Live Machine Health Analysis - LIMHA

• Tech Stack: Python, SoC, Sensors, Machine Learning, Predictions

1. Live machine health analysis. M.L., FFT, DSP, machine to machine communication, failure prediction.

2. LIMHA is a real-time analysis of machine health that gathers real-time machine data using sensors and analyses the health of the machine with the help of AI-ML algorithms.

3. The objective of the project is to detect any abnormality in the machine behaviour, probable error in any of the machine components and to predict probable failure before it happens to reduce downtime, maintenance cost, production delay, and any unfortunate incident due to machine failure.

4. Edge computing has been used which makes communication faster, enforces privacy, gives greater operational efficiency, and is having lower operating costs.

5. It segregates the probable failure into multiple levels and then gives the root cause of the failure and generates alerts and recommendations which makes maintenance easily understandable and less time-consuming.