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.

37 GENERAL MECHANICS AND MECHANICAL ENGINEERING UDC 621.7 Volodymyr Davydenko Graduate student Vadym Medvedev Ph.D., Associate Professor Igor Sikorsky Kyiv Polytechnic Institute (KPI) Kyiv, Ukraine CURRENT STATE OF QUALITY CONTROL IN ENGINEERING PRODUCTION Abstract. This literature review explores the integration of comprehensive quality indicators in manufacturing processes to ensure optimal technological operations in the context of Industry 4.0. It begins with a background on the evolution of quality assurance, highlighting the limitations of traditional reactive methods and the need for dynamic, predictive systems that aggregate metrics such as cost, time, defect rates, and variability. Analyzing 10 key sources, the review synthesizes approaches from object-oriented process models for interoperability, AI- driven predictive frameworks for zero-defect manufacturing, and structured quality assurance in assembly along with relevant metrics. Strengths include enhanced defect prediction and risk mitigation, while weaknesses encompass data quality issues, scalability challenges, and incomplete integration of predictive analytics. Contradictions in prior research, such as planning-focused models lacking prediction versus AI methods struggling with interoperability, are identified. The conclusion