IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING, VOL. 23, NO. 2, MAY 2010
149
Introduction to the Special Section on Advanced Process Control
A
DVANCED process control (APC), which includes run-to-run (R2R) control and Fault Detection and Classification (FDC), though less than 20 years old, is a required component in all fabrications today that are instrumental in achieving targets of improved productivity and reduced waste. APC discussion is receiving increased mention in the International Technology Roadmap for Semiconductors (ITRS) as a potential solution to “ prevent process excursions, improve yield, reduce non-product runs, reduce cycle time due to rework, and reduce equipment calibration and maintenance.” APC will play an even larger role in the next-generation factory and 450-mm applications, but will also serve an increasingly important role in 200-mm and 300-mm fabs to reduce variability and waste, thereby increasing productivity and product quality. This Special Issue on APC is the second publication collection of its type in the IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING. As with the first publication, this publication provides information on current and future efforts in APC research and development.
Many of the ideas presented in papers in this special section were first introduced in presentations at recent AEC/APC Symposiums which are held three times a year in Europe, the United States, and Asia, respectively; these symposiums have been attracting leaders in the APC research for over 15 years, and, in recent years, the IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING, working together with select symposium authors, have come together to provide a more detailed description of key ideas in an archival form that can serve as a research foundation for many years to come. In the first publication collection, which was published as a special section in the November 2007 issue of IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING, there was a focus on APC standards, utilizing prediction in APC in the form of virtual metrology, describing new and innovative methods for improved fault detection, applications of run-to-run (R2R) control, extending capabilities of R2R control in the areas of performance evaluation of controllers, linking control with scheduling/dispatch, and improving methods for data sampling associated with control. The papers selected for the current special section reflect the continued maturation of APC research and its movement into new application and technology areas. Specifically, there is a focus in this special section on methods for improving R2R control in areas such as high product mix environments, gain adaptation, sampling approaches, optimization solvers, and real-time extensions; methods for improving FDC in the areas Digital Object Identifier 10.1109/TSM.2010.2046115
of model size reduction; and extending APC into new areas such as back-end operations and yield optimization and control. In the area of R2R control science improvements, five papers are presented that all address different aspects of R2R control science. In “Model Regularization for High-Mix Control,” Patel looks at the multi-context R2R control problem and presents a regularization scheme that addresses the problem of lack of observability in these systems, a problem that can result in sporadic excursions in practice due to the phenomena of estimation error drift. In “Properties of EWMA Controllers with Gain Adaptation,” Wang explores the stability and sensitivity of EWMA controllers, the most commonly used R2R controller approach, when the gain of these controllers is allowed to be updated run-to-run. In “Compensating for the Initialization and Sampling of EWMA Run-to-Run Controlled Processes,” Good et al. address the problem of EWMA controller optimization under infrequent and irregular metrology sampling by presenting an algorithm that provides the minimum mean-square-error forecast of an integrated moving average process for irregularly sampled processes. In “Optimization Solvers in Run-to-Run Control,” Hanish looks at the problem of semiconductor processes that require an optimization process (e.g., because they have multiple settings or multiple targets) by providing an explanation of when optimizers are needed and examining how the structure of the process model can be used to speed up the optimization process and ensure that the global optimum is found. Finally, in “Addressing Dynamic Changes in High Volume Plasma Etch Manufacturing by using Real-time Multivariate Process Control,” Parkinson et al. present multivariate plasma etch modeling and control methodologies based on 65-nm and 45-nm poly gate production data utilizing wafer-to-wafer tool-level APC and integrated scatterometry. In the area of FDC science improvement, two papers are presented that provide two different approaches to model size reduction. In “Large-Scale Semiconductor Process Monitoring Using a Fast Pattern Recognition Based Method,” He and Wang address two persistent problems in FDC by utilizing a principal component analysis method to reduce dimensionality of the problem and a k-nearest neighbor technique to address both non-linearity in processes and multi-mode trajectories due to product mix. In “Introducing a Unified PCA Algorithm for Model Size Reduction,” Good et al. introduce an algorithm that greatly reduces the overall size of FDC principle component analysis problems by breaking the analysis of a large number of variables into multiple analyses of smaller uncorrelated blocks of variables. In the area of extending APC into new areas, two papers are presented illustrating the extension of both the technology and applicability space of APC. In “Scheduling Back-End Operations in Semiconductor Manufacturing,” Deng et al. address a topic that reflects both the expanded scope and
0894-6507/$26.00 © 2010 IEEE
150
IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING, VOL. 23, NO. 2, MAY 2010
expanded application domain of APC, namely scheduling in back-end processing. Specifically, the authors propose a new model and solution methodology aimed at maximizing the weighted throughput of lots undergoing assembly and test, while ensuring that critical lots are given priority. Finally, in “Yield Management Enhanced Advanced Process Control System (YMeAPC)—Part I: Description and Case Study of Feedback for Optimized Multiprocess Control,” Moyne and Schulze describe a solution for extending APC into the yield optimization space by utilizing APC to enable yield prediction and then using the yield prediction results for optimization of multiprocess R2R control to yield improvement targets. This special section aims to provide the reader with a picture of the current research and future vision of APC in semiconductor manufacturing. Readers are encouraged to explore these topics further by reading through the rich body of research found in the AEC/APC symposia. In that light, the editors would like to acknowledge the guidance of Brad Van Eck, who has served as chair of the AEC/APC symposia in the United States for over 12 years. Looking at the research and development body of work in APC as well as the strong body of APC researchers in
both academia and industry, it is clear that APC research will continue for many years to come and a need will continue for capturing APC ideas into an archival form. With the support and cooperation of the IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING editorial team, the guest editors look forward to continuing to work with the APC research community to guide the publication of high quality APC papers in IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING for many years to come.
JAMES MOYNE, Guest Editor Applied Materials Inc. Canton, MI 48187 USA
[email protected]
NITAL S. PATEL, Guest Editor Intel Corporation Chandler, AZ 85226 USA
[email protected]
James Moyne (M’90) received the B.S.E.E., the B.S.E. in mathematics, the M.S.E.E., and Ph.D. degrees from the University of Michigan, Ann Arbor. He is a Standards and Technology Specialist for the Applied Global Services Group, Applied Materials, Canton, MI, and is currently an Associate Research Scientist with the Department of Mechanical Engineering, University of Michigan. He was President and Cofounder of MiTeX Solutions Inc., established in 1995 to provide the first third-party integrated run-to-run control solutions for semiconductor and display manufacturing; he holds patents in the areas of software control and prediction technology and is coauthor of Run-to-Run Control in Semiconductor Manufacturing. He is also coauthor of a number of semiconductor standards in the areas of process control (E133 and E126), sensor bus (E54), and communications (E30 elements) and currently cochairs process control systems and data quality standards efforts.
Nital S. Patel (S’91–M’96–SM’01) received the B.Tech. degree from the Indian Institute of Technology, Kanpur, India, and the M.S. and Ph.D. degrees from the University of Maryland, College Park, all in electrical engineering. He is currently with the Assembly and Test Technology Development Group, Intel Corporation, Chandler, AZ, where he is the Process Control Systems Program Manager. Previously, he was a Senior Member of Technical Staff focusing on process control at Texas Instruments Inc. He holds ten patents in the area of semiconductor process control. Dr. Patel serves on the Editorial Board of the IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING.
