Abstract

Advancements in product development have reached full integration of engineering activities and processes in product lifecycle management (PLM) systems. PLM systems are based on high-level modeling, simulation and data management. Despite significant development of modeling in PLM systems, a strong demand was recognized for improved decision assistance in product development. Decision assistance can be improved by application of methods from the area of computer intelligence. In order for a product development company to stay competitive, it is important for its modeling system to be relied on local even personal knowledge. The authors analyzed current PLM systems for shortcomings and possibilities for extended intelligence at decision-making during product development. They propose methods in order to increase suitability of current modeling systems to accommodate knowledge based IT at definition of sets of parameters of modeled objects and in the management of frequent changes of modeled objects. In the center of the proposed methodology, constrained parameters act as restricting factors at definition and modification of parameters of associative engineering objects. Paper starts with an outlook to modeling in current engineering systems and preliminary results by the authors. Following this, groups of essential information as handled by he proposed modeling are summarized and procedures for processing of that groups of information are detailed. Next, management of chains of changes along chains of associa-tive product objects and a new style of decision assistance in modeling systems are explained. Changes are created or verified by behavior analysis. Finally, behavior analysis, human intent combination, product data view creation, and change management are discussed as the proposed integrated and coordinated methodology for enhanced support of decision-making in product development.

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