Malls in general is a place where people go to enjoy themselves. Have an amazing shopping experience. Kids can play around and all this is possible with the chillness that it is able to provide us with from the scorching heat of the Sun by using industrial grade Chillers.

These Chillers are Large and Expensive equipment that has a high initial capital cost, Operation, and Maintenance. Apart from that with increasing fuel prices, the cost of energy has also gone up in terms of Cost and CO2 Footprint.

Real-time data are currently been used to manage the operation and the older data are usually discarded. These devices use a phenomenal amount of data in real-time to decide what is the next operation. Since these settings are done based on a factory test bench, the actual performance is majorly affected in the real scenario. We won't know whether units are running optimally in different geographical locations or even how they are performing over a longer period of time. Since these tests are done in a temperature-controlled environment, operation curves are based on that. Some of them are unchanged from the past 20-30 years as well.

A buyer would have to follow the same datasheet and decide to go for the solution. Here the buyer has limited information for choosing the solution.
Data would help a buyer to make a better choice by choosing the solution based on a specific use case from a broad number of chillers. The data would help in understanding which chillers work more efficiently for long periods under a low load or which are better in humid environments or which are optimal for operation under a sustained heavy load.

With better access to data, one can clearly see when their chillers are costing them the most to operate. As well as seeing what is happening, access to data allows the owners of chiller units to detect potential faults. By collecting and analyzing these data from different parts of HVAC, the Planning team can detect any hardware fault or find out any bad control strategy and make the system operate more efficiently. With continuous optimizations which are easier to detect, maintenance costs would come down dramatically. Source: LinkedIn