2.1 System design tools

Systems thinking is the concept of handling all the subsystems of a defined system at once. The tools that have been used for engineering are the subsystems mainly dealing with only parameters or any aspects. Such as, computational fluid dynamics (CFD) provides insight into flow or aerodynamic aspects. On the other hand, systems thinking needs further tools that could help to see all interactions of all subsystems in all physical aspects. Such as, aerodynamic flow will cause thermal changes, which at the end may cause contraction/expansion of all the structures, which can lead to cyclic interactions.

2.2 Failures due to ignoring systems thinking

To understand how critical systems thinking is in every aspect of daily life, a look at historical events can be quite illuminating. This study looked at the potential consequences of neglecting or not sufficiently implementing systems thinking, focusing on the serious events that occur in different time periods. Historically, many tragic events, from the BP Deepwater Horizon Oil Spill to the Space Shuttle Challenger Disaster and the Hindenburg Disaster, have been associated with a lack or neglect of systems thought. These events highlight the importance of systems thinking and show how vital a more holistic approach is to prevent similar disasters in the future.

1. Case 1: BP Deepwater Horizon Oil Spill: BP’s Deepwater Horizon oil platform exploded, and the platform sank. As a result, one of the largest oil spills in history occurred in the Gulf of Mexico [Reference Borunda11].

   Analysis: The neglect of systems thinking in this case can be considered as ignoring technical problems and inadequacy of safety measures on the platform and not considering the whole system holistically. The root causes behind the explosion and leakage on the platform are attributed to many parameters, not just a single component. By applying systems thinking, how each factor interacts with each other could have been modeled and understood in advance, and measures could have been taken to prevent such an accident [Reference Makocha, Ete and Saini34].

2. Case 2: Space Shuttle Challenger Disaster: A leak in the shuttle’s fuel tank during the launch of NASA’s Challenger space shuttle caused an explosion at the end of the Earth’s return phase, killing seven astronauts [22].

   Analysis: The main reason behind the Challenger disaster is that weaknesses in the structural design of the shuttle and warnings about the O-ring seals becoming dysfunctional at low temperatures were not considered. As shown in Fig. 3, the failure to fully understand the interactions between the different parts and the lack of a holistic approach to the problem can be seen as one of the reasons for the disaster [22].

3. Case 3: Hindenburg Airship Disaster: The Hindenburg airship, which ran from Germany to New Jersey, was burned as it landed at the airport in Lakehurst, New Jersey. The reason for this tragic event was the use of hydrogen gas in an airship with inadequate safety measures [23].

   Analysis: The Hindenburg airship disaster was caused by the use of hydrogen gas in an airship with inadequate safety measures. The design of the airship and the choice of fuel are preferred without being based on a method of systems thinking that fully assesses the hazards. Safer fuel options and better safety measures were ignored or not adequately investigated [23].

Figure 3.

The causal-loop of the Challenger disaster (AI is partly used to form the diagram).

The examples listed show that neglecting systems thinking or not applying it sufficiently can lead to serious consequences. The importance of systems thinking can be observed through historical events and experiences as well as the examples given.

3.1 Evolution of aircraft design

Initially, aircraft design relied on trial-and-error methodologies to demonstrate the feasibility of flight. For the flight to take place, the plane had to be lightweight, and a wooden structure was used for this purpose. After adopting the metal body structure, aerodynamic-based calculations began to be used to build the aircraft. Thus, engineering methods were incorporated into the design phases of the technically focused design process. The need for long-range and high-altitude became evident with the emphasis on operations. The 1973 oil crisis prompted a transition to a cost-centric strategy aimed at the civilian market, emphasising fulfilling customer needs. Subsequently, technical advances heightened the demand for rapid competition. Consequently, the production of a rapid product has emerged as a critical criterion in the aircraft design process for civil aviation. The design process transitioned to a digital environment through digitalisation, utilising computer-aided design systems for aircraft modeling. This expedited the evaluation of designs, enhanced efficiency and performance, and facilitated optimisation. Nowadays, systems across several disciplines are integrated as a cohesive unit, with an emphasis on the functionality of the system.

The assessment of the focus of engineering studies can be summarised by year as follows:

1. Material oriented (1900–1945)

2. Technically oriented (1945–1960)

3. Operation oriented (1960–1975)

4. Maintenance and cost oriented (1975–1985)

5. Digitalisation (1985–2000)

6. Integrated function-oriented (2000-)

3.2 Early design efforts

In the early stages of large passenger aircraft design and production, companies have a design organisation focused on competency groups. In this organisation, the design team makes its design and transfers it to the production unit. There is a structure where the production team transfers the aircraft to the sales/marketing unit.

In the conventional functional-oriented system approach method, the aircraft design process is organised vertically as shown in Fig. 4. These processes are independent; only the results are carried to the next stage.

Figure 4.

Process-oriented system approach [Reference Grose28].

Safety requirements and certification are considered a fundamental element of aircraft design. Aircraft must comply with high safety and certification standards. This means ensuring the aircraft can fly safely, handle emergencies and ensure all passengers are safe. Security is always a priority throughout the design process [Reference Zipay, Modlin and Larsen63].

3.3 Function-oriented design

In a study conducted by Boeing in 1994 [Reference Grose28], aircraft development processes were analysed, and a more customer-oriented structure was envisaged in which integration activities started at an earlier stage. Basically, the structure is based on the simultaneous focus of the integration process and the structural production of the aircraft. The proposed system-oriented design approach structure is illustrated in Fig. 5. Interestingly, although a function-oriented structure was envisaged for the systems-oriented approach in the same report, the approach proposed in Fig. 5 is still being used by two companies producing large-scale civil passenger aircraft. This approach is based on the flow of information rather than the flow of tasks between units. It is important to note that at the time this second approach entered new and intensive use of computing technologies in the years it was put forward, it is necessary to take into account the use of software on airplanes, as well as the use of software products in design processes [Reference Raj46].

Figure 5.

Function-oriented system approach [Reference Grose28].

Detection of possible problems in unit and functionality-oriented design approaches, production and/or integration stages is not possible at the preliminary design stage. In this approach, problems usually arise during the detailed design phase, and this period may even extend until the production line and customer feedback. This leads to costs arising from change management during the detailed design phase, as well as a lack of customer satisfaction.

In both above-mentioned approaches, it has been observed that the team performing the preliminary design does not have data on the production process, it is not possible to access the production cost parameters, there is a need to go back to the design stage during production, and high production costs are encountered. This includes the possibility of unnoticed problems until the customer returns, both the negative impact of the production-sales channel and the cost and calendar pressure on the whole process of returning to the detailed design, especially in the civilian aircraft market, it should be expected to be high. Returns and revisions, in addition to negatively affecting the project cost, cause time pressure on the project team and often the failure to provide the committed values to the customer. For example, during the preliminary design phase of the A400M aircraft, the 32-ton payload target committed to customer countries could not be met due to the functional focus of the design [Reference López Díez and Asenjo Tornell33].

When evaluating design approaches, aircraft performance, as well as another important issue for companies, is that costs are kept under control at every phase of the project. For the reasons mentioned above, the fact that unforeseen changes of requirements may arise in the project is an important obstacle in predicting project costs. It should also be considered that customers need an approach or tool to obtain data on project duration, cost of ownership and product reliability during the early design phases.

3.4 Digitalisation and integrated function-oriented design

Almost all of the literature dealing with the functional design approach emphasises system optimisation [Reference Grose28, Reference Raj46, Reference Wiseman, Scoggins, Michelli, Janet and Walker60]. In particular, with the increase in computing possibilities, multidisciplinary design optimisation (MDO) application techniques have been developed and have become the most important activity of aircraft engineering [Reference Alonso, LeGresley and Pereyra3, Reference Fioriti, Boggero, Corpino, Prakasha, Ciampa and Nagel25]. With the development of the idea of systems thinking, it was understood that system design is not only optimisation, but it was also concluded that the system should be developed integrally. Systems thinking is the preferred effective method for modeling systems, identifying parameters, complex factors, elements and their relationships, as well as providing an analytical understanding of systems. Systems thinking not only optimises problems and the connections between them, but also creates a system that can integrate new knowledge and strategies [Reference Claeys and Minati17]. Digitalisation provides uncertainty reduction and decision support in aircraft design efforts [Reference Longueville, Jézégou, Bénard and Gourinat32].

System optimisation refers to the strategic approach used to improve the performance of a system and minimise inefficiencies. In the light of this research, optimisation can be redefined as resizing or realignment of related components (system elements) to maximise environmental coherency and performance. This discipline aims to provide improvements in critical areas such as repeatability, reliability, consistency and accuracy by using available resources in the most effective and efficient way [Reference Dincer, Rosen and Ahmadi18]. In addition to minimising costs, system optimisation offers an approach that focuses on long-term goals. This approach gives you the opportunity to build systems that are reliable, long-term and have low maintenance requirements. With the ability to adapt to technological changes and needs, system optimisation also represents a continuous improvement process. In this way, systems and organisations can adapt faster to changing conditions and gain competitive advantage [Reference Dincer, Rosen and Ahmadi18].

Figure 6 shows an example of an interface where functional tests can be performed during the design phase of an aircraft.

Figure 6.

Modelling and simulation interface.

3.5 Application examples

The applications of the systems thinking approach and the gains brought by these applications are examined. In a design effort, as the design progresses, knowledge about the final system increases but the flexibility in the design reduces. The systems thinking helps to increase knowledge well before the detailed design to give enough room to have innovative design flexibility at the earlier stages of the project. This can be achieved by using systems thinking tools, which gives the ability to see systems performances before system integration phase [Reference Verhagen, Bermell-Garcia, Van Dijk and Curran55]. Some examples related to these advantages are summarised as follows.

In one of the research projects, the authors suggest combining traditional methods with the systems thinking of digital twin (DT) technology to save time and cost problems to the complexity experienced in the aircraft design process. For this purpose, a cargo plane was created with an example of a simulation that included climbing, cruising and landing missions. The data obtained in the flight simulation performed at a maximum of 18,000 feet were compatible with FCOM data. Thus, it has been shown that the necessary tests and changes can be followed in the digital environment without the need for physical prototype [Reference Nacak, Yildiz and Zöldy40].

In order to model and dynamically simulate an individual combat quadrotor unmanned aerial vehicle (UAV), the UAV was designed using the digital twin-based ROS (robot operating system) and Gazebo simulator. A large database was created, including historical flight data, real-time sensor data of the physical system, system data and simulation data obtained with the digital twin. Using connectors, these data obtained from the physical and twin models were integrated with the control system containing the system objectives and the system was simulated. The physical system and the digital twin were analysed interactively, and an experimental setup was set up to compare the results. As a result, it was concluded that the digital twin method is consistent in basic flight missions but needs to be improved as it is more stable than the physical system [Reference Ji, Hao, Gao and Lu30].

In another study, a battlefield and an aircraft were modeled for use in combat training using the digital twin method. The study includes the creation of a 3D model of the battlefield, processing of environmental conditions, development of a data flow system, aircraft modeling and examination of different scenarios. 3D reconstruction programmes such as simultaneous mapping were used for modeling. The fighter jet was studied in two modes: driving mode, where flight data information is used directly, and correction mode, which processes real flight data into the system as correction, and it was observed that it could be a good training tool for pilots [Reference Hu, Zhang and Ma29].

The digital twin method is used to analyse large systems involving different disciplines as well as specific components. For example, Paternina-Verona et al. modeled the filling procedure of a pipeline with an irregular profile using the numerical twin method. CFD analysis of the model was performed to investigate the air oscillation dynamics, and the results agreed with the simultaneous experimental data. Thus, it is observed that it increases the efficiency and safety of the systems compared to standard modeling methods [Reference Paternina-Verona, Coronado-Hernández, Pérez-Sánchez and Ramos44].

In another study, it was used in the controller design and simulation studies of a four-engine VTOL aircraft. Pitch, roll, yaw and thrust control movements are used to determine the block parameters. The input voltage of the engine is changed, and the angular position of the load is adjusted, and it keeps track of the actual position information, allowing it to reach the targeted position. It has been seen that the system control algorithm can be improved while still in the sub-system design. It is concluded that it will be possible to direct the UAV to the desired position without the need for GPS or internet connection [Reference Gökçe, Yıldız, Kale-Halasz and Zöldy27].

Since multiphysics modeling functionally allows the evaluation of functional performance during the design phase, it is seen that it will provide significant time and cost savings by allowing the trial and error and integration process on the prototype to be included in the design phase [Reference Nacak39].

3.6 Disadvantages of systems thinking in aircraft design

The systems thinking approach has many advantages, as well as some disadvantages and restrictions in its development and implementation.

• • The necessity to analyse components from different fields (aerodynamics, avionics, propulsion, etc.) within a unified framework may result in complexity. Furthermore, this collaboration across disciplines requires experts to understand the entire system, which can lead to the need for highly trained experts. To prevent this situation, an infrastructure can be created through experimental learning from simple to complex systems and standardisation of systems thought approach and results can be ensured. Thus, an appropriate training and orientation can be provided for the new experts [Reference Beasley9].

• • There may not be enough time to model complex systems and analyse them under different conditions and/or may not be able to respond quickly during a real-time operation [Reference Adamenko, Kunnen, Pluhnau, Loibl and Nagarajah1]. For this, predefined decision scenarios can be implemented, or it can be programmed to prioritise emergency alerts when processing decision mechanisms.

• • In organisations, especially successful companies, there can be a resistance to change. Instead of completely replacing existing applications, a gradual change process may need to be undertaken as an addition to systems engineering.

Despite the disadvantages mentioned, a functional simulation system can be developed that will provide many advantages in design processes with the development of data processing, interdisciplinary information and collaboration management and modeling process.