Comprehensive approach toward IIoT based condition monitoring of machining processes

This comprehensive review aims to achieve and develop an automated platform to acquire and process data for error compensation in CNC manufacturing. The Industrial Internet of Things (IIoT) is of interest in manufacturing and cloud manufacturing. An IIoT-based condition monitoring solution with multiple sensors can predict the potential variability of the part specifications in the in-process or possible defects by acquiring large data to be processed with prognostic tools in the cloud server. This includes data acquisition and management from various sensors in progress, data collection, and data transfer to the cloud. The latter may include warnings or altering some operating parameters, for example, spindle speed, feed rate, and depth of cut. This paper discusses monitoring techniques and includes a comprehensive description of machining process parameters and their ranges of variability based on experimental results extracted from the studies on materials under several process conditions for both milling and turning processes. This literature review assists in identifying appropriate sensors and their respective ranges of operations. Furthermore, the relationship between the process and monitoring parameters is further studied to understand the parameter selection and combination better. This development will serve efficiently as a cyber-physical production system under cloud manufacturing management and can be extended to non-I4.0-ready machines via IIoTs.