- Lubbock, Texas, United States
La Asociación Nacional de Universidades e Instituciones de Educación Superior ha diseñado programas para el desarrollo de la educación superior, donde surge la tutoría académica. La Universidad Juárez del Estado de Durango cuenta con el... more
La Asociación Nacional de Universidades e Instituciones de Educación Superior ha diseñado programas para el desarrollo de la educación superior, donde surge la tutoría académica. La Universidad Juárez del Estado de Durango cuenta con el Programa Institucional de Tutoría (PIT) con el propósito de combatir el abandono y rezago escolar. Aunque se han desarrollado diversas evaluaciones al PIT, ninguna ha contado con la participación de todos los actores educativos involucrados en este programa. Este trabajo, exploratorio y descriptivo, se llevó a cabo mediante la aplicación y análisis estadístico de un cuestionario diseñado por la Red Regional Noreste de Tutoría, con el objetivo de evaluar el PIT desde el enfoque de todos los actores que participan en él. Se contó con la participación de 3859 actores educativos, encontrando que la percepción de las figuras académicas sí tienen un impacto en la manera en que los estudiantes perciben este programa.
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La Asociación Nacional de Universidades e Instituciones de Educación Superior ha diseñado programas para la tutoría académica como el Programa Institucional de Tutoría (PIT) aplicado por la Universidad Juárez del Estado de Durango (UJED)... more
La Asociación Nacional de Universidades e Instituciones de Educación Superior ha diseñado programas para la tutoría académica como el Programa Institucional de Tutoría (PIT) aplicado por la Universidad Juárez del Estado de Durango (UJED) orientado a combatir el abandono y rezago escolar. Pocas evaluaciones al PIT han involucrado a todos sus actores educativos. Este trabajo tuvo como objetivo analizar las relaciones estadísticas entre las evaluaciones de los diversos actores educativos del PIT en la UJED, con alcance exploratorio y descriptivo, llevado a cabo a través de la aplicación y análisis estadístico del cuestionario diseñado por la Red Regional Noreste de Tutoría. Participaron 3859 actores educativos entre Tutorados, Tutores, Coordinadores de Tutoría en la Unidad Académica, Directivos de ésta y Coordinador Institucional de Tutoría. Se encontró que la percepción de las figuras académicas sí tienen un impacto en la manera en que los estudiantes perciben este programa.
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Research Interests:
Introducción: El comienzo del año 2020 llegó acompañado de una pandemia causada por el virus denominado SARS-CoV-2. Con las medidas de distanciamiento social implementadas para evitar la propagación de este virus, se presentan... more
Introducción: El comienzo del año 2020 llegó acompañado de una pandemia causada por el virus denominado SARS-CoV-2. Con las medidas de distanciamiento social implementadas para evitar la propagación de este virus, se presentan problemáticas de salud mental, como ansiedad, depresión, etc., trayendo como consecuencia una necesidad de atención a pacientes a distancia. Dadas las cifras alarmantes de incidencias de suicidio en la sociedad actual, aunadas a estas medidas de distanciamiento, son requeridas herramientas de apoyo para identificar individuos en riesgo de cometer suicidio. Objetivo: Proponer y evaluar una nueva metodología para calcular riesgo de suicidio en usuarios de Twitter, apoyándose en el análisis de emociones. Materiales y Métodos: Usando modelos de aprendizaje estadístico (supervisado y no supervisado), la metodología propuesta identifica el nivel de riesgo en el texto analizado de 77 tuits de usuarios regulares y de figuras políticas en México y Latinoamérica. Result...
Engineering managers use productivity measures for performance evaluation and decision-making. The common assessment of productivity normally considers a simple fractional relationship of revenues over costs, where desirable productivity... more
Engineering managers use productivity measures for performance evaluation and decision-making. The common assessment of productivity normally considers a simple fractional relationship of revenues over costs, where desirable productivity occurs when the system delivers higher revenues than the volume point of costs, leading to a productivity index value larger than one; implying that the output is greater than the input. However, the second law of thermodynamics states it is impossible to convert energy completely into work in a closed system. Contemporary productivity tools do not follow this law because they assume open systems in which energy can enter and exit a system, and they do not concern themselves with externalities imposed on meta-systems. This leaves an opportunity to create a different perspective on the efficiency of work. This paper uses the laws of thermodynamics to develop a formula that shifts the perception of productivity measures. The dynamics of the formula ar...
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Before World War II, industries carried out maintenance only when equipment suffered a breakdown and no interest was showed towards its economic implications. The manufacturing conditions during WWII produced a paradigm shift in... more
Before World War II, industries carried out maintenance only when equipment suffered a breakdown and no interest was showed towards its economic implications. The manufacturing conditions during WWII produced a paradigm shift in maintenance management. Avoiding failure, instead of waiting for it, led to consider costs in maintenance policies. Much research has been developed in the area of maintenance-related costs and maintenance cost models. In this research paper, these costs were analyzed to understand its applications and relevance in maintenance management. Cost categories and subcategories are used to present models and a brief discussion is presented about advantages and disadvantages of maintenance cost models.
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Abstract A wide variety of Condition-Based Maintenance (CBM) techniques deal with the problem of predicting the time for an asset fault. Most statistical approaches rely on historical failure data that might not be available in several... more
Abstract A wide variety of Condition-Based Maintenance (CBM) techniques deal with the problem of predicting the time for an asset fault. Most statistical approaches rely on historical failure data that might not be available in several practical situations. To address this issue, practitioners might require the use of self-starting approaches that consider only the available knowledge about the current degradation process and the asset operating context to update the prognostic model. Some authors use Autoregressive (AR) models for this purpose that are adequate when the asset operating context is constant, however, if it is variable, the accuracy of the models can be affected. In this paper, three autoregressive models with exogenous variables (ARX) were constructed, and their capability to estimate the remaining useful life (RUL) of a process was evaluated following the case of the aluminum crack growth problem. An existing stochastic model of aluminum crack growth was implemented and used to assess RUL estimation performance of the proposed ARX models through extensive Monte Carlo simulations. Point and interval estimations were made based only on individual history, behavior, operating conditions and failure thresholds. Both analytic and bootstrapping techniques were used in the estimation process. Finally, by including recursive parameter estimation and a forgetting factor, the ARX methodology adapts to changing operating conditions and maintain the focus on the current degradation level of an asset.
Research Interests:
Research Interests:
Condition-Based Maintenance (CBM) appeared in the eighties as a response to avoid unnecessary maintenance and its related economic and time implications. Many techniques, based on the asset’s condition, to determine the adequate moment to... more
Condition-Based Maintenance (CBM) appeared in the eighties as a response to avoid unnecessary maintenance and its related economic and time implications. Many techniques, based on the asset’s condition, to determine the adequate moment to perform maintenance actions have been developed, using a wide variety of tools. However, CBM is not actively applied by managers or companies. An in-depth literature review using the State of the Art Matrix (SAM) analysis methodology is applied to the CBM literature to understand the reason for poor CBM implementation. In addition, the critical areas of future CBM research are explored and analyzed to assist industrial engineers and managers to better comprehend the current state of CBM applications and research opportunities.
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Managing a complex technical system, which incorporates extensive human-technology interface, is difficult due to its inherent systemic unpredictability. Management often wants to create a shift in an underperforming system, but is... more
Managing a complex technical system, which incorporates extensive human-technology interface, is difficult due to its inherent systemic unpredictability. Management often wants to create a shift in an underperforming system, but is uncertain about how an intervention will affect it. A living systems simulator would be useful to engineers and technical managers in monitoring policy decisions for shifts in the trend of performance. The creation of a tool to monitor living systems will require the fields of system dynamics and statistical process control to converge. A State of the Art Matrix approach identifies the literature intersecting the fields of system dynamics and statistical process control. A review of the literature found an opportunity to implement linear profile monitoring within systems dynamic simulation, and room for improvement in the use of general systems tools. A scorecard approach evaluates the potential of existing capabilities of system dynamics software to simu...
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Objectives: To identify early suicide risk signs on depressive subjects, so that specialized care can be provided. Various studies have focused on studying expressions on social networks, where users pour their emotions, to determine if... more
Objectives: To identify early suicide risk signs on depressive subjects, so that specialized care can be provided. Various studies have focused on studying expressions on social networks, where users pour their emotions, to determine if they show signs of depression or not. However, they have neglected the quantification of the risk of committing suicide. Therefore, this article proposes a new index for identifying suicide risk in Mexico. Methodology: The proposal index is constructed through opinion mining using Twitter and the Analytic Hierarchy Process. Contribution: Using R statistical package, a study is presented considering real data, making a classification of people according to the obtained index and using information from psychologists. The proposed methodology represents an innovative prevention alternative for suicide.
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Condition-Based Maintenance (CBM) appeared in the eighties as a response to avoid unnecessary maintenance and its related economic and time implications. Many techniques, based on the asset's condition, to determine the adequate... more
Condition-Based Maintenance (CBM) appeared in the eighties as a response to avoid unnecessary maintenance and its related economic and time implications. Many techniques, based on the asset's condition, to determine the adequate moment to perform maintenance actions have been developed, using a wide variety of tools. However, CBM is not actively applied by managers or companies. An in-depth literature review using the State of the Art Matrix (SAM) analysis methodology is applied to the CBM literature to understand the reason for poor CBM implementation. In addition, the critical areas of future CBM research are explored and analyzed to assist industrial engineers and managers to better comprehend the current state of CBM applications and research opportunities.
Research Interests:
A wide variety of Condition-Based Maintenance (CBM) techniques deal with the problem of predicting the time for an asset fault. Most statistical approaches rely on historical failure data that might not be available in several practical... more
A wide variety of Condition-Based Maintenance (CBM) techniques deal with the problem of predicting the time for an asset fault. Most statistical approaches rely on historical failure data that might not be available in several practical situations. To address this issue, practitioners might require the use of self-starting approaches that consider only the available knowledge about the current degradation process and the asset operating context to update the prognostic model. Some authors use Autoregressive (AR) models for this purpose that are adequate when the asset operating context is constant, however, if it is variable, the accuracy of the models can be affected. In this paper, three autoregressive models with exogenous variables (ARX) were constructed, and their capability to estimate the remaining useful life (RUL) of a process was evaluated following the case of the aluminum crack growth problem. An existing stochastic model of aluminum crack growth was implemented and used to assess RUL estimation performance of the proposed ARX models through extensive Monte Carlo simulations. Point and interval estimations were made based only on individual history, behavior, operating conditions and failure thresholds. Both analytic and bootstrapping techniques were used in the estimation process. Finally, by including recursive parameter estimation and a forgetting factor, the ARX methodology adapts to changing operating conditions and maintain the focus on the current degradation level of an asset.
Research Interests:
The main objective of Condition-Based Maintenance (CBM) is to assess the level of degradation on an equipment for maintenance decision-making. CBM literature shows a wide variety of methodologies to fulfill this objective, with positive... more
The main objective of Condition-Based Maintenance (CBM) is to assess the level of degradation on an equipment for maintenance decision-making. CBM literature shows a wide variety of methodologies to fulfill this objective, with positive results on diagnostics and prognostics of failure. However, the degradation variable could suffer an unexpected change on degradation rate (due to external conditions or natural behavior on degradation process) that might negatively affect the performance of these methodologies. Identifying this change as soon as possible could bring relevant information to maintenance managers for better decision making. The identification of changes in condition degradation can be done through statistical monitoring in the form of Control Charts that emit alerts when the monitored variable shows special variations. This paper develops a review of the current state of the body knowledge performed with the State-of-the-Art Matrix methodology on Control Charts applied in CBM, with the objective of detecting applications, challenges and opportunity areas for statistical monitoring on CBM decision-making.