Predictive Maintenance

Approach

Using pre-build AI models of Amazon Lookout for Equipement plus custom built specific for customer, we have:

• Built a Data Lake for data storage (historical and current)
• Develop a web application to analyse data and tag/identify events
• Develop a trigger mechanism to send alerts when:
  • Specific threshold are above/below pre-defined limits
  • Advance notices for potential errors/needed repairs
• Visual analytics like Balance Scorecard of entire company/production lines

Value Delivered

Benefits of a predictive maintenance platform using AWS, supported by a Data Lake and leveraging machine learning and analytics:

• Proactive Maintenance Scheduling: Predict failures before they occur to minimize equipment downtime.
• Strategic Asset Management: Use trend analysis for better decision-making about asset utilization and lifecycle management.
• Reduced Operational Risks: Implement preventive strategies to mitigate risks associated with equipment failure.
• Automated Real-Time Reporting: Generate automated reports and dashboards for up-to-date maintenance insights.
• Enhanced Historical Analysis: Leverage historical data to improve predictive accuracy and strategic planning.
• Early Anomaly Detection: Identify and address unusual machine behavior before it leads to breakdowns.
• Immediate Predictive Alerts: Receive alerts for potential issues to prevent costly downtimes.
• Cost Efficiency: Reduce maintenance costs by avoiding unnecessary repairs and optimizing part usage.
• Increased Operational Efficiency: Improve overall operational productivity through efficient equipment management and reduced downtime.