Human Interactions for Self-Adaptive Virtual Product Prototype

In engineering, self-adaptive product model provides a medium which is in the possession of the capability to accommodate any knowledge for autonomous actions to modify product representations in case of any changed circumstance. In current advanced product models, knowledge defines relationships among feature parameters in order to automatic modification of the model for new situations and events. In this way rules, formulas, algorithms, and other knowledge features give self-adaptive characteristic to product model for design parameter driven self modification and reconfiguration. Generally, new instances are created from a generic model. Changes are propagated across the product model by contextual connections of feature parameters. Development of self adaptive product model needs new methods for decision assistance during lifecycle of the product. This paper introduces a research which is aimed to contribute to this effort by extension of the direct feature parameter control knowledge towards higher level representations. The proposed modeling applies higher level knowledge for the definition of relationship between product objectives and feature parameters. Objective covers product function which is supported by specification and knowledge driven method in order to control product feature generation. Any objective change initiates appropriate changes of the self adaptive product model. In order to achieve this, contextual chain is established between objective and the related affected feature parameters in the product model. The proposed method is a contribution to efforts to achieve aimed physical product behaviors using more sophisticated virtual prototype of product.