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Across the world, manufacturing equipments face failures and downtimes, while in different environments, due to the nature of repetitive tasks being performed by them.
Across the world, manufacturing equipments face failures and downtimes, while in different environments, due to the nature of repetitive tasks being performed by them. However, with a higher demand for efficiency and quality in production and manufacturing, these unplanned downtimes cause delays and customer-loss, thereby hitting the bottom line of the organization. Therefore it is essential to limit the possibility of unplanned downtimes as much as possible, which can be done using machine performance data.
Predictive maintenance refers to the use of a data-driven approach, that analyses the equipment condition to predict when that equipment requires maintenance. It involves techniques that can significantly improve the performance and lifetime of assets.
Predictive maintenance enables strategic allocation of maintenance resource to optimize equipment performance throughout the organization. Inclusion of predictive maintenance to organizational activities is not very simple. It allows to avoid unwanted pitfalls that causes wastage of time and resources while failing to deliver results.
This blog deep dives into the technology and strategy required for smooth and successful transition to predictive maintenance.
What is Predictive Maintenance?
Predictive maintenance is a multi-step process that helps you monitor your equipment health to prevent failures and unplanned downtimes. It uses data from sensors and Artificial Intelligence based predictive algorithms to estimate the correct time of equipment failure and schedule maintenance. It identifies the root cause of issues in complex machinery and the parts that need replacement. Predictive maintenance process generally involves:
- Monitoring equipment to collect data about its performance and condition.
- Analyzing the data obtained to gain actionable insights.
- Taking remedial measures based on the insights obtained.
Benefits of Predictive Maintenance
- Minimizing unplanned downtimes
- Improving the performance of machines
- Maximizing equipment life
- Optimizing maintenance costs
- Improving safety
- Real-time information of the condition of the machines.
How does Predictive Maintenance work
Now that it is clear that predictive maintenance can help reduce unplanned downtimes, the question is, how does it work?
- Define the problem
It is crucial to define and understand the problem you are trying to fix. For example, are you concerned of the unplanned downtimes? or Are is the worry about employee safety due to sudden equipment breakdowns?
- Establishing Baseline
After defining the problem, it is essential to create a baseline for the equipment performance so that the data collected can be compared to identify variance and subsequent glitches / anomalies. Noting historical variations and patterns can also help track the equipment health.
- Installation
Install the necessary system in place to capture the information that can help monitor the desired metric. The system (censors & algorithms) should be calibrated to account for seasonal patterns as well as breaches.
- Monitor dashboards and alerts.
Automatic alerts are triggered in case of any anomalies detected by the censors. The dashboard gives an overview of the machine health, and manual inspection can be scheduled based on the dashboard reports, for convenience.
Conclusion
To get the best results from your predictive maintenance program, adopt the right philosophy, invest in the required technology, and implement the program in small, and measurable portions. With this approach, you can steadily build momentum and see positive results from the bottom-line from your predictive maintenance implementation.