OEM : Aerospace
The National Aeronautics and Space Administration is America’s civil space program and the global leader in space exploration. The agency has a diverse workforce of just under 18,000 civil servants, and works with many more U.S. contractors, academia, and international and commercial partners to explore, discover, and expand knowledge for the benefit of humanity. With an annual budget of $23.2 billion in Fiscal Year 2021, which is less than 0.5% of the overall U.S. federal budget, NASA supports more than 312,000 jobs across the United States, generating more than $64.3 billion in total economic output (Fiscal Year 2019).
Additive for Aerospace: Welcome to the New Frontier
Gao, a tech fellow and AM technical lead at Aerojet Rocketdyne, is particularly interested in the 3D printing of heat-resistant superalloys (HRSAs) and a special group of elements known as refractory metals. The first of these enjoy broad use in gas turbines and rocket engines, but it’s the latter that offers the greatest potential for changing the speed and manner in which humans propel aircraft, spacecraft, and weaponry from Point A to Point B.
“When you print these materials, they typically become both stronger and harder than their wrought or forged equivalents,” he said. “The laser promotes the creation of a supersaturated solid solution with fantastic properties, ones that cannot be achieved otherwise. When you combine this with AM’s ability to generate shapes that were previously impossible to manufacture, it presents some very exciting possibilities for the aerospace industry.”
Eric Barnes, a fellow of advanced and additive manufacturing at Northrop Grumman, says “Northrop Grumman and its customers are now in a position to more readily adopt additive manufacturing and prepare to enter that plateau of productivity because we have spent the past few years collecting the required data and generating the statistical information needed to ensure long term use of additive manufacturing in an aeronautical environment… In the future, you may be able to eliminate NDT completely. Comprehensive build data will also serve to reduce qualification timelines, and if you’re able to understand all that’s going on inside the build chamber in real-time, machine learning and AI systems might be able to adjust process parameters such that you never have a bad part.”
Aerospace, Defense and Industry 4.0
“Designing for manufacturability, modeling the production environment, and then producing our products with a minimum of duplicated effort—this can give us the breakthroughs in speed and affordability that the A&D environment needs in a time of limited budgets and rapidly changing threats,” explains Daughters. “These technologies are an essential component to our ‘digital thread’ across the product life cycle. They give us the ability to simulate tradeoffs between capability, manufacturability, complexity, materials and cost before transitioning to the physical world.”
“In a nutshell, I4.0 involves leveraging technology to better serve the world,” says Matt Medley, industry director for A&D manufacturing at IFS, a multinational enterprise software company. “More than just collecting and processing mounds of data via sensors and the Industrial Internet of Things (IIoT), I4.0 is turning data into actionable intelligence to not only drive efficiency and grow profits, but to also help companies be good stewards of our natural resources and local communities. Aerospace and defense companies whose enterprise software can keep pace with developments like additive manufacturing, AI, digital twins, and virtual and augmented reality (V/AR) are the ones that will thrive in an increasingly digital 4.0 era.”
The Genius of 3D Printed Rockets
Evolutionary Algorithms: How Natural Selection Beats Human Design
An evolutionary algorithm, which is a subset of evolutionary computation, can be defined as a “population-based metaheuristic optimization algorithm.” These nature-inspired algorithms evolve populations of experimental solutions through numerous generations by using the basic principles of evolutionary biology such as reproduction, mutation, recombination, and selection.
Origins of the Digital Twin Concept
While the terminology has changed over time, the basic concept of the Digital Twin model has remained fairly stable from its inception in 2002. It is based on the idea that a digital informational construct about a physical system could be created as an entity on its own. This digital information would be a “twin” of the information that was embedded within the physical system itself and be linked with that physical system through the entire lifecycle of the system.
The concept of the Digital Twin dates back to a University of Michigan presentation to industry in 2002 for the formation of a Product Lifecycle Management (PLM) center. The presentation slide, as shown in Figure 3 and originated by Dr. Grieves, was simply called “Conceptual Ideal for PLM.” However, it did have all the elements of the Digital Twin: real space, virtual space, the link for data flow from real space to virtual space, the link for information flow from virtual space to real space and virtual sub-spaces.