Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
Browse
Search Results
- Virtual architecture of the automation pyramid based on the digital twin(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022-05-30) Martinez Galicia, Edwin Mauricio; PONCE CRUZ, PEDRO; 31857; Ponce Cruz, Pedro; emipsanchez; López Caudana, Édgar Omar; Soriano Avendaño, Luis Arturo; Escuela de Ingeniería y Ciencias; Campus Ciudad de México; Molina Gutiérrez, ArturoIndustry 4.0 has been empowered by new emerging technologies to improve the competitiveness in companies. One of these technologies is the digital twin (DT) which is an advanced virtual model that enables to predict, detect and classify normal and abnormal operating conditions in a factory or a particular production process to improve the features of a physical system. On the other hand, the manufacturing processes generally follow standards to segment and distribute their processes, information, and implementation areas. Among the most widely recognized standards in the manufacturing industry is the ISA-95 standard that incorporates the business functions and control systems performed in a company with the objective to enhance the implementation of interfaces between business and control systems. Some architectures, as the Automation Pyramid (AP), hierarchically place the elements that take part in a manufacturing process, from the basic elements such as sensors and actuators, to the decision-making systems, whose functions and shared information are defined in the ISA-95 standard. In industry, one of the main functions of decision-making systems, such as the Manufacturing Execution System (MES), is to provide critical data in real-time at the operational level to increase productivity and process capability of the manufacturing process. However, these systems usually do not have capabilities to offer a prompt/autonomous/learning-based response to face unpredicted changes in the course of operating resources. Therefore, when a fault condition occurs, not only quick responses are required but also predictive information to prevent future failure scenarios. Thus, this work proposes to provide responsiveness to decision-making levels in the face of unforeseen scenarios, through the incorporation of intelligent algorithms. The main objectives of this thesis are presented below: To propose a complete Virtual Architecture of the Automation Pyramid based on the Digital Twin: This enables the simulation of scenarios with elements from the shop-floor to the management levels, considering the advantages that the DT provides. To align the proposal with international standards: The model is driven by the ISA-95 standard incorporating the functions and information flow defined in it for decision-making levels. %Thus, the decision-making process is into an automation dynamic loop. To provide learning capabilities to the decision-making systems through artificial neural networks, incorporated in a model based on the DT concept: Since neural networks are able to learn and generalize knowledge, they can learn specific conditions for helping the decision-making process. Evaluate a manufacturing system for educational purposes through the proposed model: The parts of the virtual model of the AP will be identified in a manufacturing cell system used for education at Tec de Monterrey. Its components will be evaluated within the framework of the proposed architecture and the elements to complete the virtual model of the AP will be identified. As a result, this work proposes the complete virtual model of the Automation Pyramid based on the concept of the Digital Twin, where it is proposed to add autonomy capabilities to the decision-making levels through neural networks. The proposed model is aligned with the international standard ISA-95 as an alternative to be applied directly to a process or factory that can be based on the standard.
- Deep learning for clothing classification, case study:thermal comfort(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2021-11-23) Medina Rosales, Adán; Ponce Cruz, Pedro; puemcuervo; López Caudana, Edgar Omar; Rojas Hernández, Mario; Soriano Avendaño, Luis Arturo; School of Engineering and Sciences; Campus Ciudad de México; Molina Gutiérrez, ArturoImage classification algorithm has being in quick development over the last 10 years with a new algorithm appearing every year, this new algorithms aim to be faster and more accurate than its predecessors, so real time implementations for object classifiers are more frequent. However the solutions for problems are going to more complex problems leaving things such as clothing ensemble classification on the side. There are some proposed solutions on the recognition of clothing garments but all aim to a specific solution in the fashion industry for customer categorization or shopping proposals, however a more general approach which recognizes multiple clothing garments is missing, and a real time clothing ensemble detection could be implemented in several problems. One of such problems is the case study for this project were a CNN implementation is used in video testing to propose the solution for clothing insulation determination using the real time clothing ensemble detector and therefore have a more accurate thermal comfort value. The results proved that the implementation of the chosen CNN architecture could be used as a clothing ensemble detector in a real time implementation, however since a minimized version of the needed dataset was used to verify the viability of this proposal a more complete dataset needs to be created in order to improve the models performance. In general this proposal shows the comparison between come CNN architectures and the datasets available for the propose objectives, as well as the creation of a new dataset that can be successfully used to train the chosen CNN model and produce a real time clothing ensemble detector.
- DFT-based phasor estimator using a MAF with a phase-lead compensator(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2021-09-15) Escudero Armillas, Rafael; Ponce Cruz, Pedro; puelquio/tolmquevedo; Guillén Aparicio, Daniel; Soriano Avendaño, Luis Arturo; Gómez Hernández, José Alberto; Escuela de Ingeniería y Ciencias; Campus Ciudad de México; Ibarra Moyers, Luis MiguelDue to the advancing complexity of the electrical power system, phasor estimators are becoming essential for measuring its dynamics. Many estimators are now needed to effectively monitor some grid, specially for the wireless sensor networks development. However, the smart sensors comprising such networks are low-cost devices and they are only capable of running low computationally loaded algorithms. In consequence, complex algorithms, like the ones based on Kalman filters and the wavelet transform, cannot be applied and a simpler approach is needed. The Fourier filter emerges as a solution since it has a low computational load and it incorporates a moving average filter, whose main advantage is that it can eliminate harmonics. Nevertheless, the moving average filter causes a significant phase delay that is undesirable in fast-response applications. Therefore, in this thesis it is proposed to add a phase-lead compensator to the moving average filter to solve its phase delay problem, while preserving its harmonic rejection ability and the algorithm’s simplicity. This estimator was compared with the conventional Fourier filter and the cosine filter in IEEE C37.118.1 standardized tests to analyze its performance under harmonic contamination, amplitude, and phase angle step changes. After tuning the compensator, the proposal did meet all the standard requirements and showed a slightly faster response than its non-compensated version, yet increasing the algorithm’s execution time. Also, the proposal was tested over the IEEE 13 node test feeder, showing a faster response than the Fourier filter and the cosine filter.