Development of a Smart Supervision System for Achieving Chatter-free Manual Drilling Operation

Abstract

Monitoring twist drill chatter is essential to avoid catastrophic failures, achieve better hole accuracy, and realize smart manufacturing goals. This paper presents a framework for developing a supervisory system that combines a sensor, data acquisition, detection algorithm, and Human Machine Interface (HMI) to achieve chatter-free operation of manual drilling machines. It utilizes an accelerometer for capturing real-time process information and extracts features from the sensor data using Root Mean Square (RMS) and Quadratic Support Vector Machine (QSVM) algorithms. The drilling operation stability or chatter conditions are communicated to the operator through HMI for enhanced human-process interactions. The proposed supervisory system has been implemented on a manual drilling machine to achieve chatter-free operations and demonstrate robust performance under various conditions. The developed framework is validated by performing manual drilling experiments with typical work materials (Aluminum, Mild Steel, and Titanium) and drill (High-Speed Steel and Solid Carbide) combinations over a range of feed rates and spindle speeds.