Manufacturing Trends and Technology in the Aerospace and Defence Industry
Published on : Monday 05-07-2021
A&D OEMs will develop the smart factories of the future that will be run by AI, the digital twin, and intelligent production systems, says Dick Slansky.
Overview 2020 was a rough year for the commercial aircraft industry, with the Covid19 pandemic wreaking havoc on travel and the global airline industry. Airlines are the lifeblood of the aviation market. When airlines succeed and prosper, the rest of the commercial market prospers. Conversely, when airlines struggle, the entire market struggles from aircraft OEMs and the global supply chain that supports them, to service, maintenance, and MRO. The nearly complete shutdown of air travel during 2020 was devastating to the travel business and caused severe curtailments of production for aircraft OEMs, where a record backlog of orders went to practically nothing overnight as airlines shut down and stopped taking any new aircraft deliveries.
This dilemma not only affected US aircraft manufacturer, Boeing, but its primary competitor, Airbus, in the global commercial aircraft duopoly. The situation was very serious for both, as each faced its own liquidity crisis as aircraft deliveries dried up and their respective production lines were significantly curtailed. Moreover, the extended global supply chain for both aircraft manufacturers was likewise seriously affected, and some suppliers went out of business altogether.
Today, the crisis has alleviated, with travel restrictions easing, and many carriers resuming several pre-pandemic routes. But it will take time to crank up manufacturing production lines and get the labour force back in place.
Additionally, the carriers will have to start taking deliveries of new aircraft to provide revenue for Boeing and Airbus, and we can expect this to be tentative at first as the carriers recover their losses, assess their own revenue streams, and get back up to speed.
What will help the aircraft manufacturing OEMs get their production lines humming again will be the adoption of new manufacturing technologies that have emerged from Industrial IoT, Manufacturing 4.0, and the wave of ongoing digital transformation across the entire design/build/operate/ maintain product lifecycle of airframe manufacturing.
Next generation intelligent automation along with the implementation of cognitive manufacturing powered by AI, advanced analytics, and digital twin implementation will optimise production processes, cut costs, and help A&D manufacturers reach pre-pandemic delivery rates faster and more efficiently. The emergence of material science is also spawning a range of new materials, along with additive manufacturing, and human/robot collaboration that will significantly change the face of aircraft manufacturing.
Leveraging emerging technologies
The A&D industry has a history of early adoption of disruptive technologies to advance both product development and manufacturing processes. There are currently several key technologies that the industry is using to meet new manufacturing challenges and deal with the pre-pandemic order backlog of aircraft. These technologies include additive manufacturing, advanced composite manufacturing methods, implementation of the digital twin, cognitive manufacturing and advanced analytics, robot/worker collaboration, and AI/ML, all of which are permeating many areas of the production process.
Both Boeing and Airbus continued to build at very high rates into the pandemic-induced downturn and the Boeing 737 Max grounding. Supply chain suppliers were also still producing at peak or close to peak rates. Conversely, 30 to 40 percent of the global carriers’ fleets remain on the ground. The result is that OEMs have a considerable number of aircraft that remain undelivered and parked on the tarmacs.
While airlines are beginning to open many of their routes and resume service as the public begins to fly again, the number of travellers remains well below pre-pandemic rates. Things will begin to improve in 2022 when the flying public is expected to resume travel and the carriers work back to full fleet capacity. But the reality is that for the short term the carriers will not be accepting very many new aircraft orders into their already underutilised fleets. In the meantime, aircraft OEMs need to leverage manufacturing technologies that significantly improve production efficiency, smarter automation, new materials, and better utilisation of the workforce.
The emerging role of AI
Top technology investment areas for aerospace manufacturing include advanced analytics, cloud computing, modelling and simulation, IoT platforms, optimisation of production processes, and predictive analytics. AI and subsets of AI like machine learning (ML) will drive much of this technology in actual implementation.
Earlier research into AI and cognitive computing has resulted in real solutions being applied to real-world processes. In addition to robotics, additive manufacturing, and other disruptive technologies, the A&D industries were relatively quick to recognise the potential of AI and readily embraced the science and technology it has spawned. Both industries have developed and implemented their respective roadmaps for digital transformation.
Automated systems have historically been an important element of the A&D industry from the cockpit to the factory floor. We’ve seen a steady progression from the first use of autopilots and other automated systems toward future autonomous avionics systems. Automated factory production systems have evolved from programmed control systems to machines and production systems based on predictive, prescriptive, and even autonomous self-healing systems enabled by AI/ML algorithms.
In the factory production areas, ML is helping to improve and optimise the production process in several ways. These include reduced occurrence of equipment failures to keep the production rate humming and reduce expensive downtime. ML-based algorithms can access and analyse very large volumes of data from vibration sensors in machines to detect and predict machine anomalies and failures. Moreover, ML can be prescriptive to determine how to best fix and prevent problems. Ultimately, ML algorithms can orchestrate a complete self-healing autonomous production environment of machines and assembly lines.
AI and ML are being used to determine the optimal production processes in aerospace manufacturing. Prescriptive analytics combine big data, mathematical statistics, logic, and ML to reveal the origins of the most complex production problems empirically and then suggest decision options to solve them. ML-based production intelligence systems use pattern recognition technology to analyse existing production data for both product and process and identify patterns of what works (best practices) and what does not (risk situations). These patterns are translated into a form of human-readable rules that are then applied to manufacturing operations for best practices. Aerospace manufacturers are using this method to optimise advanced composite manufacturing processes.
The rise of additive manufacturing
Today, the A&D industry is the largest user of additive manufacturing (AM) produced parts. From the commercial duopoly of Boeing and Airbus to defence OEMs like Lockheed Martin, thousands of AM “fly away” parts are used in the manufacturing of aircraft. For example, Boeing’s latest wide body model, the 777X, has over 600 printed parts in the aircraft, with over 300 printed parts in the huge GE9X engines, billed as the most powerful and efficient engines for a twinjet wide body aircraft today. The Boeing 777X is competing with the Airbus A350 XWB, in terms of size, performance, and number of AM parts. The A350 already features over 1,000 printed parts.
Boeing has made a major push into AM and has filed for patents related to the 3D printing of replacement aircraft parts, which could have serious implications to the company’s operations going forward. They want to create a parts library to store AM part definition files, including a database and a parts management system instead of storing parts at their various distribution hubs, or requiring parts to be shipped to them, causing extensive delays.
Instead, the company can just pull up a specific AM file for a part that is needed, and have it fabricated within minutes or hours wherever they have a printer available. Currently, the company has over 350 AM standard parts spanning 10 different aircraft production programs with around 20,000 printed parts currently being used on their aircraft.
The other area of A&D manufacturing where AM is making a significant impact is in the tooling used to support production line assembly and installation. Using a new generation of big area additive manufacturing (BAAM) printers, large tooling fixtures and jigs can be fabricated as single large parts in reduced time and eliminating multiple parts assemblies.
Currently, AI is an integral part of the design process for AM in aerospace. In designing parts for aircraft, achieving the optimal weight-to-strength ratio is a primary objective, since reducing weight is an important factor in airframe structures design. Today’s PLM solutions offer function-driven generative design using AI-based algorithms to capture the functional specifications and generate and validate conceptual shapes best suited for AM fabrication. Using this generative functional design method produces the optimal lightweight design within the functional specifications.
Digital twin and new materials
Implementation of the digital twin will be important to maintain constant production process improvement and optimisation to streamline production operations and increase production rates. The application of advanced analytics to speed up production efficiency will be essential for A&D OEMs to meet the significant backlog of aircraft orders. Digital twins will also be critical to ramp up production lines that have slowed or shut down due to the pandemic.
The use of advanced composite materials is becoming the standard manufacturing process for aircraft structures for a large percentage of the overall aircraft, including body, wings, and empennage. The use of advanced composite materials along with advances in generative design and large-scale AM fabrication will allow structures designers to design and build a new generation of very lightweight and stronger airframes based on bio-structure and lattice configuration that would be impossible to fabricate with standard fabrication and assembly processes.
Recommendations
Clearly, the A&D industry is coping with some serious challenges in terms of business and manufacturing in a global pandemic environment. As airlines begin to resume the business of aviation transportation, updating their aging fleets, and taking delivery of new aircraft, A&D OEMs will again ramp up their production lines. As serious as the curtailment of production has been to A&D manufacturers, this unanticipated pause in normal operations will afford them the opportunity to make significant upgrades and improvements to their manufacturing processes by implementing emerging technologies in many areas.
The A&D industry will once again lead in the adoption of emerging technologies in both the design of next generation aircraft and in advanced manufacturing processes. A&D OEMs will develop the smart factories of the future that will be run by AI, the digital twin, and intelligent production systems.
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Dick Slansky is Senior Analyst, PLM & Engineering Design Tools, ARC Advisory Group, Boston, USA. Dick's responsibilities at ARC include directing the research and consulting in the areas of PLM (CAD/CAM/CAE), engineering design tools for both discrete and process industries, Industrial IoT, Advanced Analytics for Production Systems, Digital Twin, Virtual Simulation for Product and Production.
Dick brings over 30 years of direct experience in the areas of manufacturing engineering, engineering design tools (CAD/CAM/CAE), N/C programming, controls systems integration, automated assembly systems, embedded systems, software development, and technical project management. Dick provides technical consulting services for discrete manufacturing end users in the aerospace, automotive and other industrial verticals. Additionally, he focuses on engineering design tools for process, energy, and infrastructure.
