This paper presents an investigation of the structural performance of a 3D-printed Polylactic Acid (PLA) wing rib structure that is integrated with Internet of Things (IoT) sensory capabilities for application in an Industry 4.0 ecosystem. Both finite element analysis and experimental testing were employed to assess the strain distribution in the structure under various loading conditions and testing setups. The Taguchi approach was utilized to identify the physical factors and their interactions that have a significant impact on the strain distribution in the structure. The findings indicate that the bending load versus strain curve is highly influenced by the applied load position and wing rib cut-out locations, while the structural performance is also highly dependent on torsion. The incorporation of sensory locations with covers improved the component’s ability to withstand traction load and resulted in a 61% reduction in corresponding strain. The most significant factor during bending tests was identified as the applied load, along with the interactions between the load location and crosshead speed of the testing machine.
Aluminium alloys (AA) are ubiquitous materials in manufacturing used in powder bed fusion (PBF) processes due to light weight, high strength and corrosion resistance. Current research focuses on other materials whilst additively manufactured AA 7050 remains unexplored. This paper examines the formability of AA 7050-T7451 powder for the Selective Laser Melting (SLM) process. To define this material in Simufact AdditiveTM the creep behaviour required flow curves obtained by writing a MATLAB® script to calculate the true stress–strain behaviour depending on strain rate and temperature. The results of the mechanical calibration for aluminium alloy are presented to obtain its inherent strains.
Graphical abstract
The process of metal additive manufacturing (AM) is now widely used in fabricating complex parts in today’s industry. The scope of this paper is to redesign a manufacturing process for complex aircraft components using wing ribs as example by considering embedded Internet of Things (IoT) sensory capability that can be used in an Industry 4.0 ecosystem for moving away from a condition-based preventive maintenance system to a data-driven predictive maintenance-based system. This work is based on a previous study that considered the part design stage which deals with finding the best design solution for a single part. Considering a wing rib geometry of 3-mm web thickness with 6-mm upper and lower caps, the manufacturing process is designed and assessed using the Simufact Additive™ software. The use of AM when embedding IoT sensors allows more flexibility without compromising the structural integrity of parts, as well as the advantage of design freedom and limited cost when modifying geometries. The outcomes show that the manufacturing process depends strongly on hot isostatic pressing (HIP) for the wing rib, but for the sensory covers it presented no significant improvement. The results also show that the support optimisation can lead to an important reduction of mass and volume as well as an improvement of the structural performance.
This paper presents a deployment of an IoT architecture in aircraft wings based on a physical asset, three IoT platforms, MATLAB® on a personal computer and ThingSpeak as a cloud. The IoT architecture was designed considering five layers and implemented using a simple wireless sensor network. Temperature, humidity, air quality and air pressure were collected, pre-processed and visualised in real-time to improve the reliability of aircraft components. The results show that embedding sensory capability into wing components can create a smart ecosystem that will support different IoT-enabled services in-flight, and it can also be used for predictive maintenance purposes.
Graphical abstract
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.