Predictive Maintenance as a Service for the Steel Industry
Unexpected downtime can cost not just a lot of money and time for any steel plant but can also affect the production and growth of downstream industries dependent on steel production. Machine availability and reliability being the top concern in steel production, the cost of secondary damages of such breakdowns can be astronomical. This can significantly affect the quality, operational efficiency, loss of productivity, and increased risk of accidents on site. With such high stakes, using predictive maintenance to avoid unexpected downtime can be a gamechanger for steel plants.
What are the Challenges in Steel Manufacturing Industry?
- Production process parameters from the upstream steel manufacturing processes strongly influence the downstream ones.
- The intermediate products in the process undergo both chemical and mechanical changes, making monitoring quality and output more difficult.
- Older & legacy machinery
- Frequent halts in production due to machine failure & downtime
- Expensive coal & raw materials
- Avoiding unexpected accidents on site
- Various external factors like lockouts, strikes, inefficient administration, and shortage of raw materials
Predictive maintenance is the next level of condition-based maintenance that regularly monitors the operating condition and health of machines through edge computing. It helps predict asset issues before they occur, thus not disrupting the manufacturing workflow, reducing accidents, and improving the machine’s overall availability & reliability. The data from the edge computing systems continuously provide results in real-time to alert you of machine performances and machine breakdowns. It also alerts you of maintenance based on what machine data indicates, which helps to avoid any unexpected repair costs.
Advantages of Predictive Maintenance for Steel plants
Reducing downtime and Ensuring asset longevity & RUL:
Failure of machines can be pretty stressful and is an added expense. Using predictive maintenance, you can predict issues ahead of time, reduce downtime of machines, increase uptime by 15-20%, schedule maintenance as and when required, and thus improve the lifeline of the old machine by up to 20%.
How Does Infinite Uptime’s Predictive Maintenance as a Service Solution Work for Steel Industry?
Infinite Uptime’s Predictive Maintenance as a Service uses real-time data to find out the status of the machine and the health of every rotating asset. The edge computing system is deployed to monitor all critical assets in every process and monitors parameters like vibration, temperature, etc. A machine health score is provided in real-time for every monitoring location. Anytime there is a dip between the prescribed machine score, an alert goes to the plant supervisor, along with a recommended remedial action suggested by our Predictive Maintenance as a Service solution. The machine status is further analyzed to ensure that the mitigated solution has improved the status quo.
Customized dashboards for different levels like plant operator, manager, plant head, or manufacturing head (multi-plant) are created & made accessible for the team to ensure agile & proactive decision making to ensure the production continues smoothly.
Conclusion
Want to learn more about how we have helped large global steel manufacturers avoid downtime & improve factory performance? Click here to read a case study.
FAQs
Data analytics in Infinite Uptime’s solution enables comprehensive monitoring and analysis of machine performance trends. This data-driven approach supports informed decision-making at various management levels, from plant operators to manufacturing heads, fostering agile responses to maintenance needs.