Proceedings of the International scientific and practical conference ―Science, Technology and Culture: Interaction, Evolution and Progress‖ (December 21-23, 2025) / Publisher website: www.naukainfo.com. – Copenhagen, Denmark, 2026. – 161 p.

42 in technological processes The scope is informed by the aim to achieve seamless integration of design, planning, and execution. Research objectives outline the specific steps: (1) Analyze existing quality models and indicators; (2) Develop a composite metric aggregating key parameters; (3) Test the model in simulated manufacturing scenarios; (4) Evaluate impacts on efficiency and defects. These objectives are SMART: Specific, Measurable, Achievable, Realistic, and Time-constrained. The method involves literature synthesis, model development using UML and ML algorithms, and validation through case studies. REFERENCES: 1. Feng S. C., Song E. Y. A manufacturing process information model for design and process planning integration. Journal of Manufacturing Systems. 2003. Vol. 22, № 1. P. 1–15. DOI: 10.1016/S0278-6125(03)90001-X. 2. Qiao L.-H., Yang Z.-B., Wang H.-P. B. A computer-aided process planning methodology. Computers in Industry. 1994. Vol. 25, № 1. P. 83–94. DOI: 10.1016/0166-3615(94)90035-3. 3. Markatos N. G., Mousavi A. Manufacturing quality assessment in the industry 4.0 era: a review : Ph.D. dissertation. London : Brunel Univ. London, 2023. DOI: 10.1080/14783363.2023.2194524. 4. Mondal S., Goswami S. S. Machine learning techniques for quality assurance in additive manufacturing processes. Int. J. Addit. Manuf. Digit. 2024. Vol. 1, № 2. P. 86–99. DOI: 10.36922/ijamd.3455. 5. Tang X., Wang B., Wang S. Quality assurance model in mechanical assembly. Int. J. Adv. Manuf. Technol. 2010. Vol. 51. P. 1121–1138. DOI: 10.1007/s00170-010-2679-2. 6. Playbook: Manufacturing metrics. PCBennett. 2022. URL: https://www.pcbennett.com/wp-content/uploads/2022/07/playbook- manufacturing-metrics-1.pdf (accessed at: 17.12.2025).