## 4 Results and Discussion  
### Preliminary Data Analyses  
Data collection for the analytical process was conducted between April and May 2024, during the final quality control stage of the finished products. The data collected were subject to extensive preliminary analysis. The first step was to assess the completeness of the data, identify any missing data, and analyse outliers that could affect the results of further analyses. Advanced statistical methods and algorithms were used to assess the quality of the data, allowing anomalies to be accurately identified and removed. Data were then standardised and normalised to ensure consistency of scale and to prevent the influence of different units of measurement of variables on subsequent stages of analysis. This process ensured consistent results when comparing different variables. Furthermore, a detailed analysis of the types of defects in finished products was performed. This analysis included classifying and categorising the different types of defects and determining their frequency of occurrence. Figure 2 shows that the most common defects recorded in the manufacturing process are D2 and D3, which represent 25.20% and 21.85% of the total defects, respectively. Cracks pose a significant threat to product integrity, often leading to serious performance problems or product failure. Surface imperfections, which affect both the appearance and functionality of the product, are also a major concern, particularly in industries that require high-precision and smooth surfaces. Addressing these two types of defects should be a primary focus to improve overall quality and reduce production losses. D1 follows with 15.63% of defects, making it the third most common problem. Although not as critical as cracks or irregularities, scratches and abrasions can still affect aesthetic quality and, in certain applications, performance. D4, which accounts for 14.04% of defects, can cause significant problems in components that require rotational accuracy, such as drive shafts or machine parts. Controlling these medium-level defects can improve product reliability and customer satisfaction, especially in performance-critical environments. The least common defects are D5 at 12.28% and D6 at 11.00%. Incorrect dimensions can lead to assembly problems or operational malfunctions, while inappropriate hardness can undermine the durability and wear resistance of the product. Although less common, these defects still need to be addressed, as their impact on product performance can be significant. Focussing on reducing these defects, in addition to addressing the most common problems, will ensure an overall improvement in production quality and process efficiency. Figure 3 illustrates the distribution of defect types (D1 to D6) across specific weeks from April to May 2024. Figure 2: Defects recorded in the manufacturing process. In the initial week of April, the data indicate a notable prevalence of defects D1, D2, and D3, with D2 exhibiting the highest incidence among all identified defects. D4 and D5 are relatively less prevalent, while D6 has a minimal occurrence. In the second week, there is a notable increase in the incidence of defect D3, while D1 and D2 exhibit a slight decline in comparison to the preceding week. The distribution of defects D4, D5, and D6 remains low, but there is a more even distribution of these defects. In the third week, defects D3 and D2 continue to exert a dominant influence, maintaining high counts. In contrast, D1 and D5 exhibit a slight increase, while D4 and D6 remain at lower levels. In the fourth week, D3 reaches its highest count for this defect type throughout the period, with moderate counts for D1 and D2 and lower counts for D5 and D6. In May, there is a notable shift in the distribution of defects. In the initial week, the frequency of defect D3 declines, while that of D1 and D2 increases, with a slight rise in D4 and minimal change in D5 and D6.