The COVID-19 pandemic and the quarantine period determined that university students (human resource) in Mexico had adopted the online class modality, which required them to adapt themselves to new technologies and environmental conditions that are different from classrooms at their university. Specifically, these new environmental conditions can be uncomfortable and have an impact on the students’ academic performance. Consequently, the present study aims to determine the impact that the lighting, noise, and temperature levels (independent variables) have on academic performance (dependent variable) in university students during the COVID-19 pandemic. To do this, a questionnaire was developed, which was applied to 206 university students online, and a structural equation model was built that integrates the four variables through three hypotheses, which were statistically validated through the partial least squares method. Results showed that temperature, lighting, and noise have significant direct effects on university students’ academic performance. As a conclusion, it was obtained that the three independent variables have an impact in the sustainability of university students (human resource).

Defects are considered as one of the wastes in manufacturing systems that negatively affect the delivery times, cost and quality of products leading to manufacturing companies facing a critical situation with the customers and to not comply with the IPC-A-610E standard for the acceptability of electronic components. This is the case is a manufacturing company located in Tijuana, Mexico. Due to an increasing demand on the products manufactured by this company, several defects have been detected in the welding process of electronic boards, as well as in the components named Thru-Holes. It is for this reason that this paper presents a lean manufacturing application case study. The objective of this research is to reduce at least 20% the defects that are generated during the welding process. In addition, it is intended to increase 20% the capacity of three double production lines where electronic boards are processed. As method, the Plan-Do-Check-Act (PDCA) cycle, is applied. The Pareto charts and the flowchart are used as support tools. As results, defects decreased 65%, 79%, and 77% in three analyzed product models. As conclusion, the PDCA cycle, the Pareto charts, and the flowchart are excellent quality tools that help to decrease the number of defective components.

The present work aims at the comprehensive application of stochastic and optimization tools with the support of Information and Communication Technologies (ICT) through a case study in a logistics process for electronic goods; simulation and Response Surface Methodology (RSM) are applied for this purpose. The problem to be evaluated is to define an optimal distribution cost for products shipped to wholesale customers located in different cities in Mexico from a manufacturing plant in Tijuana, Mexico. The factors under study are the product allocation for each distribution center, finished good inventory level and on time deliveries, which are supposed to be significant to get the objective. The methodology applied for this problem considers the design of a discrete event simulation model to represent virtually the real life of logistics process, which is considered a complex system due to different activities are interrelated to carry it out. This model is used to execute the different experiments proposed by the RSM. The results obtained from simulation model were analyzed with the RSM to define the mathematical model that allows identifying the parameters of the factors in order to optimize the process. The findings prove how the ICT facilitate the application of stochastic tools with the purpose of process optimization.

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