Doctor of Philosophy

dissertationIn order to ensure high production yield of semiconductor devices, it is desirable to characterize intermediate progress towards the final product by using metrology tools to acquire relevant measurements after each sequential processing step. The metrology data are commonly used in feedback and feed-forward loops of Run-to-Run (R2R) controllers to improve process capability and optimize recipes from lot-to-lot or batch-to-batch. In this dissertation, we focus on two related issues. First, we propose a novel non-threaded R2R controller that utilizes all available metrology measurements, even when the data were acquired during prior runs that differed in their contexts from the current fabrication thread. The developed controller is the first known implementation of a non-threaded R2R control strategy that was successfully deployed in the high-volume production semiconductor fab. Its introduction improved the process capability by 8% compared with the traditional threaded R2R control and significantly reduced out of control (OOC) events at one of the most critical steps in NAND memory manufacturing. The second contribution demonstrates the value of developing virtual metrology (VM) estimators using the insight gained from multiphysics models. Unlike the traditional statistical regression techniques, which lead to linear models that depend on a linear combination of the available measurements, we develop VM models, the structure of which and the functional interdependence between their input and output variables are determined from the insight provided by the multiphysics describing the operation of the processing step for which the VM system is being developed. We demonstrate this approach for three different processes, and describe the superior performance of the developed VM systems after their first-of-a-kind deployment in a high-volume semiconductor manufacturing environment

Control of semiconductor manufacturing: CMP & thickness variations

Master'sMASTER OF ENGINEERIN

Virtual metrology for semiconductor manufacturing applications

Per essere competitive nel mercato, le industrie di semiconduttori devono poter raggiungere elevati standard di produzione a un prezzo ragionevole. Per motivi legati tanto ai costi quanto ai tempi di esecuzione, una strategia di controllo della qualità che preveda la misurazione completa del prodotto non è attuabile; i test sono eettuati su un ristretto campione dei dati originali. Il traguardo del presente lavoro di Tesi è lo studio e l'implementazione, attraverso metodologie di modellistica tipo non lineare, di un algoritmo di metrologia virtuale (Virtual Metrology) d'ausilio al controllo di processo nella produzione di semiconduttori. Infatti, la conoscenza di una stima delle misure non realmente eseguite (misure virtuali) può rappresentare un primo passo verso la costruzione di sistemi di controllo di processo e controllo della qualità sempre più ranati ed ecienti. Da un punto di vista operativo, l'obiettivo è fornire la più accurata stima possibile delle dimensioni critiche a monte della fase di etching, a partire dai dati disponibili (includendo misurazioni da fasi di litograa e deposizione e dati di processo - ove disponibili). Le tecniche statistiche allo stato dell'arte analizzate in questo lavoro comprendono: - multilayer feedforward networks; Confronto e validazione degli algoritmi presi in esame sono stati possibili grazie ai data-set forniti da un'industria manifatturiera di semiconduttori. In conclusione, questo lavoro di Tesi rappresenta un primo passo verso la creazione di un sistema di controllo di processo e controllo della qualità evoluto e essibile, che abbia il ne ultimo di migliorare la qualità della produzione.ope

Model-based Design Development and Control of a Wind Resistant Multirotor UAV

Multirotor UAVs have in recent years become a trend among academics, engineers and hobbyists alike due to their mechanical simplicity and availability. Commercial uses range from surveillance to recreational flight with plenty of research being conducted in regards to design and control. With applications towards search and rescue missions in mind, the main objective of this thesis work is the development of a mechanical design and control algorithm aimed at maximizing wind resistance. To these ends, an advanced multirotor simulator, based on helicopter theory, has been developed to give an accurate description of the flight dynamics. Controllers are then designed and tuned to stabilize the attitude and position of the UAV followed by a discussion regarding disturbance attenuation. In order to study the impact of different design setups, the UAV model is constructed so that physical properties can be scaled. Parameter influence is then investigated for a specified wind test using a Design of Experiments methodology. These results are combined with a concept generation process and evaluated with a control engineering approach. It was concluded that the proposed final design should incorporate a compact three-armed airframe with six rotors configured coaxially

Virtual metrology for plasma etch processes.

Plasma processes can present dicult control challenges due to time-varying dynamics and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the use of mathematical models with accessible measurements from an operating process to estimate variables of interest. This thesis addresses the challenge of virtual metrology for plasma processes, with a particular focus on semiconductor plasma etch. Introductory material covering the essentials of plasma physics, plasma etching, plasma measurement techniques, and black-box modelling techniques is rst presented for readers not familiar with these subjects. A comprehensive literature review is then completed to detail the state of the art in modelling and VM research for plasma etch processes. To demonstrate the versatility of VM, a temperature monitoring system utilising a state-space model and Luenberger observer is designed for the variable specic impulse magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The temperature monitoring system uses optical emission spectroscopy (OES) measurements from the VASIMR engine plasma to correct temperature estimates in the presence of modelling error and inaccurate initial conditions. Temperature estimates within 2% of the real values are achieved using this scheme. An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate plasma etch rate for an industrial plasma etch process is presented. The VM models estimate etch rate using measurements from the processing tool and a plasma impedance monitor (PIM). A selection of modelling techniques are considered for VM modelling, and Gaussian process regression (GPR) is applied for the rst time for VM of plasma etch rate. Models with global and local scope are compared, and modelling schemes that attempt to cater for the etch process dynamics are proposed. GPR-based windowed models produce the most accurate estimates, achieving mean absolute percentage errors (MAPEs) of approximately 1:15%. The consistency of the results presented suggests that this level of accuracy represents the best accuracy achievable for the plasma etch system at the current frequency of metrology. Finally, a real-time VM and model predictive control (MPC) scheme for control of plasma electron density in an industrial etch chamber is designed and tested. The VM scheme uses PIM measurements to estimate electron density in real time. A predictive functional control (PFC) scheme is implemented to cater for a time delay in the VM system. The controller achieves time constants of less than one second, no overshoot, and excellent disturbance rejection properties. The PFC scheme is further expanded by adapting the internal model in the controller in real time in response to changes in the process operating point

Virtual metrology for plasma etch processes.

Plasma processes can present dicult control challenges due to time-varying dynamics and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the use of mathematical models with accessible measurements from an operating process to estimate variables of interest. This thesis addresses the challenge of virtual metrology for plasma processes, with a particular focus on semiconductor plasma etch. Introductory material covering the essentials of plasma physics, plasma etching, plasma measurement techniques, and black-box modelling techniques is rst presented for readers not familiar with these subjects. A comprehensive literature review is then completed to detail the state of the art in modelling and VM research for plasma etch processes. To demonstrate the versatility of VM, a temperature monitoring system utilising a state-space model and Luenberger observer is designed for the variable specic impulse magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The temperature monitoring system uses optical emission spectroscopy (OES) measurements from the VASIMR engine plasma to correct temperature estimates in the presence of modelling error and inaccurate initial conditions. Temperature estimates within 2% of the real values are achieved using this scheme. An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate plasma etch rate for an industrial plasma etch process is presented. The VM models estimate etch rate using measurements from the processing tool and a plasma impedance monitor (PIM). A selection of modelling techniques are considered for VM modelling, and Gaussian process regression (GPR) is applied for the rst time for VM of plasma etch rate. Models with global and local scope are compared, and modelling schemes that attempt to cater for the etch process dynamics are proposed. GPR-based windowed models produce the most accurate estimates, achieving mean absolute percentage errors (MAPEs) of approximately 1:15%. The consistency of the results presented suggests that this level of accuracy represents the best accuracy achievable for the plasma etch system at the current frequency of metrology. Finally, a real-time VM and model predictive control (MPC) scheme for control of plasma electron density in an industrial etch chamber is designed and tested. The VM scheme uses PIM measurements to estimate electron density in real time. A predictive functional control (PFC) scheme is implemented to cater for a time delay in the VM system. The controller achieves time constants of less than one second, no overshoot, and excellent disturbance rejection properties. The PFC scheme is further expanded by adapting the internal model in the controller in real time in response to changes in the process operating point

Quantifying biometrology operator data analysis subjectivity within flow cytometry using measurement uncertainty principles

A recent evaluation of medical error has shown it to be the third leading cause of death in the US, following heart disease and cancer. Better reporting and decision making could tackle this, but ultimately more accurate and precise measurement, with correct interpretation could make a significant difference to this unnecessary statistic. Clinical pathology measurement platforms are complex, requiring significant standardisation efforts to reduce false positives/negatives and the impacts these have on patient safety. Cell and Gene Therapy (CGT) manufacturing processes depend upon these platforms for measurement, with Flow Cytometry (FC) used for in-process and release metrics. However, the highly subjective nature of FC data analysis requires investigation to monitor impact on manufacturing and clinical decision making.FC standardisation efforts have reduced variation from sample preparation and setup, however, no efforts have purely focused on the final post-analytical stage, to quantify the effect of subjective analysis of data files. This research has isolated this section of FC analysis, providing better measurement precision to build up a realistic uncertainty budget for FC measurements. Through a series of participant analysis studies that build in complexity, it has been shown that as FC data becomes more complex, the uncertainty contributions from inter-operator data analysis increase from 8 % to 34 %. This increase could mean the difference between a CGT treatment being provided at the right time, being discarded when it was suitable for administration, or an unsuitable treatment administered to the patient at an unsuitable time, having costly implications for all.This variation does not correlate with operator experience or use frequency of the instrument, but is influenced by data visualisation effects, requiring further investigation at a later date to reduce this impact. Image parameters for other CGT measurement platforms are also impacted by subjective data analysis, requiring harmonisation to ensure the subjectivity is quantifiable, standardised and reduces manufacturing and hence medical error impacts to the patient and therapeutic product.</div

Control algorithms for aerobraking in the Martian atmosphere

The Analytic Predictor Corrector (APC) and Energy Controller (EC) atmospheric guidance concepts were adapted to control an interplanetary vehicle aerobraking in the Martian atmosphere. Changes are made to the APC to improve its robustness to density variations. These changes include adaptation of a new exit phase algorithm, an adaptive transition velocity to initiate the exit phase, refinement of the reference dynamic pressure calculation and two improved density estimation techniques. The modified controller with the hybrid density estimation technique is called the Mars Hybrid Predictor Corrector (MHPC), while the modified controller with a polynomial density estimator is called the Mars Predictor Corrector (MPC). A Lyapunov Steepest Descent Controller (LSDC) is adapted to control the vehicle. The LSDC lacked robustness, so a Lyapunov tracking exit phase algorithm is developed to guide the vehicle along a reference trajectory. This algorithm, when using the hybrid density estimation technique to define the reference path, is called the Lyapunov Hybrid Tracking Controller (LHTC). With the polynomial density estimator used to define the reference trajectory, the algorithm is called the Lyapunov Tracking Controller (LTC). These four new controllers are tested using a six degree of freedom computer simulation to evaluate their robustness. The MHPC, MPC, LHTC, and LTC show dramatic improvements in robustness over the APC and EC