Driving Chiller OEM Success with Pulse Intelligent Digital Twin Technology

Improved asset uptime and reduce unplanned visits

Problem Statement

The Chiller OEM faced significant challenges in managing the performance and reliability of their equipment post-deployment. Unplanned downtime, inefficient energy consumption, and high maintenance costs disrupted their operations, reduced customer satisfaction, and had impact on profitability. Traditional approaches lack the precision and predictive capabilities needed to address these issues effectively.


Objective:

The objective was to empower the Chiller OEM with Pulse’s advanced predictive analytics and real-time monitoring capabilities to transform their operations. By enabling proactive maintenance, optimizing energy efficiency, and enhancing equipment reliability, Pulse ensures seamless performance and long-term value for both OEMs and their customers.

Challenges

Despite their innovative IoT-enabled chillers, the OEM encountered several challenges that hindered their ability to deliver optimal equipment performance and proactive maintenance. These challenges included:

  • Limited Predictive Capabilities: Although the OEM’s IoT-enabled chillers offered real-time monitoring, the data primarily supported reactive maintenance rather than proactive failure prevention. This limitation prevented the OEM from leveraging data-driven insights to address equipment issues, leading to operational inefficiencies and unmet customer expectations.
  • Frequent Service Visits: The lack of predictive analytics forced the OEM to undertake unplanned and costly site visits to remote industrial locations to address unexpected chiller breakdowns during operations. These visits strained resources, disrupted schedules, and added pressure to operational budgets.
  • Shrinking AMC Margins: The frequency and unpredictability of service visits directly impacted the OEM’s Annual Maintenance Contract (AMC) margins. The costs associated with emergency maintenance were increasing consequently decreasing profits and making it challenging to maintain competitive margins.



Solution

To overcome these key challenges, the OEM partnered with ExactSpace’s Pulse which is an Intelligent Digital Twin that leverages IOT Embedded Maintenance through predictive analytics to increase maintenance efficiency. This collaboration provided the OEM with critical information in order to minimize disruptions and optimize their chiller performance.

Seamless IoT Integration

Pulse integrated effortlessly into the existing infrastructure without disruption, enhancing the OEM’s IoT capabilities with advanced predictive analytics.

Predictive Analytics & Diagnostics

Pulse's AI-driven models offered early warnings, including chiller tube leak detection, enabling preventive actions before costly breakdowns occurred.

Proactive Customer Engagement

The OEM could now address issues before they become problems, offering proactive customer support, reducing emergency visits, and optimizing service delivery.

Impact

The implementation of Pulse delivered significant, measurable results for the OEM:

Improved Uptime

Predictive maintenance reduced failures, maximizing chiller availability and enhancing customer trust.

Increased AMC Margins

Fewer unplanned service visits led to cost savings and higher profit margins for AMCs.

Strengthened Reliability

The OEM solidified its reputation for reliable, high-performance chillersthrough better operational outcomes.

Frequently Asked Questions About Chillers

Pulse's advanced predictive maintenance capabilities transformed chiller performance by reducing unexpected breakdowns, enabling proactive issue resolution, and maximizing uptime.

Pulse’s predictive maintenance capabilities have significantly boosted AMC margins by reducing unexpected breakdowns and costly repairs. This leads to higher profitability, lower operational costs, and increased customer retention, resulting in more profitable service contracts and enhanced revenue.

Pulse strengthens chiller reliability by utilizing predictive maintenance to detect potential issues before they escalate, ensuring timely interventions. Its real-time monitoring and data-driven insights optimize performance, reduce unplanned downtime, and extend equipment lifespan, ultimately enhancing operational efficiency and reliability.

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