Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Guidelines for selection and justification of computeraided engineering (CAE) software for plastic injection molding(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2010-10-01) Serna Vázquez, Livier; Serna Vázquez, Livier; 227068; ITESMThe present research focuses on the use of plastic injection simulation in part design. CAE analysis for injection molding can be used at three different levels: parts design, mold design and molding process troubleshooting. Injection molded plastic parts include the following elements: material, part design, mold design and process. The injection molding process involves many considerations such as part geometry, material, mold design and process variables. The simulation module being considered in this study is the mold fill analysis (based on Cadmould, a commercial simulation system). Material, mold design, injection machine is already defined. As part of this study, complexity taxonomy for plastic parts was developed, as well as a differentiation between the engineering team involved in terms of expertise. Several information sources were used to develop a case study, which approaches a part fill time optimization. The scenario in which this optimization is made is a manufacturing plant that launches several new parts per year. These parts have different degrees of complexities. This study's main contribution is the identification and quantification of key factors regarding the cost and benefit associated with simulation for injection molding. It was concluded that the economic benefit of simulation will increase as more parts are run, whereas the level of expertise of the engineering team has a negative impact in this kind of benefit. The percentage of time saved in the case study falls between 10-30% using simulation tools.
- Effects on Clustering Quality of Direct and Indirect Communication Among Agent in Ant-based Clustering Algorithms(Instituto Tecnológico y de Estudios Superiores de Monterrey, 01/05/2005) Montes de Oca Roldán, Marco A.; Dr. Leonardo Garrido Luna; Dr. José Luis Aguirre Cervantes; Dr. Ramón Felipe Brena PineroAnt-based clustering algorithms are knowledge discovery tools inspired by the collective behavior of social insect colonies. In these algorithms, insects are modeled as software agents that communicate with each other indirectly through the environment. This particular kind of communication is known as stigmergic communication. In the classic ant-based clustering algorithm, a group of agents that exhibit the same behavior move randomly over a toroidal square grid. In the environment there are data objects that were initially scattered in a random fashion. The objects can be picked up, moved or dropped in any free location on the grid. An object is picked up with high probability if it is not surrounded by similar objects and is dropped with high probability if an agent's neighborhood is densely populated by other similar objects and its location is free. Here, stigmergy occurs when an object is placed next to another. The resultant structure is much more attractive to agents to drop other similar objects nearby. However, stigmergy is not the only way social insects interact with each other. In most species, trophallaxis or liquid food exchange among members of the same colony, plays a key role in their social organization. Consider the case of some termite species which require intestinal protozoa to derive benefits from cellulose. Their early instar nymphs are fed either by oral or anal trophallaxis. The latter infects them with symbiotic protozoa or bacteria contained in the proctodeal liquid. The subsocial association result of this codependence have evolved into a complex social and morphological structure. Inspired by the trophallaxis phenomenon observed in some ant and termite species, two different communication strategies among agents in ant-based clustering algorithms are investigated: (i) direct and (ii) indirect communication. The impact on the final clustering quality is evaluated by comparing the development of the clustering process generated by each strategy. It is shown that benefits on the final clustering are directly related to the usefulness of the exchanged information, its use, and on the number of participating agents.