Browsing by Author "Miller Peluffo, Jhon Alexander"
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Item Descripción del Impacto de la Inteligencia Artificial en metodologías Lean mediante una revisión bibliográfica para la optimización de recursos operacionales(Universidad Santiago de Cali, 2022) Miller Peluffo, Jhon Alexander; Bustos Ramirez, Andres Felipe; Vargas Vásquez, Jhon Edwar (Director)Currently industries are not only facing challenges concerning increasing sales volume or owning a product on the market, to be more competitive and stand out both commercially and technologically decide to implement strategies that allow them to have a continuous improvement in all areas of their operations. Several companies have decided to take a step forward towards adopting Industry 4.0 due to the wide benefits that it can have for the optimization of their processes and use of resources, since to a large extent in synergy with the implementation of Lean methodologies are attributed benefits such as reduction of waste in the production and provision of services, operational costs among others. Usually, these wastes are associated with the execution of activities that do not generate value to the process, such as excess inventory in process, quality defects or reprocessing, these over costs in the operations limit the productivity of the industries and in turn to be commercially competitive regarding the price of their offered products, the implementation of productive models under lean methodologies allow this desired optimization. But using parallel Industry 4.0 tools such as Artificial Intelligence, it is possible to reduce operational costs associated with micro-waste that are not easily identifiable, but that represent a high percentage in the cost overruns that end up impacting the final cost and the retail price to the consumer; through a complete, cutting-edge bibliographic review, defines the impact that Artificial Intelligence has on these operational models structured under the Lean methodology