James Moyne

Using deadbands to reduce communication in networked control systems

The most effective way to improve networked control systems (NCSs) performance is to reduce network traffic. By adapting a system to a network configuration, the communication medium is more efficiently used and time-delays are minimized. Adjustable deadbands are explored as a solution to reduce network traffic in NCSs. The stability of deadband control is derived and then verified via simulation. A method to determine the size of the deadbands is presented that relies on a performance metric that takes into account system response as well as network traffic. The effectiveness of deadband control with different controllers is studied as well as the effect of disturbances and plant uncertainty.

Run-to-run control in semiconductor manufacturing

Introduction What is Run-top-Run Control? Target Audience Purpose of this Book Outline Background Current State-of-the-Art in Semiconductor Manufacturing Process Control History of the Development of Run-to-Run Control Current State o-of-the-Art in Run-to-Run Control Development and Deployment Simple Example: Run-to-Run Control and Comparison to Statistical Process Control Identifying Target Applications for Run-to-Run Control Class of Applications that can Utilize Run-t0-Run Control General Run-to-Run Control Development and Deployment Process Issues in Deploying Run-to-Run Control Developing a Run-to-Run Solution: Run-to-Run Algorithms Introduction Linear Approximation Algorithms Higher Order Approximation Algorithms Neural Network Algorithms Other Approaches Developing a Run-to-Run Solution: Practical Extensions to Algorithms Developing and Deploying Run-to-Run Solutions: Integrating Control Introduction The Generic Cell Controller Other Approaches Integrating into Factory-Wide Manufacturing System Run-to-Run Solution Development, Deployment, and Customization Methodology Introduction Process Identification Choosing a Run-to-Run Control Solution Customizing the Run-to-Run Control Solution to the Process Issues Run-to-Run Control System Deployment Case Studies Chemical-Mechanical Planarization Vapor Phase Epitaxy Advanced Topics Feasibility Analysis of Run-to-Run Control Solutions Stability Analysis of Run-to-Run Control Solutions Combining Process Run-to-Run Control with Inter-Process Control Conclusions Summary of Run-to-Run Development and Deployment Process Deploying Run-to-Run Control in a Timely and Cost Effective Manner Overcoming Barriers to Deployment Future Research and Development Issues References

Modelling and optimal controller design of networked control systems with multiple delays

In this paper we discuss the modelling and control of networked control systems (NCS) where sensors, actuators and controllers are distributed and interconnected by a common communication network. Multiple distributed communication delays as well as multiple inputs and multiple outputs (MIMO) are considered in the modelling algorithm. In addition, the asynchronous sampling mechanisms of distributed sensors are characterized to obtain the actual time delays between sensors and the controller. Due to the characteristics of a network architecture, piecewise constant plant inputs are assumed and discrete-time models of plant and controller dynamics are adopted to analyse the stability and performance of a closed-loop NCS. The analysis result is used to verify the stability and performance of an NCS without considering the impact of multiple time delays in the controller design. In addition, the proposed NCS model is used as a foundation for optimal controller design. The proposed control algorithm utilizes the information of delayed signals and improves the control performance of a control system encountering distributed communication delays. Several simulation studies are provided to verify the control performance of the proposed controller design.

Run by run control of chemical-mechanical polishing

A prototype hardware/software system has been developed and applied to the control of single wafer chemical-mechanical polishing (CMP) processes. The control methodology consists of experimental design to build response surface and linearized control models of the process, and the use of feedback control to change recipe parameters (machine settings) on a lot by lot basis. Acceptable regression models for a single wafer polishing tool and process were constructed for average removal rate and nonuniformity which are calculated based on film thickness measurement at nine points on 8-in blanket oxide wafers. For control, an exponentially weighted moving average model adaptation strategy was used, coupled to multivariate recipe generation incorporating user weights on the inputs and outputs, bounds on the input ranges, and discrete quantization in the machine settings. We found that this strategy successfully compensated for substantial drift in the uncontrolled tools removal rate. It was also found that the equipment model generated during the experimental design was surprisingly robust; the same model was effective across more than one CMP tool, and over several months. We believe that the same methodology is applicable to patterned oxide wafers; work is in progress to demonstrate patterned wafer control, to improve the control, communication, and diagnosis components of the system, and to integrate real-time information into the run by run control of the process.

An Approach for Factory-Wide Control Utilizing Virtual Metrology

In the semiconductor manufacturing industry, market demands and technology trends drive manufacturers towards increases in wafer size and decreases in device size. Application of factory-wide advanced process control (APC) techniques down to the wafer-to-wafer (W2W) level control capability is becoming the only choice to cope with the demanding situation. However, one of the main limitations in undertaking W2W control is the nonavailability of timely metrology data at the wafer level. Recently virtual metrology (VM) techniques have been proposed to provide timely wafer level metrology data; they have the potential to be used in realizing W2W control. In this paper, the VM approach to W2W control on factory level is described. VM for an individual process is realized by utilizing the preprocess metrology and the process data from the underlying tools that is generally collected in real time for fault detection purposes. The VM implementation for factory-wide run-to-run control brings unique opportunities and issues to the forefront such as dealing with expected lower quality of VM data, coordination between VM modules of cascading processes for better prediction quality, flexibility of the factory-wide controller to accommodate lower quality VM data, dynamic adjustments to the target values of individual processes by the factory-wide controller when using VM data, and dealing with metrology delays at the factory level. Near and long-term solutions are presented to address these issues in order to allow VM to be used today and become an integral part of the factory-wide APC solution for W2W control.

Analysis and modeling of networked control systems: MIMO case with multiple time delays

This paper discusses the modeling and analysis of networked control systems (NCS) where sensors, actuators, and controllers are distributed and interconnected by a common communication medium. Therefore, multiple distributed communication delays as well as multiple inputs and multiple outputs are considered in the modeling algorithm. In addition, the asynchronous sampling mechanisms of distributed sensors axe characterized to obtain the actual time delays between sensors and the controller. Due to the characteristics of a network architecture, piecewise constant plant inputs are assumed and discrete-time models of plant and controller dynamics are adopted to analyze the stability and performance of a closed-loop NCS. The analysis result is used to verify the stability and performance of an NCS if the controller is designed without considering the impact of multiple time delays. Also, the NCS model provided can be used as a foundation for further controller design to compensate for the distributed communication delays.

Control of semiconductor manufacturing equipment: real-time feedback control of a reactive ion etcher

This paper describes the development of real-time control technology for the improvement of manufacturing characteristics of reactive ion etchers. A general control strategy is presented. The principal ideas are to sense key plasma parameters, develop a dynamic input-output model for the subsystem connecting the equipment inputs to the key plasma variables, and design and implement a multivariable control system to control these variables. Experimental results show that this approach to closed-loop control leads to a much more stable etch rate in the presence of a variety of disturbances as compared to current industrial practice. >

An extended database design methodology for uncertain data management

Abstract Many real world systems require the support of database management systems (DBMS) that can handle vague or imprecise data. Fuzzy theory has been shown to be particularly suitable for this purpose. Indeed there have been several proposals for extending the relational data model in order to represent and query fuzzy data. However, little work has been done in modeling uncertainty at the conceptual schema level or for mapping such a schema to a relational DBMS. To fill this gap, we propose fuzzy entity-relationship methodology (FERM), which is a comprehensive methodology for design and development of fuzzy relational databases. FERM includes an extended fuzzy entity-relationship model to capture imprecision at the schema level as well as generic rules for mapping this schema to relational databases. In this paper, we also show the application of FERM to build a prototype of a fuzzy database for a discrete control system for a semiconductor manufacturing process.

Optimal controller design and evaluation for a class of networked control systems with distributed constant delays

In this paper we discuss the framework for optimal controller design of networked control systems (NCS) where sensors, actuators, and controllers are distributed and interconnected by a common communication network. Multiple distributed communication delays as well as multiple inputs and multiple outputs are considered in the discrete-time modeling algorithm. The proposed NCS model is used as a foundation for optimal controller design to compensate for the multiple time delays. The proposed control algorithm utilizes the information of delayed signals and improves the control performance of a control system with distributed communication delays. Several simulation studies are provided to evaluate the control performance of the proposed controller design.

Adaptive extensions to a multibranch run‐to‐run controller for plasma etching

Fuzzy logic and database learning mechanisms have been incorporated into a generic plasma etching run‐to‐run controller, resulting in a very dynamic, adaptable, and robust system. The system features an Applied 8300 reactive ion etcher controlled by a Techware II equipment controller. A TCP/IP connection links this equipment controller to the run‐to‐run controller residing on a SUN. The run‐to‐run control environment is generic in that the basic control framework and controller development results are applicable to very large scale integrated manufacturing in general. The controller is multibranch as it utilizes multiple algorithms in complementary fashion to achieve process optimization and control. The current implementation utilizes three branches: (1) a linear approximation control algorithm, (2) an optimization algorithm that utilizes (real‐time) data collected in situ to determine optimal run‐to‐run process parameter settings, and (3) a statistical optimization algorithm that utilizes run‐to‐run dat...