INTEGRATION OF ARTIFICIAL INTELLIGENCE ALGORITHMS INTO THE PROCESSES OF AUTOMATED DESIGN OF LIFTING AND TRANSPORT SYSTEMS

Abstract

The article investigates the integration of artificial intelligence algorithms into the automated design processes of elevators and lifting and transport systems. Particular attention is devoted to the transformation of traditional engineering workflows under the influence of AI-driven tools and digital technologies. Modern approaches to the application of machine learning, parametric modeling, generative algorithms, and intelligent optimization within CAD/CAE environments are analyzed in the context of improving design accuracy, speed, and adaptability. The role of AI is considered not as a replacement for the engineer, but as an advanced decision-support and automation instrument that enhances productivity and reduces routine workload.Special emphasis is placed on the practical implementation of AI elements within the complete production chain — from the creation of parametric 3D models and automated generation of technical drawings to batch export of manufacturing files and integration with digital production management systems. A detailed case study of comprehensive automation in preparing sheet metal layouts for elevator components is presented. The results demonstrate a substantial reduction in processing time for hundreds of design configurations, improved standardization of documentation, and minimization of errors caused by manual data handling. The automation framework ensures consistency of engineering parameters across assemblies, accelerates the updating of documentation after design modifications, and enhances coordination between design and manufacturing departments.The study confirms that the integration of AI-based tools into automated design workflows contributes to improved data integrity, increased operational efficiency, and higher reliability of lifting equipment development. Furthermore, the adoption of intelligent algorithms supports the transition toward digital manufacturing and Industry 4.0 principles in the elevator sector. The findings substantiate the feasibility and перспективність of further development and large-scale implementation of AI-driven solutions in the automated design and production of lifting and transport systems.