Predictive Maintenance
Introduction
What is Predictive Maintenance?
Predictive maintenance is a proactive maintenance strategy that employs data and analytics to predict when an equipment is likely to fail, allowing repairs or replacements to be scheduled just before the failure happens.
This approach contrasts with traditional reactive maintenance, where equipment is serviced only after it breaks down, and preventive maintenance, which involves scheduled maintenance tasks regardless of the equipment's actual condition.
Source:
Asset Infinity
Why is it important?
Predictive maintenance is key strategy employed by industries to optimize the performance of their assets and machinery. Here are some reasons why predictive maintenance is crucial to the industries:
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Cost Savings
Predictive maintenance allows organization to address potential issues before they lead to equipment failure, allowing for optimal scheduling of maintenance during planned downtime, thereby reducing downtime cost.
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**Optimizes Equipment Utilization **
By addressing problems proactively during planned maintenance windows, organization can ensure that equipment remains operational for more extended periods. Additionally, with continuous monitoring of equipment health through sensors, organizations can also ensure that assets are operating at their optimal performance levels, maximizing utilization.
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Extends Equipment Lifespan
Instead of following a fixed schedule, predictive maintenance relies on the actual condition of equipment to determine when a maintenance is necessary. This condition-based approach, optimizes maintenance intervals, and preserves critical components, therefore ensures the overall longevity and reliability of the entire system.
What is the Outlook for Predictive Maintenance?
According to the Predictive Maintenance and Asset Performance Market Report 2023-2028, the global predictive maintenance market stands at $5.5 billion in 2022, with an estimated CAGR of 17% until 2028. This indicates a strong anticipated growth in the predictive maintenance market, suggesting that more industries are recognizing its benefits.
The adoption of predictive maintenance aligns closely with the principles of the Fourth Industrial Revolution, often referred to as Industry 4.0.
Industry4.0 is defined as the integration of intelligent digital technologies, data analytics and automation into manufacturing and industrial processes. Some Industry4.0 technologies used in Predictive Maintenance includes:
- Industrial Internet of Things (IIOT)
- Machine Learning
- Cloud Automation
Source:
IOT Analytics
A Data Scientist Role in Predictive Maintenance
Data Collection and Preparation
Predictive Modelling
Deployment and Monitoring
Challenges and Personal Takeaways
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How to perform Predictive Maintenance
- Data Collection and Preparation
- Predictive Modelling
- Statistical Modelling
- Machine Learning
- Time Series Analysis
- Deployment and Monitoring
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Challenges and Personal Takeaways