## 4 Results and Discussion
This underscores the necessity of a skilled workforce that is well-versed in both the technical aspects of antenna manufacturing and the application of emerging technologies. The strategic focus on these resources, especially on human capital and information, is pivotal for achieving higher efficiency, innovation, and reliability in the production process. The emphasis across these varied resources reflects a balanced approach, integrating human skills with technological, financial, and material aspects to optimize manufacturing outcomes in the dynamic field of 5G technology. The _CI_ value is calculated to be 0.041, and the _CR_ is determined to be 0.037. Furthermore, the maximum eigenvalue (\(\lambda_{\text{max}}\)) obtained from the analysis is 5.164. These metrics are crucial in validating the logical consistency of the pairwise comparisons made during the AHP process. For the purpose of this analysis, and as indicated in our study, we utilized an _RI_ value of 1.12 for a matrix size of \(n=5\), as outlined in Table 4. The _RI_ value is an important component in the calculation of the _CR_ and is used to assess the probability that the matrix judgments were randomly generated. A _CR_ value less than 0.1 is generally considered acceptable, indicating a reasonable level of consistency in the pairwise comparisons. In our case, the _CR_ value of 0.037, being well below this threshold, signifies a high level of agreement among the expert assessments, thereby adding to the credibility and reliability of the AHP results. This careful and methodical approach in calculating the _CI_, _CR_, and \(\lambda_{\text{max}}\), along with the use of the appropriate _RI_ value, ensures that the AHP analysis for determining the weights of the 'Resources' factor in 5G ceramic antenna manufacturing is both coherent and robust. It reinforces the validity of the findings and supports the strategic insights derived from the analysis, particularly in terms of prioritizing resource allocation in the manufacturing process. Figure 9 encapsulates and visualizes the findings from Tables 7-9 in the form of a bar graph, providing a succinct and comparative view of the weighted significance of various sub-factors in the manufacturing of 5G ceramic antennas. As depicted in the graph, 'Manufacturing Company' commands the highest local weight of 0.443, indicating that the technical capabilities and the stability of the manufacturing processes within the company are of paramount importance. This suggests that the core competencies and the operational excellence of the manufacturing company are the most critical determinants of success in the industry. The graph also shows that 'Human Resources' holds the second highest weight, which conveys the continued importance of skilled personnel in the production process. Despite the trend towards automation, the significant weight of human resources implies that the impact of human expertise, problem-solving abilities, and innovative thinking remains substantial. This factor's prominence emphasizes the need for comprehensive training and skill development programs to enhance the workforce's capabilities in managing and executing complex manufacturing tasks, particularly those involving new technologies such as blockchain and smart contracts. The third highest weight is attributed to 'Technical Service Provider', reinforcing the notion that the expertise provided by these entities is crucial. Technical service providers include those who offer specialized knowledge and services essential for the manufacturing process, such as equipment maintenance, software support, and technical consulting. The high weight of this sub-factor underscores the reliance on specialized technical services and the value of partnerships with service providers who contribute to the robustness and advancement of manufacturing operations. Together, these weights illustrate a manufacturing ecosystem where technology, human skill, and specialized services play interdependent roles.