Aspects of artificial intelligence implementation in the technological support of the life cycle of machine-building products
Abstract
Kovalevskyy S., Sydiuk D., Kovalevska O.
Aspects of artificial intelligence implementation in the technological support of the life cycle of machine-building products.
The article is dedicated to the analysis of the implementation of artificial intelligence (AI) in the technological support of the life cycle of manufacturing products. Key aspects of AI application for increasing the efficiency of all stages of the life cycle of manufacturing objects – from design to disposal – are described. Special attention is given to the use of advanced technologies for automation, predictive maintenance, and diagnostics of the condition of production objects. Mechanical processing by pressure and cutting is considered as important stages of the production process, where AI application ensures adaptive control of parameters such as pressure, temperature, cutting speed, and deformation force, which helps to minimize tool wear, improve processing accuracy, and ensure stable product quality. A conceptual structural scheme for integrating AI into production control processes and the maintenance of functional surfaces of parts has been developed. It includes the collection and processing of data, the prediction of the condition of production objects, and their operational recovery in case of wear or damage detection. The use of AI technologies allows timely identification of issues arising at the stages of equipment operation, ensuring its uninterrupted work and reducing downtime. AI integration into product recycling processes is also important, optimizing material processing and reducing the negative environmental impact. The article separately addresses predictive maintenance issues, where, through data analysis from sensors and detectors using AI, wear and failure of parts can be predicted. The creation of digital twins of production objects enables real-time monitoring of their functional condition, improving equipment efficiency and reducing maintenance costs. The article demonstrates that the implementation of AI at all stages of the life cycle of production objects is a critical factor in enhancing their reliability, durability, and competitiveness. The obtained results show that the use of AI significantly increases production efficiency, reduces maintenance and repair costs, improves product quality, and ensures environmental sustainability in modern manufacturing. AI plays a crucial role in providing adaptive approaches to managing production processes, allowing high productivity to be achieved with minimal costs.
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