Nexperia Malaysia Sdn Bhd is a semiconductor manufacturing company located in Senawang, Negeri Sembilan. Their HVAC and process cooling systems are served by a centralized chiller plant, which also includes air handling units (AHUs) and small ducted AC units with temperature control valves.

However, the current system has several issues. There is no real-time monitoring of cleanroom pressure, production floor temperature, or humidity. Additionally, users are unable to remotely control the temperature setpoint of the production floor. Some of the AHU modulating valves are not working, and there are limited and inaccurate temperature sensors, leading to overcooling of the production floor.

Furthermore, the chiller plant operates 24/7 with a total capacity of 2,200 refrigeration tons (RT) and consumes over 8.5 million kWh annually. The HVAC system alone uses 70% of the total chiller plant’s capacity, and the company aims to reduce this usage by 10%.

To improve production floor management, 120 temperature, humidity, and cleanroom pressure sensors were installed for real-time monitoring. These sensors provide accurate feedback and work with Easi HVAC AI-driven software to remotely control the AHU fan and chilled water control valve. The software uses a new demand-based dynamic set point that adjusts to the ever-changing heat demand on the production floor due to outdoor temperature changes.

In addition, a real-time chiller plant energy monitoring system was installed to measure the kW/RT performance. This enables remote adjustments of the chiller’s settings and provides in-depth analysis of its running and error logs via a simple web dashboard accessible from anywhere.

Easi HVAC is designed for easy operation with minimal training and includes built-in FCU, AHU, and chiller schedulers similar to Google Calendar. The software has various settings, including fixed demand profiles or automatic detection by cost-effective wireless Tx-sensor series (human activity sensors) and/or AI-driven predictive algorithms.

To ease the maintenance team’s workload, Easi HVAC’s predictive maintenance function automates more than 75% of routine preventive maintenance tasks using AIoT sensors. This simplifies the data into a digital health score, providing insightful reports for the maintenance team to focus on the right HVAC equipment before failure. This feature reduces the need for daily fire-fighting and enables a highly productive maintenance team.

Easi HVAC also has built-in digitalized complaint/user feedback via a QR code with an Automated Digital Assistance ChatBot called Easi Bot to further reduce the burden on the facilities maintenance team.

To sum up, these systems provide real-time monitoring and control of chiller plant operations with the following features:

• Real-time Chiller Plant Efficiency Measurement kW/hour
• Real-time Chiller Plant Load (RT)
• Real-time Chiller Performance Benchmarking
• Real-time Demand Control Optimization (Air side/AHU side) with 10X real-time accuracy feedback
• Real-time Chiller Plant Optimization (Remote Set Point, Scheduling & Part Load Optimization)
• Real-time abnormalities detection (from load changes, efficiency changes, temperature changes, or energy pattern changes)
• Insightful, data trending, monitoring & operational control all-in-one dashboard