Universal mobile platform for servicing computer numerical control machines

In the context of the development of Industry 4.0 and digital manufacturing, minimizing downtime of process equipment is a key factor in increasing efficiency. The development of a universal mobile platform (UMP) is driven by the growing need for robotic automation of CNC machine tool interoperability, which still relies heavily on manual labor, resulting in lost time and reduced overall productivity. Existing stationary and mobile solutionsdo not provide the necessary combination of precision, adaptability, and rapid deployment in a dynamic production environment.

Aim. The study is to develop a universal mobile platform for servicing numerically controlled (CNC) machines with improved adaptability, accuracy, and reliability.

Research materials and methods. The research methodology includes systems analysis, mathematical modeling, and strength calculations, which confirm the structural reliability (safety factor of 36.4–52.3%). Results. This paper presents a mobile robotic platform designed for the rapid maintenance of CNC machine tools in a dynamic production environment. The scientific novelty lies in the synthesis of three innovative elements: a modular architecture, an adaptive air suspension, and a high-speed stabilization system, which provides improved off-road capability by adapting to surface irregularities, unlike existing solutions.

Conclusions. The results demonstrate the feasibility of integrating the platform into the production cycle based on predictive notifications from equipment, ensuring positioning accuracy of ±1.5 mmand autonomous operation. An important practical result is the proven reliability of the selected air springs, ensuring safe operation even in emergency situations. The work offers potential in the development of artificial intelligence (AI) algorithms for automatic control systems (ACS), enabling more complex predictive planning and adaptation to unforeseen situations without operator intervention. The practical significance of the work is confirmed by the estimated reduction in equipment downtime by 15–20%.