The OSS dashboard provides an overview of the metrics used to value the performance of all devices.

You can determine the period of time that the report will cover. We are choosing the last week and selecting the scheduler view.

Below are some tips to review the metrics at a glance:

Comfort

• Comfort index tells you how close you were to your setpoint goals at the target time. 

• Comfort lost indicates you were late to reach a setpoint even though you might have been close.

• Zones on Setpoint tells you % of zones that were exactly inside setpoint range. Devices that were off 0.1 degrees are counted as being off setpoint.

Runtime Lost

• Runtime lost indicates equipment that reached setpoint too early and therefore ran for extra runtime.

Outliers

• Outliers indicate which zones took more than 3 hours to reach setpoints. This equipment should be reviewed.

OSS Score

• OSS Score allows you to monitor how well OSS algorithm is balancing comfort while saving device runtime 

These metrics provide indicators for how OSS has performance at glance to dive deeper into the performance walk through the charts below.

OSS Score Trend Chart

Our first chart is the OSS Score Trend which can be used to understand how the key metrics of comfort lost and runtime lost vary overtime.

If you wish to select a specific trend to display, you can hide trends through clicking on their legend, and the y-axis will scale according to the trends you select.

Comfort Index Chart

The Comfort Index chart helps you understand where in your building (by area or by schedule) you have comfort issues or optimal comfort. The comfort lost bars will tell you which equipment is reaching setpoint the latest, but should be kept in mind with the overall comfort index which communicates how close you were to setpoint if not exactly in the range. Hovering over a specific bar will display the details of the device's performance related to comfort.

The following chart shows how many zones were outside the target setpoint range at the occupancy start time. It also shows how many devices failed to reach setpoint after being on for at least 3 hours (outliers). These areas should be investigated in more detail using the bubble chart below.

Temperature Recovery Chart

Use the bubble chart to review specific equipment and how long it took it to reach setpoint according to the temperature difference it had to overcome. Optimal buildings will see most devices in the bottom left corner. If a zone is 0 min, a possible explanation is that a setpoint was changed between when the OSS prediction was made and when OSS started the device.

Savings Chart

If your interest is runtime savings before and/or after OSS, use the savings chart below. There are two different scales for runtime lost and savings both in minutes. You should be able to  select which one is of interest by clicking on the legend. The runtime lost is ordered from scheduler/are with lowest runtime lost to highest.

All together these graphs can quickly identify devices that score low on comfort level, devices that can improve in runtime savings. 

Device Start Time

This table shows device start times, offering insights based on your specific filters—the scheduler or designated areas. Hover over your area of interest to discover the first device start time, median time, and last device start time.

Device Details Table

To get the full picture for either one device or more, the Device Details table groups all the metrics used in the above chart for each device to ease the troubleshooting process: scheduler, area, metric scores. You can order the devices by any score in ascending or descending order. Clicking on a header will order the devices. By default, the OSS dashboard displays devices ordered by the Scheduler.

Clicking on the devices will open a new tab with the device’s trend.

Select the trend lines to review the points of interest. In this case we are looking to follow zone temperature and its lower and upper limits setpoints (occ cooling and occ heating temp setpoints).

You can analyze individual device trends. This is particularly useful for understanding outliers and other equipment issues.