El diseño de experimentos es una herramienta utilizada para descubrir como entran en juego distintas variables de un proceso en la obtención de un producto. Existen dos enfoques principales para realizar experimentación, el enfoque clásico y el enfoque de Taguchi. Los diseños de Taguchi son diseños ortogonales que se especializan en estimar efectos principales e interacciones de control por ruido, dejando en segundo plano las interacciones de control por control. Los arreglos ortogonales de Taguchi fueron diseñados de tal manera que un arreglo especifico puede ser utilizado para diferentes números de factores, por ejemplo, el L32 se utiliza cuando existen de 16 a 31 factores y requiere de 32 experimentos. Cuando el número de columnas disponibles excede al número de factores que se desea investigar, las columnas sobrantes se utilizan comúnmente para estimar interacciones. Sin embargo, en casos en que el investigador esta solo interesado en los efectos principales, correr el arreglo completo podría ser algo innecesario y costoso. La presente investigación tiene como objetivo fraccionar los arreglos ortogonales de Taguchi L8, L12, L16 y L32 de tal forma que la fracción generada sirva únicamente para estimar efectos principales y las corridas restantes se agreguen solo en caso de ser requeridas. El método propuesto se basa en búsqueda exhaustiva y utiliza como criterios de selección la D-optimalidad, los factores de inflación de varianza (FIV) y el índice de balance general (IBG). Solo arreglos ortogonales de Taguchi de dos niveles fueron considerados para esta investigación. Los resultados de la investigación se traducen en ahorros significativos de recursos, reducción del tiempo de experimentación y del numero de corridas.

Recently, water has become a resource that generates controversy due to shortage alarms and high consumption by production companies. Making good use of water has become the main objective of government institutions. The food industry generates a large amount of wastewater, concentrating the largest number of contaminants originated in its processes. Wastewater from the food industry is characterized by having a large amount of organic matter, especially fats and oils, as well as suspended solids. The objective of this research is to carry out a characterization of effluents generated in a wastewater treatment plant in the food sector based on Mexican and international regulations to determine whether it is reusable. This article addresses Mexico’s lag in the reuse of treated wastewater in the face of the water crisis, highlighting the urgency of adopting these practices to mitigate water scarcity. For the development of this investigation, samples were collected at the discharge point produced by the company’s effluents, followed by an evaluation of their physical, chemical, and biological parameters, and finally, it was determined that the effluent follows the regulatory standards for discharge into the city sewer but outside the range for reuse in productive processes or irrigation of green areas.

Alias structures for two-level fractional designs are commonly used to describe the correlations between different terms. The concept of alias structures can be extended to other types of designs such as fractional mixed-level designs. This paper proposes an algorithm that uses the Pearson’s correlation coefficient and the correlation matrix to construct alias structures for these designs, which can help experimenters to more easily visualize which terms are correlated (or confounded) in the mixed-level fraction and constitute the basis for efficient sequential experimentation.

Precise control and monitoring systems are essential for efficient energy consumption in food dehydration. This study develops an applied cyber-physical control system to optimize food dehydration in rotary dryers, integrating fuzzy control algorithms through data acquisition. The system architecture utilizes DHT22 transducers for temperature monitoring, a DHT11 for humidity measurement, an IP65 anemometer for dryer wind speed detection, and a load cell weight tracking system, all connected to an Arduino Mega 2560 R3 microcontroller implementing the integrated fuzzy logic library. Experimental evaluations were performed with different carrot loads (1.5, 2.5, and 3.5 kg), demonstrating optimal performance at the initial load of 3.5 kg with an energy consumption of 11,589 kJ for 9.33 h, achieving a final moisture reduction of 10%. The 1.5 kg sample showed optimal dehydration kinetics at an average dryer hot air velocity of 1.5 m/s, while maximum efficiency (86%) was achieved with the 3.5 kg load, compared to 30% and 17% for the smaller batches. These results validate the integration of cyber-physical systems to optimize the dehydration rate (0.301 kg/h), thereby ensuring product quality in agro-industrial drying applications.

This article shows a method for the statistical analysis of signals. Firstly, this method was applied to analyze the processing of signs generated by an acquisition card for pulse measurement using the synchronous demodulation method. The application of the method allowed the study of each signal consisting of a descriptive statistical analysis, followed by the analysis of the trend and dynamics of the movement using the augmented Dickey–Fuller test and Hurst exponent, respectively. Secondarily, the method presented here supported the comparison between the pulse signals obtained by synchronous demodulation and plethysmography methods. In addition, the residuals from the pulse comparison of both methods were analyzed. To quantify the differences between the signals, these were compared using the mean-squared error, the root-mean-square error, the mean absolute error, the mean error, the mean absolute percentage error, and the mean percentage error. After this research, it was possible to analyze the signals knowing characteristics such as the following: the presence of normal, exponential, lognormal, and uniform distributions, stationary trend, and dynamic movement anti-persistent. The novelty that this article proposes is the use of concepts traditionally used in the study of time series and models of demand administration, now focused on supporting improvements over the different stages of design and conceptualization of signal processing devices.