Ultra-high precision predictive assembly of composite parts is vital for large-scale aircraft production. The current practice of composite fuselage shape control is low efficient, non-optimal and experience-dependent. We propose an automated optimal shape control system that can adjust composite parts to an optimal configuration efficiently. The objective is accomplished by (i) building a finite element analysis platform, validated by experimental data; (ii) developing a surrogate model with consideration of actuator uncertainty, part uncertainty, modeling uncertainty, and unquantified uncertainty to achieve predictive performance and embedding the model into a feed-forward control algorithm; (iii) conducting multivariable optimization to determine the optimal actions of actuators. Via a case study, we show that the surrogate model considering uncertainties achieves satisfactory prediction performance and that the automated optimal shape control system can significantly reduce the assembly time with improved dimensional quality. (This research has obtained recognition in academia. The relevant research project has won three best paper awards.)
- Obtain the simulation platform development of composite fuselage assembly, and computer model calibration
- Understand a new technique “automatic optimal shape control of composite fuselage,” which can improve the assembly quality and reduce the flow time
- Know more about predictive modeling and uncertainty quantification in the composite manufacturing and assembly process
Why Is It Important?
Composite materials have been widely used in Aerospace and Defence (AeroDef) industry due to high strength-to-weight ratio, high stiffness-to-weight ratio, potentially long life and low life-cycle cost. As an example, a Boeing 787 aircraft has major structural parts made of composite materials and the composite parts represent more than 50% by weight. Due to multiple suppliers and multiple manufacturing batches, dimensional variability of composite parts inevitably exists when the composite parts are assembled. Significant dimensional issues have been discovered when two composite fuselages are assembled. The major AeroDef companies understand the properties of conventional materials such as aluminum and titanium after decades of development. But for assembly of composite parts, it is extremely challenging due to the highly nonlinear anisotropic properties and large manufacturing uncertainties. For this common and challenging problem in AeroDef manufacturing domain, we have developed physics-based computational modeling and analysis that can compress the timeline needed to understand composite properties, achieve ultra-high precision predictive assembly, shape control, and effective variation reduction.