Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 238 for “"Process Data"”.
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Application of process data reconciliation in power plants
The operation of power plants and chemical processes requires process measurements for optimal operations. Process measurements are essential for plant performance optimization, process monitoring and process control. It is vital to have reliable and accurate process data to achieve process …
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Representation and extraction of trends from process data
Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1992.
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Probability based approaches to process data modeling and rectifictaion
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1996.
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Local Likelihood for Interval-censored and Aggregated Point Process Data
… the presence of interval-censored or aggregated data leads to a natural consideration of an EM-type strategy, or rather a local EM algorithm. In the thesis, we consider local EM to analyze the point process data that are either interval-censored or aggregated into regional counts. We specifically …
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A maturity model for process data analytics in biopharmaceutical manufacturing
… builds up pressure to make their manufacturing processes faster, more consistent, and more productive. Increased digitalization is expected to address these needs by means of new capabilities related to the analysis of the data collected in the manufacturing process (a.k.a. process data …
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Automatic learning from process data using neural network based methodologies
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1998.
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Some advances in Bayesian variable selection, cognitive diagnostic modeling, and process data analysis
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-08-01
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Development of a program to gather and process data from oil and gas fields
… from oil and gas fields and to analyze data in an efficient manner. The program outlines potential setups as well as practical analysis techniques. The result is a program to store field data and capability to analyze input in different formats.;The developed system uses accounting, …
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Diagnostic process monitoring with temporally uncertain models
… templates in which the temporal points where data patterns change are variable with respect to the actual process data. This thesis uses similar models to construct a monitoring system that is able to run in real time, based on a continuous, linearly segmented process data input stream. The …
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Critical process parameter determination during production start-up
Production start-up data is consistently utilized in a reactive manner during the initial stages of a product's lifecycle. However, if proactive information systems are created before full scale production starts, ramp-up cycles can be shortened considerably. This project attempts to develop a …
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PROCESS MINING FOR REENGINEERING CIRCULAR AND RESILIENT PRODUCTION PROCESSES
This thesis explores the integration of process mining techniques with deep learning models to enhance the understanding, analysis, and optimization of complex business processes. Process mining bridges the gap between model-driven and data-driven approaches through a set of techniques that extract …
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Predictive Analytics Applications for Oil and Gas Processing Facilities
… on the Industry 4.0 journey, the pillar of big data becomes increasingly important in an industry that generates massive amounts of data with low to no value extracted from it. Data are generated across all value chain sectors—upstream, midstream, and downstream—starting at reservoirs up to the …
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Bayesian Estimation of Material Properties in Case of Correlated and Insufficient Data
… to be reliable and suitable tools to process data, describing probability distributions and uncertainty bounds for investigated parameters in absence of explicit inverse analytical expressions. Though it is necessary to repeat experiments multiple times for good estimations, this might …
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Process Monitoring and Control of Advanced Manufacturing based on Physics-Assisted Machine Learning
… the development of technology, the manufacturing process is becoming more and more advanced. This appears as an advanced manufacturing process that uses innovative technology, including robotics, artificial intelligence, and autonomous systems. Additive manufacturing (AM), also known as 3D …
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ATR Process Geomatics: Process, Content, and Style
… portfolio papers explore a land-based geomatics data perspective, exploring its process, data practice, and process history-engagement style. The ATR process geomatics is an emerging topic that has moved to a digital post-counter mapping practice, with land title transfer factors outlined in the …
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Investigation of a multi-layer perceptron network to model and control a non-linear system.
… a neural network model of a non-linear process. The scheme is based on a Multi-Layer Perceptron neural net-work as a modelling tool for a real non-linear, dual tank, liquid level process. A neural network process model is developed and evaluated firstly in simulation studies and then …
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Modeling System Efficiency in Mixed-Model Assembly Lines
… These efforts leverage either vehicle or process data, but none incorporate both, as no combined data system exists. One can overcome this disconnect by generating an integrated model that links the production sequence with assembly jobs using vehicle model and feature relationships. What …
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Hybrid neural networks models for a membrane reactor
… model, which can provide simulated process data as needed, as well as its potential industrial importance. Also, two modeling schemes were developed, a fully 'black box' model (BANN), based on ANN technique only, and a simple hybrid model, combining ANN with mass balances (HANN1). …
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