Home / Case Studies / How an AI/ML-Based IoT Solution reduced downtime for an Industrial System Overview Challenge Solution Impact Want to learn more? CONTACT US Overview Challenge Solution Impact Contact Us Contact Us First Name*Last Name*Company*Work Email* What can we help you with?*How did you hear about us?I agree to receive marketing communications from Orion Innovation.* I agree to receive marketing communications from Orion Innovation. We are committed to protecting and respecting your privacy. Please review our privacy policy for more information. If you consent to us contacting you for this purpose, please tick above. By clicking Register below, you consent to allow Orion Innovation to store and process the personal information submitted above to provide you the content requested.NameThis field is for validation purposes and should be left unchanged. 100K+ HVAC and Water Heating Systems Across the Globe 200+ Identified Potentially Faulty Systems in Two Months The customer is a leading US-based global manufacturer of professional factory-grade systems such as Commercial Air Handlers, Split Heat Pumps, Split Air Conditioners. The company currently operates 100K+ HVAC (heating, ventilating and air conditioning) and water heating systems for its enterprise clients across the globe. Challenge Failure in any of the HVAC or water heating systems installed in the field, can have severe impact on operations for enterprise clients. Upon failure, replacement parts or skilled technicians to resolve an issue may not be readily available, leading to further downtime and losses. Our customer wanted the ability to predict system anomalies and automate maintenance requests or alerts for immediate corrective actions. Solution Orion developed and implemented an AI/ML-based IoT solution that could track system anomalies and suggest corrective measures. The HVAC and water heating systems installed in the field, regularly report their configuration and sensor measurements to the cloud producing several gigabytes of data per day. The data collected indicates the health and performance of systems and its components, and the solution developed leverages this information to drive alerts regarding predictive maintenance. The Orion team organized the data received from thousands of sensors, e.g., temperature inside and outside a vessel, power input / output at which a system was running, weather conditions and other information. They then applied Mathematical, Statistical and Deep Machine Learning approaches to the organized datasets and clustered systems to predict failures, their severity and impact on operations. The Orion team applied the following techniques: Dynamic Analysis: Each device’s behavior was compared with its past performance and other similar devices. This allowed us to cluster the data and identify devices with anomalous behavior. Correlation Analysis: We correlated internal measurements with external measurements such as temperature, humidity and more. This helped in identifying device anomalies with respect to external weather conditions. Classification Analysis: We identified and labeled past events such as alarms and warranty claims, against respective data measured by the sensors at the same instance. Machine Learning: Deep Machine learning algorithms were trained based on the above analysis and the labeled event data, to predict alarms and warranty claims. Impact Orion identified 200+ potentially faulty systems in two months. Along with accurate observations regarding failures, our team delivered a detailed analysis and solution to the customer. We highlighted anomalies such as, an HVAC system starting at full power unnecessarily; and a water heater unable to boil water to the required temperature during certain periods. Our algorithms were iteratively tested in real-world conditions and adapted based on test results. Finally, our solution was validated by the field engineers, who rectified system issues based on our recommendations. At present, our solution is deployed for continuous monitoring. As a result, system failures have reduced drastically, as most of the issues are flagged-off for predictive maintenance. Related Links Industrial & Consumer Tech Digital Product Engineering Industrial IoT Industries Industrial & Consumer Tech COIs Digital Product Engineering Services Artificial Intelligence & Machine Learning Industrial IoT View All Case Studies
A Leader in Outdoor and Sporting Goods Delivering a Business Idea to Production: Developing an IoT-Enabled Smart Trail Camera
A Global Manufacturer of HVAC products How Rheem and Orion Built an Award-Winning Application to Transform Contractor Efficiency
A Major American Manufacturer How a Major Industrial Products Manufacturer Developed an App for Users to Interact with Their Smart Products
A Leading Healthcare and Life Sciences Company How Developing a Cloud-based Software Platform for A Life Science Company Sped Up Communication Between Patients and Medical Personnel