Overview:
A manufacturing client sought to improve equipment uptime and reduce maintenance costs. Techseria used Azure Data & AI to implement predictive maintenance, helping the company anticipate and prevent equipment failures.
Solution:
- Data Integration & Processing: We set up an Azure IoT Hub to gather and process data from factory sensors.
- Predictive Maintenance Model: Using Azure Machine Learning, we developed a predictive model that identifies signs of wear and tear, alerting the team to maintenance needs before breakdowns occur.
- Dashboard & Analytics: Through Power BI, we provided real-time monitoring and analytics, giving the client a comprehensive view of equipment health.
Results:
- 25% Reduction in Maintenance Costs: Predictive insights allowed proactive maintenance, reducing costs by 25%.
- Increased Equipment Uptime: Equipment uptime improved by 30%, allowing the company to meet production targets more effectively.
- Operational Transparency: Real-time insights enhanced decision-making, enabling better resource allocation.