Automated sizing of automotive steering ball joints in parametric CAD environment using expert knowledge and feature-based computer-assisted 3D modelling

Ball joints used in the steering systems of vehicles are exposed to fluctuating loads, which can cause fatal accidents in case of failure. The design of ball joints is an iterative and time-consuming process. Even though the automotive industry is preparing for the era of autonomous self-steering vehicles, parts such as ball joints were not designed using a fully automated parametric design methodology. Recently, parametric design of automotive ball joints based on variable design methodology using knowledge and feature-based computer-assisted-3D modelling methods was studied. However, these studies do not give details of the interactive sizing process within the part and assembly module to determine the final dimensions for avoidance of fatigue failure. This work provides methods and discusses details of the configurable sizing of a ball joint assembly under the boundaries of the developed “parametric design platform”. The platform closes the software gap for the automated reconfiguration and sizing of the ball joint assembly using a three-dimensional (3D) modelling technique. The platform can parametrically change part, material, feature, geometry, assembly and dimension features in a programmable environment. It can also reconfigure the ball joint assembly model considering various structured data conforming to technical standards and reasoning mechanisms with “engineering and geometrical relations” provided in this work, and data gathering along the life cycle of a product. Parameterised 3D solid models and a knowledge base of ball joints are stored in a database, and then an evaluation process within the platform that is capable of sizing ball joints for infinite fatigue-life has been established to verify sizing. It demonstrates the practicability and validity of the automated sizing of a steering ball joint within a configurable design environment and with minimum human expert knowledge and interaction.