Se presenta una metodología que integra variables internas y externas, en tres estadios, que determinan la viabilidad de un proyecto de generación de energía elécrica, a partir del biogás captado del sitio de disposición final (SDF) del municipio de Pachuca, Hidalgo. Primero, se analiza el SDF a nivel técnico-financiero, con una proyección de 20 años, con y sin certificados de carbono, resultando viable el proyecto. El segundo estadio (regional) determina que las variables que más impactan son los tiempos de gestión municipal, los aspectos legales y sociales y la sensibilización de actores. El tercer nivel (ambiente macro) considera que el precio de certificados de carbono, apoyos federales y aspectos ambientales permiten que el proyecto tenga proyección para la gestión municipal. Las variables que más impactan al proyecto son: periódos municipales, sensibilización de actores políticos y población afectada, así como la asesoría de expertos en la materia que asocien las variables como un proyecto integral.

Process reengineering is a very useful tool, specifically in industrial engineering where technological advances, information systems, customer requirements, and more have led to the need for radical change in some or all areas of an organization. The objective of this work is to show the usefulness of applying reengineering in the case of the footwear industry to make a proposal to change the problem area and the production decoration line as well as compare it with the current process using models of simulation performed in the Arena™ software. The proposal consisted of merging two production lines and comparing the current design with the proposal as well as comparing different parameters such as the use of resources and the production rate. The results indicated that the production rate increases by approximately 29% with the new design, using the same resources. In addition, using the OptQuest tool of the Arena™ software, it was found that with the new process, the production rate could be increased by up to 41% compared to the current process.

This paper presents an application of the simulation of discrete events (SED) using ARENA TM in the management of large-scale breeding farms. The main objective of the simulation model is to find a policy of replacement, to ensure the best economic performance of a farm. The only variant analyzed of replacement policy was the number of cycles set in permanency for a sow in the herd. Considered incomes come from the sale of piglets and unproductive sows, and costs are due to the feeding of animals, replacement sows purchases, and the operation expenses of the farm. For this analysis, the production process was divided into three major stages called: mating, pregnancy or gestation and lactation. The sow's movement from one stage to other was modeled by cycle-dependent transition probabilities. Considering the daily utility, as response variable, the model shows the best number of cycles to maintain the sows.

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