A framework for generating operational characteristic curves for semiconductor manufacturing systems using flexible and reusable discrete event simulations

This thesis proposes a framework for generating operating curves for semiconductor manufacturing facilities using a modular flexible discrete event simulation (DES) model embedded in an application that automates the design of experiments for the simulations. Typically, operating curves are generated using analytical queueing models that are difficult to implement and hence, can only be used for benchmarking purposes. Alternatively, DES models are more capable of capturing the complexities of a semiconductor manufacturing facility such as re-entrancy, rework and non-identical toolsets. However, traditional craft-based simulations require much time and resources. The proposed methodology aims to reduce this time by automatically calculating the parameters for experimentation and generating the simulation model. It proposes a novel method to more appropriately allocate simulation effort by selecting design points more relevant to the operating curve. The methodology was initially applied to a single toolset model and tested as a pilot case study using actual factory data. Overall, the resulting operating curves matched that of the actual data. Subsequently, the methodology was applied to a full semiconductor manufacturing facility, using datasets from the Semiconductor Wafer Manufacturing Data Format Specification. The automated framework was shown to generate the curves rapidly and comparisons against a number of queueing model equivalents showed that the DES curves were more accurate. The implications of this work mean that on deployment of the application, semiconductor manufacturers can quickly obtain an accurate operating curve of their factory that could be used to aid in capacity planning and enable better decision-making regarding allocation of resources

Advanced Process Monitoring for Industry 4.0

This book reports recent advances on Process Monitoring (PM) to cope with the many challenges raised by the new production systems, sensors and “extreme data” conditions that emerged with Industry 4.0. Concepts such as digital-twins and deep learning are brought to the PM arena, pushing forward the capabilities of existing methodologies to handle more complex scenarios. The evolution of classical paradigms such as Latent Variable modeling, Six Sigma and FMEA are also covered. Applications span a wide range of domains such as microelectronics, semiconductors, chemicals, materials, agriculture, as well as the monitoring of rotating equipment, combustion systems and membrane separation processes

Etudes de bruit du fond dans le canal H→ZZ*→4l pour le Run 1 du LHC. Perspectives du mode bbH(→γγ) et études d'un système de détecteur pixel amélioré pour la mise à niveau de l'expérience ATLAS pour la phase HL-LHC

The discovery of a scalar boson, known as the Higgs boson, marked the first LHC data period (2010-2012). Using mainly di-photon and di-Z decays, with the latest leading to a four leptons final state, the mass of the boson was measured with a precision of <0.2%. Relevant couplings were estimated by combining several final states, while corresponding uncertainties would largely benefit from the increased statistics expected during the next LHC data periods (Run 2, Phase 2).The H→ZZ*→4l channel, in spite of its suppressed brunching ratio, benefits from a weak background, making it a prime choice for the investigation of the new boson’s properties. In this thesis, the analysis aimed to the observation of this mode with the ALTAS detector is presented, with a focus on the measurement and control of the reducible electron background.In the context of preparation for future high luminosity data periods, foreseen from 2025 onwards, two distinct studies are conducted:The first concerns the observability potential of the Higgs associated production mode in conjunction with two b-quarks. A multivariate analysis based on simulated data confirms a very weak expected signal in the H→di-photon channel.The second revolves around the conception and development of an inner silicon detector capable of operating in the hostile environment of high radiation and increased occupancy, expected during LHC Phase 2. Main studies were concentrated on improving radiation hardness, geometrical and detection efficiency. Through fabrication process simulation and SiMS measurements, doping profiles and electrical characteristics, expected for innovative technologies, are explored. Prototypes were designed and evaluated in test beams and irradiation experiments in order to asses their performances and that of associated read-out electronics.La première prise des données du LHC (2010-2012) a été marquée par la découverte du boson scalaire, dit boson de Higgs. Sa masse a été mesurée avec une précision de 0.2% en utilisant ses désintégrations en deux photons et celles en deux bosons Z donnant quatre leptons dans l’état final. Les couplages ont été estimés en combinant plusieurs états finaux, tandis que la précision sur leur mesure pourra bénéficier énormément de la grande statistique qui sera accumulée pendant les prochaines périodes de prise des données au LHC (Run 2, Phase 2).Le canal H→ZZ*→4 leptons, a un rapport d'embranchement réduit mais présente un faible bruit de fond, ce qui le rend attractif pour la détermination des propriétés du nouveau boson. Dans cette thèse, l’analyse conduite pour la mise en évidence de ce mode dans l’expérience ATLAS est détaillée, avec un poids particulier porté à la mesure et au contrôle du bruit de fond réductible en présence d’électrons.Dans le cadre de la préparation de futures prises de données à très haute luminosité, prévues à partir de 2025, deux études sont menées:La première concerne l’observabilité du mode de production du boson de Higgs en association avec des quarks b. Une analyse multivariée, basée sur des données simulées, confirme un très faible signal dans le canal H→2 photons.La seconde concerne la conception et le développement d’un détecteur interne en silicium, adapté à l’environnement hostile, de haute irradiation et de taux d’occupation élevée, attendues pendant la Phase 2 du LHC. Des études concernant l’optimisation de la géométrie, l’amélioration de l’efficacité ainsi que la résistance à l’irradiation ont été menées. A travers des mesures SiMS et des simulations des procédés de fabrication, les profiles de dopage et les caractéristiques électriques attendues pour des technologies innovantes sont explorés. Des prototypes ont été testés sous faisceau et soumis à des irradiations, afin d’évaluer les performances du détecteur et celles de son électronique associée

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

The Boston University Photonics Center annual report 2012-2013

This repository item contains an annual report that summarizes activities of the Boston University Photonics Center in the 2012-2013 academic year. The report provides quantitative and descriptive information regarding photonics programs in education, interdisciplinary research, business innovation, and technology development. The Boston University Photonics Center (BUPC) is an interdisciplinary hub for education, research, scholarship, innovation, and technology development associated with practical uses of light.This report summarizes activities of the Boston University Photonics Center during the period July 2012 through June 2013. These activities span the Center’s complementary missions in education, research, technology development, and commercialization. The Photonics Center continues to grow as an international leader in photonics research, while executing the Center’s strategic plan and serving as a university-wide resource for several affiliate Centers. For more information about the strategic plan, read the Photonics Center Strategic Plan section on page 10. In research, Photonics Center faculty published nearly 150 journal papers spanning the field of photonics. A number of awards for outstanding achievement in education and research were presented to Photonics Center faculty members, including a Peter Paul Professorship for Professor Xue Han, an NSF Career Award for Professor Ajay Joshi, and the 2012 Innovator of the Year Award from Boston University for Professor Theodore Moustakas. New external grant funding for the 2012- 2013 fiscal year totaled over $21.8M. For more information on our research activities, read the Research section on page 24. In technology development, the Photonics Center has turned a chapter, by completing the transition from a focus on Defense/ Security applications to a focus on the healthcare market sector. The commercial sector is expected to energize the technology development efforts for the foreseeable future, but the roots in defense/security are still important and the Center will continue to pursue new research grants in this area. For more information on our technology development program and on specific projects, read the Technology Development section on page 45. In education, 20 Photonics Center graduate students received Ph.D. diplomas. Photonics Center faculty taught 32 photonics courses. The Center supported a Research Experiences for Teachers (RET) site in Biophotonic Sensors and Systems for 10 middle school and high school teachers. The Photonics Center sponsored the Herbert J. Berman “Future of Light” Prize at the University’s Scholars Day. For more on our education programs, read the Education section on page 54. In commercialization, Boston University’s Business Innovation Center (BIC) currently hosts seven technology start-up companies. There is a healthy turnover in the Innovation Center space with a total of 19 companies residing at BIC over the past year. The mix of companies includes: life sciences, biotechnology, medical devices, photonics, and clean energy; and nine of the 19 companies originated from within BU. All the BIC tenants are engaged in the commercialization of new technologies of importance to society and all are active in the BU community in terms of offering internships, employment opportunities or research collaborations. For more information about Business Innovation Center activities, read the Business Innovation Center chapter in the Facilities and Equipment section on page 66

The Boston University Photonics Center annual report 2012-2013

This repository item contains an annual report that summarizes activities of the Boston University Photonics Center in the 2012-2013 academic year. The report provides quantitative and descriptive information regarding photonics programs in education, interdisciplinary research, business innovation, and technology development. The Boston University Photonics Center (BUPC) is an interdisciplinary hub for education, research, scholarship, innovation, and technology development associated with practical uses of light.This report summarizes activities of the Boston University Photonics Center during the period July 2012 through June 2013. These activities span the Center’s complementary missions in education, research, technology development, and commercialization. The Photonics Center continues to grow as an international leader in photonics research, while executing the Center’s strategic plan and serving as a university-wide resource for several affiliate Centers. For more information about the strategic plan, read the Photonics Center Strategic Plan section on page 10. In research, Photonics Center faculty published nearly 150 journal papers spanning the field of photonics. A number of awards for outstanding achievement in education and research were presented to Photonics Center faculty members, including a Peter Paul Professorship for Professor Xue Han, an NSF Career Award for Professor Ajay Joshi, and the 2012 Innovator of the Year Award from Boston University for Professor Theodore Moustakas. New external grant funding for the 2012- 2013 fiscal year totaled over $21.8M. For more information on our research activities, read the Research section on page 24. In technology development, the Photonics Center has turned a chapter, by completing the transition from a focus on Defense/ Security applications to a focus on the healthcare market sector. The commercial sector is expected to energize the technology development efforts for the foreseeable future, but the roots in defense/security are still important and the Center will continue to pursue new research grants in this area. For more information on our technology development program and on specific projects, read the Technology Development section on page 45. In education, 20 Photonics Center graduate students received Ph.D. diplomas. Photonics Center faculty taught 32 photonics courses. The Center supported a Research Experiences for Teachers (RET) site in Biophotonic Sensors and Systems for 10 middle school and high school teachers. The Photonics Center sponsored the Herbert J. Berman “Future of Light” Prize at the University’s Scholars Day. For more on our education programs, read the Education section on page 54. In commercialization, Boston University’s Business Innovation Center (BIC) currently hosts seven technology start-up companies. There is a healthy turnover in the Innovation Center space with a total of 19 companies residing at BIC over the past year. The mix of companies includes: life sciences, biotechnology, medical devices, photonics, and clean energy; and nine of the 19 companies originated from within BU. All the BIC tenants are engaged in the commercialization of new technologies of importance to society and all are active in the BU community in terms of offering internships, employment opportunities or research collaborations. For more information about Business Innovation Center activities, read the Business Innovation Center chapter in the Facilities and Equipment section on page 66

Improving process monitoring and modeling of batch-type plasma etching tools

Manufacturing equipments in semiconductor factories (fabs) provide abundant data and opportunities for data-driven process monitoring and modeling. In particular, virtual metrology (VM) is an active area of research. Traditional monitoring techniques using univariate statistical process control charts do not provide immediate feedback to quality excursions, hindering the implementation of fab-wide advanced process control initiatives. VM models or inferential sensors aim to bridge this gap by predicting of quality measurements instantaneously using tool fault detection and classification (FDC) sensor measurements. The existing research in the field of inferential sensor and VM has focused on comparing regressions algorithms to demonstrate their feasibility in various applications. However, two important areas, data pretreatment and post-deployment model maintenance, are usually neglected in these discussions. Since it is well known that the industrial data collected is of poor quality, and that the semiconductor processes undergo drifts and periodic disturbances, these two issues are the roadblocks in furthering the adoption of inferential sensors and VM models. In data pretreatment, batch data collected from FDC systems usually contain inconsistent trajectories of various durations. Most analysis techniques requires the data from all batches to be of same duration with similar trajectory patterns. These inconsistencies, if unresolved, will propagate into the developed model and cause challenges in interpreting the modeling results and degrade model performance. To address this issue, a Constrained selective Derivative Dynamic Time Warping (CsDTW) method was developed to perform automatic alignment of trajectories. CsDTW is designed to preserve the key features that characterizes each batch and can be solved efficiently in polynomial time. Variable selection after trajectory alignment is another topic that requires improvement. To this end, the proposed Moving Window Variable Importance in Projection (MW-VIP) method yields a more robust set of variables with demonstrably more long-term correlation with the predicted output. In model maintenance, model adaptation has been the standard solution for dealing with drifting processes. However, most case studies have already preprocessed the model update data offline. This is an implicit assumption that the adaptation data is free of faults and outliers, which is often not true for practical implementations. To this end, a moving window scheme using Total Projection to Latent Structure (T-PLS) decomposition screens incoming updates to separate the harmless process noise from the outliers that negatively affects the model. The integrated approach was demonstrated to be more robust. In addition, model adaptation is very inefficient when there are multiplicities in the process, multiplicities could occur due to process nonlinearity, switches in product grade, or different operating conditions. A growing structure multiple model system using local PLS and PCA models have been proposed to improve model performance around process conditions with multiplicity. The use of local PLS and PCA models allows the method to handle a much larger set of inputs and overcome several challenges in mixture model systems. In addition, fault detection sensitivities are also improved by using the multivariate monitoring statistics of these local PLS/PCA models. These proposed methods are tested on two plasma etch data sets provided by Texas Instruments. In addition, a proof of concept using virtual metrology in a controller performance assessment application was also tested.Chemical Engineerin

30th International Conference on Information Modelling and Knowledge Bases

Information modelling is becoming more and more important topic for researchers, designers, and users of information systems. The amount and complexity of information itself, the number of abstraction levels of information, and the size of databases and knowledge bases are continuously growing. Conceptual modelling is one of the sub-areas of information modelling. The aim of this conference is to bring together experts from different areas of computer science and other disciplines, who have a common interest in understanding and solving problems on information modelling and knowledge bases, as well as applying the results of research to practice. We also aim to recognize and study new areas on modelling and knowledge bases to which more attention should be paid. Therefore philosophy and logic, cognitive science, knowledge management, linguistics and management science are relevant areas, too. In the conference, there will be three categories of presentations, i.e. full papers, short papers and position papers