Airlines are back on a steep growth track after the slump of the 2020 and 2021 corona years. Just recently, Lufthansa put some of its decommissioned A380s back into service.
The demand for aircraft is unbroken, the construction of new machines is booming, driven in part by the sharp rise in fuel prices, as modern machines are very energy efficient and therefore also CO2 efficient. Existing airplanes must be used as efficiently as possible. Historic data on passengers' booking behavior, operating data from the aircraft, but also weather data help in this process. Flight routes can be optimized based on the weather data and the type of aircraft used is adapted to the expected bookings in terms of seats.
Predictive maintenance - i.e. maintenance based on the condition of the equipment rather than at fixed intervals - can allow maintenance work to be flexibly adapted to the flight schedule in such a way that as few interruptions as possible are necessary.
The basis for this development is data and innovation: in order to be able to introduce automation to the production process for the relatively small quantities in the aircraft industry, we need intelligent solutions.  And condition-based maintenance can only function with very up-to-date data from ongoing operation: Industry 4.0 in the air, so to speak!
 

Opportunities for value creation from data and process automation in the aviation industry

Data-centric technologies can be applied to all stages of the product lifecycle in aviation:

• In defining new aircraft models based on previous usage data and the extrapolated forecasts about the further development of routes, flight profile and utilization. 
  Utilization models based on large hubs require a mix of small and large machines, while many direct routes require medium-size machines for more efficient use. Specific airports could be more selectively used with adapted aircraft types, for example London City, which has a very short runway but is popular with many lucrative business customers.
• In development and design, the continuity of data is the basis for efficient processes.
  Simulation plays a very important role in aerospace development - not only in the field of aerodynamics, but also for the functional verification of the many highly complex systems or for calculating the expected fuel consumption.
• One major area of aircraft development is the continuous optimization of existing series. 
  Because investments and risks of a new development are enormous, it often makes more sense e.g. to equip an existing series with a new engine or aerodynamic improvements, instead of developing a completely new aircraft type. Simulation is the key to efficient modernization in this context as well. 
• Equally important is the integrated development of structure (e.g. fuselage and wing), systems (equipment and functions including electronics and software) and electrics (Electrical Wiring Interconnect System - EWIS). The efficiency of a machine in operation depends crucially on its weight, payload, engines, range, reliability, operating costs, etc. being optimally balanced and matched to market requirements. 
• In operation, continuous monitoring of many machine parameters is the basis for scheduling maintenance work. It can often be worthwhile to carry out part of the maintenance as a precaution, if e.g. spare parts or maintenance resources are currently available on site and there is enough time for the maintenance. The prescribed fixed maintenance intervals, on the other hand, can be utilized to the maximum if the exact condition of all components is known. Process automation in service makes it possible to optimize such issues with the help of artificial intelligence, for example. 

Data and 3D models become the basis for the development, construction and operation of all types of aircraft. Automated data streams ensure that information always ends up in the right place, where it can be used efficiently.

Model-based work: Faster to product maturity

In order to meet the requirements of modern aircraft, all disciplines involved must work together in an integrated manner right from the development and product definition stages. If changes have to be made in later process steps, e.g. to create more space for systems during mechanical design, this means high additional costs and time delays.

A model-based approach, in which all process participants work based on the integration of models, is essential in this regard. Only if each discipline has information about the other teams' developments can the final result be of one piece. Just as in 3D Digital Mockup (DMU) geometric models enable the integration of parts, models of subsystems and components can be linked together to evaluate, simulate and optimize the overall system.  In aviation, for example, the flight simulator for training pilots is a byproduct of system development for flight control.

Opportunities to automate the flow of data along the process 

Each new aircraft is unique because each airline has its own color schemes, the cabin is equipped differently, or other minor variations and custom requests are specified. Transferring these extensive customer specifications into a supplier specification is one of the many processes that still requires a lot of manual work today. Process automation can therefore add value here.
Reusing partial solutions, such as certain branches of the wiring harness, is another way to use information technology processes to become more efficient, shorten lead time, avoid errors, and reduce the workload for employees.

More than the sum of its parts: Integration of different systems

Model-based engineering and systems engineering allow the functions of a system or product to be initially developed independently of how they are later implemented – whether e.g. an actuator is operated hydraulically or electrically, whether it is centrally controlled or fed commands with its own intelligence via a data bus, is initially irrelevant when it comes to developing the functional architecture.
Later in the process, final decisions on implementation are made as part of the design space exploration – but the overall information situation is then much better than at the beginning and decisions can be made on a sound basis.
In today's world, where fly-by-wire is state of the art, the linking of mechanical and electronic systems plus control software has advanced to such an extent that it is downright absurd to consider the disciplines separately. The development environment must enable this integration and provide data support in a way that the information is available everywhere and, above all, in the correct format. In other words, what is a valve symbol in the hydraulic plan for the hydraulic designer must be available as a 3D model of the valve for the mechanical designer and as a parametric component model for the hydraulic valve in the simulation, in order to simulate pressure drops and noise development, for example.

Software-driven data analysis: Maximizing value creation in aviation

Data analysis can help save a lot of money and time. It allows data from each flight test to be recorded so that later, when a new flight test is scheduled to evaluate a particular flight situation, it can be checked to see if that flight situation has been flown before. This saves on test flights and eliminates the need to wait for data; you can use historically recorded test data immediately.

Digitization is based on data. This data helps to optimize processes and generate real added value. All of this helps in the end to create an attractive and optimal product.