Resumen:
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Consulta en la Biblioteca ETSI Industriales (8500)
[EN] At the present time, the automotive sector represents a competitive environment for the companies that operate in. Automotive products need to fulfil requirements in terms of cost, weight and quality, being always ...[+]
[EN] At the present time, the automotive sector represents a competitive environment for the companies that operate in. Automotive products need to fulfil requirements in terms of cost, weight and quality, being always delivered on time. These requirements suppose constraints in design and manufacturing processes. Hence, the selection of joining and assembly processes, widely used in automotive, have repercussions in the design of the product as well as in its effective total cost.
The research has been undertaken in an automotive company with expertise in spot welding. Their typical design approach is to select a joining technology from the beginning without considering other alternatives. Therefore, there is a need to be able to examine alternative joining solutions and their requirements in order to choose the solution with the lowest critical time, cost, weight and quality constraints. As a response to this need, this research aims to develop an approach that can be applied to support the knowledge modelling for three different joining technologies. This approach is based in the identification of best practices, knowledge capturing and validation through expert judgment.
Manufacturing constraints and design considerations are identified and captured due to their influence on the product design and development. These constraints, which are based on spot welding, were captured in the form of rules and recommendations. The adaptation of the spot welding rules to laser beam welding and adhesive bonding was also developed.
This research work will facilitate the transformation of product design considerations in terms of manufacturing constraints and capabilities in design rules. These set of rules and their respective adaptations establish the basis for the future development of a Knowledge-Based Engineering Environment.
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