Sierra Wireless > Case Studies > IoT-Enabled Predictive Maintenance for HVAC Systems

IoT-Enabled Predictive Maintenance for HVAC Systems

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 IoT-Enabled Predictive Maintenance for HVAC Systems - IoT ONE Case Study
Technology Category
  • Application Infrastructure & Middleware - Middleware, SDKs & Libraries
  • Networks & Connectivity - Global Navigation Satellite System (GNSS)
Applicable Industries
  • Buildings
  • Equipment & Machinery
Applicable Functions
  • Facility Management
  • Maintenance
Use Cases
  • Asset Health Management (AHM)
  • Predictive Maintenance
Services
  • System Integration
The Customer
About The Customer
The customer is a company that was founded in the early 1900s and has grown to become one of the world’s largest manufacturers of heating, ventilation, and air conditioning (HVAC) systems. The company's HVAC systems are typically installed in large-scale developments such as college campuses, commercial office buildings, and hospitals. The company was looking to leverage the Internet of Things (IoT) to enhance the capabilities of its HVAC systems, particularly in the area of predictive maintenance.
The Challenge
The company, a leading manufacturer of heating, ventilation, and air conditioning (HVAC) systems, was seeking to leverage the Internet of Things (IoT) to enhance the capabilities of its large-scale HVAC systems. These systems are typically installed in large developments such as college campuses, commercial office buildings, and hospitals. The company was particularly interested in enabling predictive maintenance, as servicing major HVAC systems is expensive and a prolonged outage can cause significant disruption. However, implementing a predictive maintenance system involves building out a complex IoT architecture. A large number of sensors and devices have to be connected to a centralized management system. The company may have hundreds if not thousands of HVAC assets in the field, all of different types and models. These devices may be spread over different regions, which means managing and negotiating with multiple network operators. To enable remote monitoring, there also has to be a stable and secure connectivity.
The Solution
The company opted for the FX30 Gateway by Sierra Wireless, a solution that could support advanced functionality for its large-scale HVAC systems, including predictive maintenance. The FX30 is designed for low power consumption and provides a sound platform for IoT connectivity. Sierra’s Enhanced Carrier Connectivity (ECC) solution simplifies the connectivity aspect of the IoT equation. ECC provides secure access to multiple Tier-1 networks throughout the US, so the company did not have to manage multiple SIM vendors. There is one point of accountability and one invoice, which greatly simplifies management. The company can closely track spending, with real-time usage information and put in alerts to prevent over-spends. Sierra’ Network Operation’s center is constantly monitoring the core network to pro-actively prevent any service disruptions. The result is reliable connectivity with minimal downtime.
Operational Impact
  • The implementation of the FX30 Gateway by Sierra Wireless and the Enhanced Carrier Connectivity (ECC) solution has enabled the company to build a complex IoT architecture for its HVAC systems. This has allowed the company to closely track the temperature in different rooms in a building and adjust the heating or AC accordingly. The IoT-based service has also enabled predictive maintenance, allowing the company to monitor the performance of individual components and send detailed information back to a cloud-management platform. This has resulted in cost savings, as service personnel can be sent only when needed, and they arrive with the appropriate parts and equipment, increasing the first time fix rate. The solution has also provided stable and secure connectivity, with minimal downtime.
Quantitative Benefit
  • Reduced operational expenses by up to 30% by creating smart buildings using IoT
  • Reduced energy consumption as HVAC accounts for 39% of all energy used in commercial buildings in the US
  • Increased first time fix rate due to foreknowledge of the fault

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