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.
Highlights
In industries, system downtime can be detrimental; surprise power outrages can create severe issues.It often requires costly repairs that increases overall operating expenses
Using smart sensor app user can check the status of their motors at any time with their smartphone
A Vanson Bourne survey of 450 UK, US and French IT decision makers in field service and service management has estimated that the average cost of downtime is $260,000 per hour
Summary
System downtime can be detrimental; surprise power outrages can create severe issues. The tangible cost of downtime go way beyond the salaries of employees who sit idle while waiting for equipment to get back up and running. If damage to equipment occurs, the costs to repair or replace it need to be factored in as well, along with any specialized technical support. The Smart sensor device can help eliminate unplanned equipment downtime with predictive analytics, and measuring data, such as vibration, temperature and other environmental factors. Software monitors any changes in parameters of a machine’s operation and automatically trigger an alert for a user or service technician to repair or replace parts prior to failure or unplanned downtime. Research [1]-[3] reveals the loss of industrialists due to unplanned downtime of machines. Bourassa et al in [4] reveals the equipment failures and their contribution to industrial incidents and accidents in the manufacturing industry
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