Conditional Monitoring of Industrial Machines

Abstract

The MSME industries manufacture spare parts for different industrial sectors at major quantities. This huge production is attained by Computer Numerical Controller (CNC) machines. The downtime of these CNC machines induces a major loss in their production line. The major symptoms of malfunctioning of the CNC machine are observed by increased radiator temperature and reverberations (irregular vibrations). It is essential to monitor these vibrations to predict the failure and go for periodical maintenance. The aim of our project is to help automate the Real-time condition monitoring of a CNC machine, which has been a challenging task for many operators in MSME sectors. It also proposes to monitor the maintenance of the CNC machine and alert the user (operator) if there are any abnormality in the vibration and temperature pattern. Temperature Sensor and Vibration Sensor are used to monitor the radiator temperature and CNC machine vibrations respectively. These sensors are connected to Raspberry Pi board with the help of Arduino UNO and the sensed information are constantly read. These observed data are simultaneously pushed to a cloud for further storage and analysis. The stored data are analysed statistically using control charts methods for validating the process control. The results of the analysis process are presented in a graphical representation to the user (operator) via Android application. Any abnormal condition of the CNC machine are immediately indicated to the operator via an alert message.