Michael L. Miller

Impact of multi-product and -process manufacturing on run-to-run control

For the past few years, both academia and industry have increased research in run-to-run or supervisory level control of semiconductor processes. Run-to-run control has been cited as a necessary and integral part of many current and future leading edge processes. Run-to-run control has been applied or proposed for common and critical fab processes such as chemical mechanical polish (CMP) and lithography/etch line width control. Many traditional as well as advanced control techniques have been used in the formulation of run-to-run controllers (time series and statistical process control- based, state space methods, simple P/PI/PID algorithms, model- based predictive control, etc.). In addition, papers have been published that discuss some of the many issues involved in deploying a run-to-run controller. However, one important issue that affects deployment of run-to-run control has largely been ignored. In many state-of-the-art fabs, especially those that manufacture microprocessors and other logic chips, costly fab tools are required to run more than one process for throughput and flexibility reasons. Furthermore, todays fabs frequently produce more than one type of chip. Both of these factors, multi-processing and - products, sometimes lead to major difficulties in designing and deploying a run-to-run controller This paper focuses on the issues involved in multi-product and -process run-to-run control, as well as compare and contrast some strategies that could be used to design a run-to-run control system under these circumstances.

Monitoring of a RTA process using multi-PCA

Process faults usually lead to changes in the normal relationship among process variables. These changes can be detected by a principle component analysis (PCA) model based on the data from normal batches of operation. Therefore, monitoring process variables via a PCA model may lead to the earlier detection of process fault than traditional SPC method which depends on periodic information from test wafers.However, PCA is a linear method, and does not explain the relationship among process variables with time. Because the relationship among process variables for a wafer processing equipment is both nonlinear, applying PCA method directly to the monitoring of such processes may prove to be difficult. A multi-PCA modeling technique is proposed in our study of process in our study of process monitoring and fault detection for a semiconductor manufacturing tool. A series of local PCA models can be built with each local model only describing a local relationship among process variables at a particular time.During monitoring, if an observation from the kth sampling time of previous normal runs, this observation can be considered normal. A method is also proposed to eliminate redundant local PCA models. The proposed method has been implemented for the monitored of a commercial Rapid Thermal Anneal (RTA) tool. The RTA process is a typical single wafer process. For the same product, all wafers should be processed according to the same recipe. First, the data from normal lots were collected and verified by wafer electrical test data to be normal data. A multi-PCA model was built based on all data for these normal production lots. In the modeling, only 2 or 3 principal components were necessary for each local PCA model to explain 99 percent variance of each sub-matrix of data. This paper will discuss using Multi-PCA as a modeling method for detecting real-time process variations based on equipment signals, with abnormal process signals being indicated by a single parameter - Squared Prediction Error - from the PCA mode. Issues related to the use of this technique in a state-of-the-art semiconductor fab will also be discussed.

Integration of the APC framework with AMD's Fab25 factory system

This paper discusses the integration and development of advanced process control technologies with AMDs Fab25 factory systems using the Advance Process Control Framework. The Framework is an open software architecture that allows the integration of existing factory systems, such as the manufacturing execution systems, configurable equipment interfaces, recipe management systems, metrology tools, process tools, and add-on sensors, into a system which provides advanced process control specific functionality. The Advanced Process Control Framework project was formulated to enable effective integration of Advanced Process Control applications into a semiconductor facility to improve manufacturing productivity and product yields. The main communication link between the factory system and the Framework is the Configurable Equipment Interface. It interfaces through a specialized component in the framework, the Machine Interface, which converts the factory system communication protocol, ISIS, to the Framework protocol, CORBA. The Framework is a distributed architecture that uses CORBA as a communication protocol between specialized components. A generalized example of how the Framework is integrated into the semiconductor facility is provided, as well as a description of the overall architecture used for process control strategy development. The main development language, Tcl/Tk, provides for increased development and deployment over traditional coding methods.