Predictive Maintenance at Your Fingertips

Project Overview: Condition Monitoring is a vital component of our heavy equipment management solution. It provides real-time insights into equipment health, enabling businesses to shift from reactive to predictive maintenance strategies, thereby reducing downtime and extending equipment lifespan.

Objectives

1. Implement a flexible system for monitoring various equipment conditions across different industries.
2. Automate the process of detecting and alerting potential equipment issues.
3. Integrate condition-based triggers with the maintenance scheduling system.
4. Provide comprehensive oil sampling analysis for early detection of wear and contamination.

Features

1. Flexible Monitoring:

• Customize the system to monitor various conditions specific to your equipment and industry.
• Support for multiple input options, including ASCII and DDE formats.

2. Automated Alerts:

• Set up triggers to automatically raise work orders when limits are exceeded.
• Customize alert thresholds based on equipment type and operating conditions.

3. Integration with Scheduled Maintenance:

• Seamlessly link condition data with the Scheduled Maintenance module for efficient workflow.
• Trigger maintenance tasks based on actual equipment condition rather than fixed schedules.

4. Oil Sampling Analysis:

• Track oil condition by plant, component, and laboratory control number.
• Chart profiles of selected elements and fuel consumption trends for comprehensive analysis.

5. User-Defined Standards:

• Set your own benchmarks for low values, high values, and trends.
• Customize analysis parameters based on equipment type and operating environment.

Technology Stack

• Backend: Open-source technologies with open standards for flexibility and scalability.
• Database: Robust database system capable of handling real-time data streams and historical records.
• User Interface: Intuitive design for easy monitoring and analysis across various devices.

Outcome

The Condition Monitoring module has revolutionized maintenance practices in heavy equipment industries. Users report significant reductions in unexpected downtime, extended equipment lifespans, and optimized maintenance schedules. The shift to predictive maintenance has led to substantial cost savings and improved operational efficiency.