Internet of Things Based Smart Health Monitoring of Industrial Standard Motors

GAYATHRI R, Shriram K Vasudevan

Abstract


The Industry 4.0 vision provides recommendations how companies can ease the challenges.  In an industrial environment, it is beneficial to  have a predictive approach to make smart industry using IoT. The Predictive approach includes automating the maintenance activities of machines which help to deliver safety, performance, customer experience, capacity, cost efficiency and sustainability of the key business assets.  It helps to improve work force safety which reduces the need to access the infrastructure, develop technologies to enable activities to be remotely controlled from safe areas and automate processes to remove manual tasks and helps to increase infrastructure reliability.  It also improves the precision and accuracy of data collection, introducing data analytics, removing human bias, improving reproducibility.  This will improve information about asset condition, inform inspection and repair schedules based  on asset risks. By implementing predictive and preventive maintenance, one can improve equipment life and avoid any unplanned maintenance activity and thus reducing unscheduled downtime.  We in this work have an unit which could be easily attached to the motor units and this does not demand any wiring to carried out. The sensor monitor signals from the motor, accurately measuring key parameters at regular interval of time, as desired.  And, the data is sent to the cloud, which in our case is adafruit.  From there, the data is analysed and it produces meaningful information. The  server then sends alert message to the users about critical data of machine.   This will help in fixing any technical issue with ease without incurring much delay.


Keywords


Real-time Monitoring, Failure Analytics, Industrial Automation, Predictiive Maintenance, Adafruit, MQTT.

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Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
ISSN 2089-3272

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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