A Solution for Predicting the Timespan Needed for Grinding Roller Bearing Rings

The optimal management of manufacturing processes can be achieved through a set of optimal decisions, which must be made to choose the best method to follow every time the process planner reaches a point when several potential manufacturing paths branch off. A dedicated method, namely the Holistic Optimization Method (HOM), has already been developed for this purpose and has been validated in several studies based on artificial- and real-instance databases. The HOM consists of two algorithms: (i) the causal identification of a manufacturing process and (ii) a comparative assessment with similar already-assessed manufacturing cases recorded in an instance database. The two algorithms can be used to estimate the values of the different performance indicators of manufacturing processes. Their application for processing cost estimation in the case of the manufacturing processes of bearing components has already shown good results. In this paper, the HOM is presented as a solution for predicting the timespan needed for grinding roller bearing rings. The specific algorithms of the HOM were applied, grounded in the use of a database with data collected from the industrial environment. The cause variables selected to describe the grinding process of the roller bearing rings were the inner and outer diameter of the ring, its width and weight, the machined surface roughness, the grinding stone rotation speed, the cutting speed, the feed rate, and the cutting depth, while the effect variable to be used by the process planner as the decision criterion was the timespan.