Papers by eduardo vyhmeister
IFIP advances in information and communication technology, 2024
arXiv (Cornell University), Mar 4, 2024
AI and ethics, Feb 14, 2024
International Journal of Production Research, Jul 22, 2022
This paper outlines the main idea and approach of the H2020 ASSISTANT (LeArning and robuSt deciSI... more This paper outlines the main idea and approach of the H2020 ASSISTANT (LeArning and robuSt deciSIon SupporT systems for agile mANufacTuring environments) project. ASSISTANT is aimed at the investigation of AI-based tools for adaptive manufacturing environments, and focuses on the development of a set of digital twins for integration with, management of, and decision support for production planning and control. The ASSISTANT tools are based on the approach of extending generative design, an established methodology for product design, to a broader set of manufacturing decision making processes; and to make use of machine learning, optimization, and simulation techniques to produce executable models capable of ethical reasoning and data-driven decision making for manufacturing systems. Combining human control and accountable AI, the ASSISTANT toolsets span a wide range of manufacturing processes and time scales, including process planning, production planning, scheduling, and real-time control. They are designed to be adaptable and applicable in a both general and specific manufacturing environments.
International Journal of Production Research
This paper outlines the main idea and approach of the H2020 ASSISTANT (LeArning and robuSt deciSI... more This paper outlines the main idea and approach of the H2020 ASSISTANT (LeArning and robuSt deciSIon SupporT systems for agile mANufacTuring environments) project. ASSISTANT is aimed at the investigation of AI-based tools for adaptive manufacturing environments, and focuses on the development of a set of digital twins for integration with, management of, and decision support for production planning and control. The ASSISTANT tools are based on the approach of extending generative design, an established methodology for product design, to a broader set of manufacturing decision making processes; and to make use of machine learning, optimization, and simulation techniques to produce executable models capable of ethical reasoning and data-driven decision making for manufacturing systems. Combining human control and accountable AI, the ASSISTANT toolsets span a wide range of manufacturing processes and time scales, including process planning, production planning, scheduling, and real-time control. They are designed to be adaptable and applicable in a both general and specific manufacturing environments.
Frontiers in Earth Science
Tsunamis are unpredictable and infrequent but potentially large impact natural disasters. To prep... more Tsunamis are unpredictable and infrequent but potentially large impact natural disasters. To prepare, mitigate and prevent losses from tsunamis, probabilistic hazard and risk analysis methods have been developed and have proved useful. However, large gaps and uncertainties still exist and many steps in the assessment methods lack information, theoretical foundation, or commonly accepted methods. Moreover, applied methods have very different levels of maturity, from already advanced probabilistic tsunami hazard analysis for earthquake sources, to less mature probabilistic risk analysis. In this review we give an overview of the current state of probabilistic tsunami hazard and risk analysis. Identifying research gaps, we offer suggestions for future research directions. An extensive literature list allows for branching into diverse aspects of this scientific approach.
Computer Aided Chemical Engineering
Congreso de Ciencia y Tecnología ESPE
Se pretende añadir valor agregado a las algas pardas (Pheophyta/Padina) ecuatorianas empleándolas... more Se pretende añadir valor agregado a las algas pardas (Pheophyta/Padina) ecuatorianas empleándolas como recursos para la producción de ácidos orgánicos y alginato de sodio de manera que se evidencie una fuente alternativa de materia prima en la petroquímica. Basado en el trabajo de Mazumder se determinaron las condiciones para la extracción alginato de sodio empleando agua de mar y concentración de catalizador (Na2CO3) al 0% ,1.5% y 3%; el valor del mejor rendimiento fue de 27,34%. Así como también para la obtención de ácidos orgánicos (ácido láctico y acético) basado en el trabajo de Jeon, se empleó metodología de superficie de respuesta (MSR); para lo cual se empleó agua de mar para dos rutas: con alginato de sodio procedente de Sigma Aldrich y con algas pardas ecuatorianas pre-tratadas. El diseño experimental de Box Behken tiene como factores a la temperatura, tiempo de digestión, salinidad del agua y cantidad de catalizador (CaO). El mayor rendimiento obtenido en el estudio para ...
Journal of Environmental Management
Clean Technologies and Environmental Policy
Analytical and Bioanalytical Chemistry
Static headspace gas chromatography-ion mobility spectrometry (SHS GC-IMS) is a relatively new an... more Static headspace gas chromatography-ion mobility spectrometry (SHS GC-IMS) is a relatively new analytical technique that has considerable potential for analysis of volatile organic compounds (VOCs). In this study, SHS GC-IMS was used for the identification of the major terpene components of various essential oils (EOs). Based on the data obtained from 25 terpene standards and 50 EOs, a database for fingerprint identification of characteristic terpenes and EOs was generated utilizing SHS GC-IMS for authenticity testing of fragrances in foods, cosmetics, and personal care products. This database contains specific normalized IMS drift times and GC retention indices for 50 terpene components of EOs. Initially, the SHS GC-IMS parameters, e.g., drift gas and carrier gas flow rates, drift tube, and column temperatures, were evaluated to determine suitable operating conditions for terpene separation and identification. Gas chromatography-mass spectrometry (GC-MS) was used as a reference method for the identification of terpenes in EOs. The fingerprint pattern based on the normalized IMS drift times and retention indices of 50 terpenes is presented for 50 EOs. The applicability of the method was proven on examples of ten commercially available food, cosmetic, and personal care product samples. The results confirm the suitability of SHS GC-IMS as a powerful analytical technique for direct identification of terpene components in solid and liquid samples without any pretreatment. Graphical abstract Fingerprint pattern identification of terpenes and essential oils using static headspace gas chromatography-ion mobility spectrometry.
Journal of Cleaner Production, 2017
Dyna, May 10, 2012
RESUMEN: Este trabajo presenta el control de un secador rotatorio directo basado en optimización ... more RESUMEN: Este trabajo presenta el control de un secador rotatorio directo basado en optimización no lineal. Esta metodología permite auto-sintonizar dinámicamente un controlador PI o PID, mejorando claramente el control del proceso respecto de la sintonización clásica. El control del proceso se realiza a través de simulación computacional vía Matlab y su verificación a través de un proceso piloto, lo que permite apreciar la potencialidad de la sintonía dinámica que se propone. Los resultados, tiempo de respuesta y dinámica de control posibilitan que investigación futura pueda escalar esta propuesta desde el laboratorio a procesos industriales.
Uploads
Papers by eduardo vyhmeister