La calidad en las instituciones de educación superior es un tema que ha cobrado fuerza desde la década de los años 80 del siglo pasado. El objetivo consiste en construir y validar un modelo útil para el mejoramiento de la calidad de las Instituciones de Educación Superior. El método de Mínimos Cuadrados Parciales (SEM-PLS), es aplicado a una muestra de 258 estudiantes de nuevo ingreso del Instituto Tecnológico de Hermosillo. Resultados, se establece que las variables: ámbito familiar o de amistad; ubicación; costos; infraestructura; y prestigio académico, influyen significativamente sobre la elección de carrera. Relevancia, proporcionar una herramienta que permita incrementar la demanda de ingreso y disminuir la tasa de deserción. Originalidad, relacionar, a través de un modelo lineal, los factores extrínsecos que influyen sobre la variable elección de carrera. Limitación, el análisis de la relación entre las variables elección y deserción, requiere del egreso de esta generación de alumnos encuestados.

A significant number of alloyed metals applied for different purposes are currently available in industry. The hardness of a piece is an important parameter to consider. The tempering process is widely used to change a metal’s hardness, which is obtained using a hardness test. Once the response is obtained, a way to evaluate the system is by performing an analysis of variance to verify the significance of terms and obtain a regression equation to improve the response. The aim of this work is to illustrate the implementation of an experimental approach based on the steepest ascent method and stopping rules for optimization purposes by considering the hardening process of the steel alloy 4140. The regression coefficients obtained from an experimental design were used to build the steepest path of improvement. The Myers and Khuri stopping rule and the enhanced parabolic stopping rule were applied to determine the best value while individual experimentation is developed. The obtained results, discussion, and a conclusive analysis are disclosed in this document.

This research communication presents an analysis of dynamic supply chains (DSCs). The main goal of model-based cybertronics is to approximate, via a mathematical model from a dynamical system, the dynamics and behavior of dynamic supply chains. This considers that is at the operational level, where automation and control theory approaches take an insight —in this case, via Lyapunov stability—as a way to extend the use of mechatronic systems. Three case studies are presented: Firstly, the mathematical modeling and stability analysis of the ball-and-beam problem, as an approximation of a two echelon supply chain. Secondly, the mathematical modeling and stability analysis of a cold chain with temperature monitoring, and its relationship to inventory levels, are presented. From a theoretical perspective, applying model-based cybertronics in DSCs has direct practical implications: it improves operational control, enhances decision-making, and optimizes inventory management, particularly in cold chains. By treating high-volume supply chains as dynamical systems, managers can anticipate fluctuations and quantify efficiency. Finally, Lyapunov stability analysis ensures that models reliably reflect real-world behavior, enabling automation and predictable performance at an operational level in DSCs.

This technical note aims to present a theoretical analysis for cybertronics engineering (CE) for a class of dynamic supply chains for artificial intelligence (AI)-based products, services or hybrid solutions. The cybertronics-based analysis encompasses three classes of supply chains: (1) energy-based dynamic supply chains (DSC); (2) semiconductor manufacturing and quantum supply chains; and (3) retailing of the AI-based DSC solutions generated. Considering the nonlinear nature of DSC, to provide solutions for products and services based on AI-chained supply chains, novel robust control is addressed via sliding mode control (SMC) with proper stability analysis for the DSC.

Success in the process of implementing the six sigma methodology in companies is not always guaranteed. The aim of this research is to provide the administration of productive companies with a tool that allows them to prioritize the actions and resources to be assigned to maximize the probability of achieving the expected success in the process of implementing the six sigma methodology. The research methodology is based on the use of the method of structural equation models with partial least squares to build a linear regression model, which establishes the causal relationship between the critical success factors and the success in the implementation of the six methodology sigma. A sample of 134 companies of the export industry located in Ciudad Juárez, Chihuahua, Mexico is analyzed. The results establish that: senior management, project management, and organizational infrastructure are the significant critical success factors; the predictive capacity of the estimated model makes it possible to reliably obtain estimates of success in this implementation process; there is no unobserved heterogeneity in the sample. This study contributes, in this region of the country, to strengthening the existing knowledge about the solution to the problem of identifying, what are the critical factors and their impact on the success variable in the implementation of the six sigma methodology? Keywords: critical success factors, six sigma methodology, structural equation models with partial least squares RESUMEN: El éxito en el proceso de implementación de la metodología seis sigma en las empresas, no siempre está garantizado. El objetivo de esta investigación es, proporcionar a la administración de las empresas productivas, una herramienta que les permita priorizar las acciones y recursos a asignar para maximizar la probabilidad de lograr el éxito esperado en el proceso de implementación de la metodología seis sigma. La metodología de investigación, se basa en el uso del método de modelos de ecuaciones estructurales con mínimos cuadrados parciales para construir un modelo de regresión lineal, que establece la relación causal entre los factores críticos de éxito y el éxito en la implementación de la metodología seis sigma. Se analiza una muestra de 134 empresas de la industria de exportación ubicadas en Ciudad Juárez, Chihuahua, México. Los resultados establecen que: alta dirección, administración del proyecto, e infraestructura organizacional son los factores críticos de éxito significativos; la capacidad de predicción del modelo estimado permite obtener, de manera confiable, estimaciones del éxito en este proceso de implementación; no existe heterogeneidad no observada en la muestra. Este estudio contribuye, en esta región del país, a fortalecer el conocimiento existente sobre la solución al problema de identificar, ¿cuáles son los factores críticos y su impacto sobre la variable éxito en la implementación de la metodología seis sigma?. Palabras clave: factores critico de éxito, metodología seis sigma, modelos de ecuaciones estructurales con mínimos cuadrados parciales.

The Six Sigma Methodology (SSM) is a useful tool for the improvement of the quality of the companies, this methodology is constituted by a set of methods of: statistical analysis, collection and analysis of data from its suppliers, customers, and production of the company; analysis of production costs, and, in addition, it is considered as a systematic methodology for the design of new products.