually suffers from a drift in the run-to-run removal rate due to the wear of the polishing pad. In this paper, two run-to-run control schemes, the predictor corrector control (PCC) and adjusted exponentially weighted moving average (d-EWMA) schemes, for processes under deterministic drifts are presented. The control performance of both schemes is analytically derived and the determination of the optimal control parameters is provided. Validation results using the field CMP data demonstrate the control effectiveness of both control schemes.