Shop Floor Efficiency

Manufacturing facilities face the challenge of ensuring maximum productivity while minimizing maintenance costs and machine downtime. In the past, over-maintenance or under-maintenance of machines was common due to a lack of data. Both of these situations resulted in machine breakdowns, downtime, and increased costs. To overcome this problem, Azile, an IoT solutions provider, introduced an advanced solution for continuous condition monitoring by collecting machine data through the use of accurate and reliable sensors.

Problem: A manufacturing company was experiencing frequent machine breakdowns, resulting in reduced productivity, increased downtime, and maintenance costs. The maintenance team was also facing challenges in predicting maintenance time and preventing unexpected costs.

Solution: Azile implemented its IoT-based condition monitoring solution by collecting data from sensors placed on machines. The data collected was automatically standardized and transformed into usable and actionable insights. The manufacturing company could then connect sensors and manage equipment through a web interface. This allowed them to analyze machine controls, view real-time data, and export the same. The collected data was then processed through an AI/ML system to facilitate intelligent decisions based on the diagnostic data. This real-time machine data helped the manufacturing company predict maintenance time, prevent breakdowns, and reduce unexpected costs and downtime.

Advantages: The IoT-based solution provided the following advantages:

1. Predictive and preventive maintenance: The manufacturing company could drive predictive and preventive maintenance by analyzing real-time data and making intelligent decisions based on the diagnostic data.
2. Alerts and notifications: The system provided alerts and notifications regarding incidents, enabling the maintenance team to take immediate action.
3. Remote fixes: The manufacturing company could share machine data with service providers for remote fixes, reducing downtime and maintenance costs.
4. Improved machine health management: The IoT-based solution provided an efficient way to manage the health of machines by providing real-time data and facilitating intelligent decisions based on the diagnostic data.

Results: The implementation of Azile’s IoT-based solution resulted in reduced downtime, improved productivity, and decreased maintenance costs for the manufacturing company. The real-time data provided by the solution enabled the manufacturing company to analyze machine controls and take intelligent decisions based on the diagnostic data. The predictive and preventive maintenance capabilities of the solution helped the company avoid unexpected costs and downtime. The alerts and notifications provided by the system ensured that the maintenance team took immediate action. Sharing machine data with service providers for remote fixes reduced downtime and maintenance costs.

Conclusion: The implementation of Azile’s IoT-based solution helped the manufacturing company improve shop floor efficiency by providing real-time data, enabling intelligent decisions based on the diagnostic data, and driving predictive and preventive maintenance. The solution’s alerts and notifications ensured that the maintenance team took immediate action, reducing downtime and maintenance costs. Sharing machine data with service providers for remote fixes also helped in reducing downtime and maintenance costs.