## 3 Results: Method Development, Implementation, and Testing of CADA Framework
### Method Development
#### 3.1.3 Axiomatic Design (AD)  
AD supports iterative thinking and separation between requirements and physical solutions. Systematic Design is made possible by enforcing the process of clearly specifying FR from the weaker formulation of pure user requirements. Engineers tend to build solutions directly from user requirements and thus miss out on the step of working on the functional requirements and their interdependencies [61].  
In contrast to other methodologies, AD provides an easy-to-use, streamlined design workflow that can be used independently of the number of available concepts. It also comes with a graphical evaluation and decision-making tool. These properties led us to implement AD techniques into our proposed tool.  
The theoretical basis of AD to create a good design are the following Axioms:  
1. Independence Axiom: maintain the independence of the functional requirements.
2. Information Axiom: minimize the information content.  
The design process is carried out iteratively through the \"zigzagging\" process between the FR and DP. This method creates a table (Design Matrix, see Figure 5) that offers the possibility of evaluating the design concept. In the best case, the Design is \"uncoupled\", meaning there are only one-on-one relationships between FR and DP, which results in a diagonal matrix. Also acceptable is the \"decoupled\" scenario where the design matrix is triangular. Design concepts that are \"coupled\" indicate non-acceptable solutions. This can result from situations where not all FR are connected to at least one DP or a violation of the Independence Axiom [28; 30].  
Figure 4: CBR working principle.  
Figure 5: AD Matrix: (**a**) Uncoupled Design; (**b**) Decoupled Design; (**c**) Coupled Design.  
If viable solutions exist, AD supports the decision-making process through the Information Axiom, which states that the best solution is the one that needs the least information to be described. Following this concept, designers strive for simplicity. This principle has the potential to be cost-effective and quality-relevant at the same time [28]. The definition of AD elements (CR, FR, DP, and PV) is very weak to keep it open for various design problems. In other words, a DP can be a system, equipment, function, or variable. This comes with the need for a clear definition available to all designers involved in the solution-finding process. A clear abstraction guideline that keeps the layer definition (what is the definition of a System, Equipment,...) is thus interchangeable information throughout different design problems and stakeholders [31]. Such a definition is crucial to support the reuse of knowledge in the context of Ontology and Epistemology. To incorporate previously designed solutions for similar problems into a new design process is an overall performance improvement of the design process. The same reasons apply to the support of data-driven design [43].  
Our proposed method takes care of this, as the definition of the data objects in the underlying dataset is described in cases following the GE method of CBR.