A system dynamics model was developed with the primary purpose of visualizing the behavior of a supply chain (SC) when it adopts a disruptive technology such as additive manufacturing (AM). The model proposed a dynamic hypothesis that defines the following issue: what is the impact of the AM characteristics and processes in the SC? The model was represented through a causal diagram in thirteen variables related to the SC, organized in two feedback cycles and a data flow diagram, based mainly on the three-essential links of the SC and the order display traceability: supplier–focal manufacturer–distribution Network. Once proposed, the model was validated through the evaluation of extreme conditions and sensitivity analysis. As a result, the dynamic behavior of the variables that condition the chain management was analyzed, evidencing reduction times in production, especially in products that require greater complexity and detail, as well as reductions in inventories and the amount of raw material due to production and storing practices from AM. This model is the starting point for alternative supply chain scenarios through structural operating policies and operating policies in terms of process management.

robot para luego realizar la construcción de robots con diferentes propósitos, en este ámbito el objetivo es desarrollar las competencias, en los estudiantes, para el diseño y construcción de tecnofactos robóticos, mediante un proceso de construcción del conocimiento necesario para hacerlo; el segundo ámbito de aplicación es la utilización de la robótica como medio que motiva y da sentido a la construcción de conocimiento en diversas áreas, promoviendo habilidades y competencias en los estudiantes. Además, el aprendizaje de la robótica y el aprendizaje con robótica pueden ser mediados por la informática, la cual aporta tecnologías y herramientas software como los lenguajes de modelado matemático y simulación, tutoriales multimediales, laboratorios virtuales y remotos, entre otros. Así, este artículo se propone destacar cómo la robótica en el aula de clase permite, por una parte, el enriquecer estrategias de aprendizaje como apoyo a la formación integral de los estudiantes, y por otra, es un campo que presenta una demanda creciente en la atención de docentes e investigadores, así como en los estímulos para su investigación, desarrollo y divulgación de parte del estado.

In order to describe the impact that the appropriation of additive manufacturing (AM) has on the supply chain (SC), a validated system dynamics model representing vectorially multiple products and multiple demands in different periods was used as a basis to apply to a case study of medical implant manufacturing, configuring three chain scenarios: 1. traditional supply chain with subtractive manufacturing, 2. centralized supply chain with additive manufacturing, and 3. decentralized supply chain with additive manufacturing. It was possible to notice that the production time is longer in additive manufacturing compared to traditional manufacturing and the cycle time and total demand closure were lower in traditional manufacturing. In addition, it was observed that the AM performance is significantly better in conditions of lower demand, which can be attributed to the characteristics of customization and small batches that this type of production approach implies.

Induced Travel Demand is a phenomenon (ITD) wherein building new road infrastructure increases private car use. ITD has been measured and corroborated through econometric models that give an account of how much travel demand can be induced after road construction. The latter without claims of causality in their inner structure (black-box approach). Beyond the contributions of black-box models, it is still needed to explain structurally ITD for understanding and identifying its causes. Thus, this approach allows policy-makers to design comprehensive policies to deal with ITD in urban context wherein new roads are still needed to guarantee connectivity. In this paper, we present a white-box flight simulator based on a System Dynamics model to support urban transportation decision-making and address ITD. Through the simulator developed, it is possible to improve the causal understanding of ITD. Besides, although the considered policies to intervene in this phenomenon have a conceptual connotation, the simulator is a means to acquire knowledge of structural complexity underlying the interaction between the policies and ITD.