Partial encryption of feature-based product models for collaborative development

Feature-based product systems have been predominantly adopted for product development. To facilitate product development collaboration, product models need to be effectively shared among co-developers. However, in a shared model, it is challenging to preserving confidential features pertaining to intellectual property originating from the initial developer. To address the challenge, this paper presents a novel approach of partially encrypting feature-based product models to support effective collaboration. In the approach, collaborative features to support co-development, and confidential features to specify intellectual property information, are defined in a shared model. An innovative Encryption Transformation Matrix (ETM) is then designed to encode confidential features parametrically and synchronized with collaborative features as a partially encrypted product model. Finally, the approach is validated via complex case studies to demonstrate its effectiveness in industrial applications. The novelty of the approach is based on the innovative ETM design, which makes encryption processes parametric, randomized and self-adaptive. In detail, zooming and transformation variables are devised in ETM to facilitate users to manage encryption processes in a parametric means. Random probability is embedded into ETM to achieve security effectiveness in encrypted models. A self-adaptive mechanism is integrated into ETM to ensure the geometrical validity of encrypted models. The research in this paper, which supports collaborative design on real-world product models, presents a disruptive innovative potential for industrial applications.