## 5 Conclusions and Discussion  
Based on the presented analyses and research, the following conclusions were drawn:  
1. The workshop produced a significant improvement in the efficiency of production processes, which was confirmed by statistical analysis of the reception time. In the case of product A, the reference time was reduced by an average of 4.32 min, which was a statistically significant change (\(p<0.05\)). For product B, the average redemption time did not change significantly after the workshop, which indicates that the implemented actions had a limited impact on the process of reliability for this product, which may be related to a different specificity of production. 2. After the workshop, an increase in the number of Machine X strokes was recorded for both products A and B. In the case of product A, the number of strokes increased significantly, which indicates an improvement in the machine's efficiency as a result of optimization. However, for product B, the differences in the number of beats before and after the workshop were statistically insignificant, which may indicate the need for further analysis of the production technology of this product. 3. The introduced organizational and technological changes translated into growth in terms of the availability of the production time of the X. Reducing the recreation time and optimization of the Destacker's work allowed for more effective use of the machine. 4. The workshop had a positive impact on the key indicators of operational efficiency. Shortening the time of tailoring and increasing the efficiency of Machine X for product A confirmed the effectiveness of the optimization activities used. Although the impact on product B was less pronounced, the general increase in the efficiency of production processes indicates the benefits of the implemented changes. 5. Applications regarding the impact of the workshop were confirmed by statistical tests, which emphasize the importance of a systematic approach to assessing processes efficiency. Statistical analysis provided reliable evidence for the effectiveness of the carried-out activities, enabling the identification of areas with the highest potential for improvement. 6. Based on the analyses conducted, it is recommended to continue monitoring effectiveness indicators and regularly implement optimization activities. Particular attention should be paid to product B to identify and eliminate barriers limiting the increase in efficiency in this area. In addition, it is worth developing and implementing modern 4.0 industry technologies, such as automation and robotization, which can bring further benefits in the context of the efficiency of production processes. The presented study can serve as a basis for further research and the use of the developed mathematical model for analysis in low-level plants to increase control of the dependencies occurring in assembly processes. Further research directions in this area should focus on more advanced cooperation between humans and machines, with an emphasis on greater intuitiveness and effectiveness of cooperation. Digital twins, i.e., virtual models of real objects, will be increasingly used to monitor and optimize design and manufacturing processes. This will allow for better resource management and faster responses to problems. To summarize, the issues presented related to the evaluation of parameters affecting the efficiency of production processes, including barriers and prospects for automation in a real production environment, are certainly not exhaustive. However, they are a starting point for research into the future challenges of the automotive industry. Conceptualization, M.N. and W.L. ; methodology, M.N. and W.L. ; software, M.N. and W.L. ; validation, M.N. ; formal analysis, M.N. and W.L. ; investigation, M.N. and W.L. ; resources, M.N. ; data curation, M.N. and W.L. ; writing--original draft preparation, M.N., W.L., A.K. and K.S. ; writing--review and editing, M.N., W.L., A.K. and K.S. ; visualization, M.N. ; supervision, W.L.