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<dc:title xml:lang="fr">Amélioration du processus de la conception inventive par l'utilisation de méthodes agiles et d'algorithmes d'apprentissage automatique.</dc:title>
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<dc:subject xml:lang="fr">Conception inventive</dc:subject>
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<dc:subject xml:lang="fr">Théorie du Lean</dc:subject>
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<dcterms:abstract xml:lang="fr">Au cours des dernières décennies, les entreprises sont constamment à la recherche d'approches qui les aident à réduire le temps du processus d'innovation. Parmi ces approches, on peut citer les processus de conception inventive basés sur TRIZ, tels que la Méthodologie de Conception Inventive (MCI). Néanmoins, une des critiques souvent formulées est que cette approche n'a pas l'agilité nécessaire. Par conséquent, il était nécessaire de combiner MCI avec d'autres méthodologies pour accroître son agilité. Dans cette thèse, une méthode basée sur le Lean a été développée pour ajouter les caractéristiques agiles à MCI. En outre, les méthodes PAH et AMDEC ont été intégrées au processus pour sélectionner le problème initial le plus important. De plus, les algorithmes d'apprentissage automatique et la méthode doc2vec ont été utilisés pour extraire les données essentielles du processus. Ces travaux de recherche visent à faciliter et à accélérer la conception inventive dans les entreprises.</dcterms:abstract>
<dcterms:abstract xml:lang="en">In recent decades, companies have continually sought approaches that help them reduce the innovation cycle time due to its importance to their success. Among these approaches, it is possible to mention the TRIZ-based systematic inventive design processes, such as Inventive Design Methodology (IDM). However, one of the criticisms often leveled is that this approach does not have the essential agility. Hence, it is required to combine IDM with other methodologies to increase its agility. In this thesis, a Lean-based based method has been developed to add the agile characteristics to IDM. Besides, Analytical Hierarchy Process (AHP) and Failure Mode and Effect Analysis (FMEA) methods have been integrated into the process to select the most important initial problem. Furthermore, the machine learning algorithms and neural network doc2vec have been applied to extract the essential data in the process. These research works aim to facilitate and accelerate inventive design in companies.</dcterms:abstract>
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