What is Industry 4.0, and how does it apply to aviation, especially in its hugely complicated manufacturing and supply chain? Here’s our take – summed up in the latest of our ab initio primers.
‘Characterised by increasing automation and the employment of smart machines and smart factories, informed data helps to produce goods more efficiently and productively across the value chain,’ explains IBM, a company at the heart of the agenda, explains. ‘Flexibility is improved so that manufacturers can better meet customer demands using mass customisation — ultimately seeking to achieve efficiency with, in many cases, a lot size of one.’
In commercial aviation manufacturing, where airlines request substantial customisation of their aircraft for operational requirements and to differentiate their product, the opportunities are particularly ripe.
Aviation is already engaging with the technologies, processes and ways of working around Industry 4.0. These are all intrinsically interlinked, and include (alphabetically):
- Additive manufacturing and 3D printing
- Artificial intelligence and machine learning
- Augmented, virtual and mixed reality, including the virtual factory
- Autonomy, robotics and cobotics
- Big data and analytics
- Cloud computing
- Digital twinning
- Horizontal and vertical integration
- Information security and cybersecurity
- Process and product simulation
We’ll come back to many of these in later articles, but here’s a thumbnail guide to the current thinking in each of them.
Additive manufacturing and 3D printing
In many ways AM seems like a natural fit for aviation, an industry with hugely complex machinery, parts sourcing and stock locations. In the 2010s, the industry began commercialising this technology, including with engine fuel nozzles for the LEAP-1A and GE9X engines.
A significant next step will be for on-demand distributed parts production, where an aircraft going tech at an outstation — and a key part being printed on location and installed onto the aircraft, perhaps with the assistance of augmented or virtual reality support from experts helping local technicians.
Artificial intelligence and machine learning
The ability of Artificial Intelligence to process massive quantities of data, streamline processes, improve procedures and continuously improve via machine learning offers game-changing opportunities for aviation manufacturing and the rest of the industry.
AI is multi-faceted, and already in place across key niche areas in the industry: flight search, recommendation engines, facial and image recognition, border and security processing, passenger experience chatbots, and airport flow simulation.
Beyond the technology, though, implementing it must be trustworthy, ethical and human-centric — as detailed in EASA’s 2020 report, the Artificial Intelligence Roadmap [PDF].
The Ethics Guidelines for Trustworthy Artificial Intelligence from the European Commission High-Level Expert Group on AI, which included input from the aviation industry, highlight seven key requirements in this space:
- Human agency and oversight
- Technical robustness and safety
- Privacy and data governance
- Transparency
- Diversity, non-discrimination and fairness
- Societal and environmental wellbeing
- Accountability
As aviation — an industry highly regulated across hundreds of individual and collective governmental geographies, many with competing priorities and requirements — engages with AI, it will need to make progress in a prudent, carefully managed, and thoughtful fashion.
Augmented, virtual and mixed reality, including the virtual factory
The primary use case for AR and VR so far has revolved around training — whether that’s for MRO, safety and inspection, flight deck or cabin crew.
While the technology was somewhat tainted by the arrival of ‘product without a solution’ of Google Glass, more recent innovations like Microsoft’s Hololens are already being adopted by companies like Lockheed Martin to make production more efficient and accurate.
Lockheed Martin creates magic with HoloLens 2:
Virtual factories, too, are moving towards actual reality, with Altran — now part of digital transformation powerhouse Capgemini — demonstrating real-world options. The advent of remote working and far less travel in recent times have only accelerated this trend.
Autonomy, robotics and cobotics
Delegating functions to autonomous machines and creating independent or assistive technologies for specific tasks, is a huge opportunity for aviation. Get strides in robotics and cobotics are already being made, with wider commercialisation next on the agenda.
Combined with digital twinning, this is yet another area in which COVID-19 has accelerated existing initiatives in other industries, including highly regulated ones like medical equipment supply.
Big data and analytics
It’s no surprise that big data is massively important to aviation especially as the new generations of aircraft have more sensors in more places than ever before.
Analysing this data at the scale it comes in can only be done in an automated way, but if successful the benefits include airframe and engine more efficient maintenance, trend-based failure prediction — and, ultimately, fewer aircraft on ground, better customer and crew experience, and more utilisation hours.
Cloud computing
Moving online operations — including servers — to cloud computing and as-a-Service models, is at the heart of digital transformation at many airlines.
Not only does a substantial part of non-core work become someone else’s SLA-defined problem, but the very nature of cloud-based provision means that the industry can become more agile with new offerings and technologies.
Digital twinning
Rolls-Royce, one of the aviation companies at the forefront of digital twinning, defines them as ‘virtual replicas of physical devices, products or entities created by combining data with machine learning and software analytics to create digital models that update and change alongside their real-life counterparts. For Rolls-Royce this means creating virtual copies of our pioneering aero engines.’
Combining this part of the toolkit with big data, analytics, AI and simulation, digital twinning enables companies to predict how their products will behave and model a wide range of potential scenarios, helping them to reduce failures, increase efficiency and reduce costs.
Horizontal and vertical integration
The recent history of aviation’s supply chain is one of integration — whether that is peer and complementary companies using mergers and acquisitions to integrate horizontally, or manufacturers buying out key sections of their supply chain to integrate vertically.
Just this year, Airbus announced it was reintegrating the aerostructures business of Stelia and Premium Aerotec, the businesses IT spun off as subsidiaries in 2007–8.
Interestingly a McKinsey structured survey of executives from fifteen major European OEMs and suppliers notes that ‘aerospace executives expect increased vertical integration of the supply chain and see the related matters of material and staff availability as challenges to the industry’s ability to meet the growing demand.’
The benefits of being able to control an increasingly complicated value stream, both for planning and for resilience, have been illuminated only too sharply by COVID-19.
Information security and cybersecurity
If the hallmark of Industry 4.0 is connectivity, then security is paramount — in terms of both the security of the huge volumes of often sensitive information and of how a system’s cybersecurity gathers, stores and processes it all.
Cybersecurity strategies and guidance from the International Civil Aviation Organisation and the International Air Transport Association both underline the importance of getting these fundamental protocols correct.
Process and product simulation
Tools like virtual prototyping and process design — to create process and product simulation — can bring reduced-cost, improved-efficiency manufacturing.
Deloitte, which implemented its AWS cloud-based Smart Factory Fabric solution for Spirit AeroSystems, highlights that these tools ‘bring aircraft producers more process flexibility, such as reduced changeover times and modular automated workflows: dynamic planning practices allow production schedules and process simulation, in order to better adapt to demand fluctuations,’ citing changes in model and customisation as key benefits.
To explore these topics further why not log into yocova.com — and perhaps collaborate with fellow members of our online community to discover and share additional insights and knowledge.
Author: John Walton
Published 17th March 2022
;
