# Design of Cognitive Assistance Systems in Manual Assembly Based on Quality Function Deployment
## 4 Conceptual Adaptation of the QFD Method
### Development of the Cognitive Assistance System-QFD (CAS-QFD) Method  
4.3.1. Analysis of the Manual Assembly Process and Identification of Requirements  
Figure 4 shows the conceptual structure of the second phase of the CAS-QFD method. In the following, the individual steps as numbered in the figure are explicitly explained. First, the requirements of the workers and the company are identified (step 1, Figure 4). These relate to the assembly process. The actual identification of the requirements can be carried out deductively or inductively in an initial step using suitable methods. The requirements identified are weighted (step 2, Figure 4), for example, by means of a pairwise comparison and ranked by relative values. The fulfillment of the requirements for the assembly process is compared with other companies in a competitive comparison (scale: \(-2\), \(-1\), \(0\), \(1\), \(2\)) (step 3, Figure 4). This contributes to defining a realistic assessment. Then, the optimization importance of the requirements is calculated (step 4, Figure 4). This is related to the specific need for action and can be calculated through following equation:  
\[o_{i}=d_{i}-c_{i} \tag{1}\]  
\(o_{i}\) is the weighted optimization importance value; \(d_{i}\) is the degree of relative importance of the worker and company requirements; \(c_{i}\) is the competitive comparison value. Now, the assembly process and the work tasks within the assembly process are defined (step 5, Figure 4). The process is modeled in advance using suitable methods (e.g., value stream mapping, precedence graph). The correct level of detail for capturing the requirements and assistance functions must be determined. In the house of quality, the interdependencies/interactions of the process elements are analyzed and the strength of the influence is defined (step 6, Figure 4). Knowledge of the interactions is important for the subsequent design of the assistance functions since the interactions of the process elements also cause the interdependencies of the assistance functions and cannot be considered isolated. Process control is graded in comparison to the competition (scale: 1 = very good to 5 = insufficient) (step 7, Figure 4). This allows the potential for optimization to be derived. The correlation between process elements and requirements is performed in  
Figure 4: Overview of the second phase of the CAS-QFD. the next step (step 8, Figure 4). For this purpose, the correlations must be identified and weighted (Table 4). This identifies the process elements that have the greatest influence on the satisfaction of workers and the company. The individual correlations (influence values) are multiplied by the optimization importance values (step 9, Figure 4). \[w_{j}=\sum_{i=1}^{n}o_{i}\cdot r_{i,j} \tag{2}\]  
\(w_{j}\) represents the value for the process importance of each manual assembly process step; \(r_{i,j}\) is the influence coefficient between the \(i_{\text{th}}\) user and company requirements and the \(j_{\text{th}}\) manual assembly process steps. In the next step, the optimization priorities of the process elements are calculated (step 10, Figure 4):  
\[p_{j}=w_{j}\cdot c_{j} \tag{3}\]  
\(p_{j}\) represents the optimization priority value for each manual assembly process step; \(c_{j}\) is the value for process control. If the process element achieves good quality values regarding the process control, less optimization is required related to the process. Based on the absolute optimization priorities, the relative optimization priorities can then be calculated, which relate the absolute values with the overall optimization project. This makes it clear in which relative relationship the optimization of a process element relates to other sub-processes.