Evaluation of cutting tool resources in flexible manufacturing systems

Abstract

Flexible manufacturing systems (FMS) are widely used in modern mechanical engineering and instrumentation due to their adaptability and high productivity. However, their effective operation is strongly dependent on accurate management of cutting
tool (CT) resources, which are subject to wear during machining processes. This study aims to develop and justify a methodology for evaluating CT resource consumption with higher precision to support decision-making in FMS operations. Machining operations are classified into positional and contour types based on their tool engagement characteristics. For each type, appropriate quantitative wear criteria are proposed: the number of discrete tool actions for positional machining and the processed volume or
path length for contour machining. A Monte Carlo-based numerical procedure is developed to estimate the actual volume of material removed during contour operations, accounting for overlapping tool trajectories and idle movements. The results confirm
that the proposed approach significantly improves the accuracy of tool workload estimation compared to traditional time-based methods. The methodology enables more reliable forecasting of CT wear, supports predictive maintenance strategies, and improves overall system efficiency. The proposed algorithm can be integrated into digital manufacturing workflows, contributing to the implementation of intelligent tool management in line with Industry 4.0 objectives.