This feature is available only to organizations with a Gold license.
Galooli Analyst Dashboard provides better understanding of your data with AI-powered analysis delivered in a simple, straightforward manner.
The dashboard will display all possible insights, but only the insights relevant to the site will display the relevant data.
This dashboards containing Planners Dashboards forecast refueling and maintenance needs for improved site visit planning and higher uptime, using our AI tools that learn the usage patterns.
Due to the fact that this dashboard contains many items and cards, there for it has been divided into multiple several "sub-dashboards":
Overview
Fuel Insights
Generator Insights
Battery Insights
Solar Insights
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Refuel Planner
Maintenance Visits Planner
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This dashboard may be used on more than one unit or site. Different information will be displayed at the unit level and at the multi-unit level. If you wish to switch between the unit level and the multi-unit level, simply peak the relevant area of the organization tree, and the data will be updated automatically. |
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Unit Level Dashboard
Overview Sub-Dashboard
The Overview sub-dashboard focuses on a single unit and provides a detailed summary of the unit's current performance and issues.
It includes key metrics such as the unit's active events, data availability, and average daily energy consumption. The dashboard tracks event trends, displaying the frequency and types of issues detected by AI, such as refuel needs or battery anomalies. Additionally, it offers a breakdown of the site's energy mix, showing contributions from solar, generator, grid, and battery sources over time. This provides a comprehensive view of the unit's overall energy usage and operational health.
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Fuel Insights Sub-Dashboard
The Fuel Insights sub-dashboard for a single unit provides a detailed analysis of fuel consumption and data quality.
It includes key metrics such as the average fuel consumption rate, total fuel consumption, and data quality score. The dashboard identifies potential issues with fuel data, such as insufficient or irregular sensor readings, and provides recommendations for site assessment and sensor replacement. It highlights alerts for low fuel data quality, offering insights into fuel usage patterns and overall data reliability. This dashboard ensures accurate monitoring and helps maintain optimal fuel management and generator performance.
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Generator Insights Sub-Dashboard
The Generator Insights sub-dashboard for a single unit provides a detailed analysis of the generator's performance and load efficiency.
It highlights key metrics such as total engine hours, generator operating load, and redundant engine usage. The dashboard tracks generator performance trends over time, including how efficiently the generator is operating within recommended load ranges. Alerts for inefficient generator utilization and load patterns are displayed, alongside detailed descriptions of potential issues and suggested actions. Overall, the dashboard offers insights to optimize fuel consumption, prevent unnecessary generator operation, and enhance generator efficiency in hybrid sites.
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Battery Insights Sub-Dashboard
The Battery Insights sub dashboard for a single unit provides a focused analysis of the battery's performance and efficiency.
It includes key metrics such as the total battery discharge and charge energy, battery usage time, and underutilization alerts. The dashboard tracks battery usage trends over time, showing how much energy has been discharged and how long the battery was in use. Issues such as inefficient battery utilization are highlighted, with specific insights into how the generator and battery performed together, and recommendations are provided for resolving any inefficiencies. Overall, it offers a detailed view of the battery's health and performance in the context of a hybrid site.
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Solar Insights
TBA
Check out the following link for more information about the different cards - AI-Based Reports
Multi-Unit Level Dashboard
Overview Sub-Dashboard
The Overview sub-dashboard provides an overview of the system's current status by showing the total number of active events and affected units. It tracks event trends over time and highlights the most impacted units, helping prioritize attention. A breakdown of event distribution across units and detailed information on critical issues make it easy to identify areas needing immediate action. Overall, it enables efficient monitoring and quick decision-making.
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Fuel Insights Sub-Dashboard
The Fuel Insights sub-dashboard provides a focused analysis of fuel-related events and consumption across the system. It tracks the total number of active fuel-related events and identifies how many units are affected. Additionally, it monitors the total fuel consumption, offering insights into fuel usage efficiency.
The dashboard also provides a breakdown of fuel events by duration, distinguishing between newly activated events, long-standing issues, and units with no fuel-related problems. A trend analysis tracks the occurrence of fuel-related events over time, highlighting issues like urgent refueling needs or low fuel data quality.
Lastly, specific units with critical fuel issues are spotlighted, along with descriptions of the problems they are facing, making it easier to prioritize actions related to fuel management. Overall, this dashboard helps optimize fuel usage and address fuel-related operational challenges efficiently.
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Generator Insights Sub-Dashboard
The Generator Insights sub-dashboard focuses on monitoring and analyzing generator performance across the system. It provides a clear count of the total active generator-related events and the number of units affected by these events. Additionally, it tracks the total engine hours, which helps in understanding the usage and workload of the generators.
The dashboard offers a detailed view of the duration of generator events across units, categorizing them by how recently they were activated—from today to those active for more than a week. This segmentation aids in assessing the urgency and persistence of generator issues.
It also features a trend analysis of generator-related events over a defined period, highlighting fluctuations and identifying specific times with peak issues, such as inefficient generator load or maintenance needs.
Spotlighted units are specifically listed with detailed event descriptions, helping to prioritize which generators may require immediate attention or intervention. This dashboard serves as a tool for proactive maintenance scheduling and operational efficiency improvement.
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Battery Insights Sub-Dashboard
The Battery Insights sub-dashboard provides an overview of battery-related performance and events. It highlights the number of ongoing events and the units impacted by battery issues, giving insights into battery health and usage.
The dashboard tracks metrics like the percentage of average battery usage per day and presents trends for battery-related issues over time. Additionally, it categorizes events based on their duration and provides details about specific units experiencing battery issues.
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Solar Insights
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Refuel Planners Dashboards
Key Takeaways:
The dashboard displays the number of days left to refuel for each unit, and helps to prioritize which units needs to be refueled first.
In order to predict the number of days for refueling, the system analyzes the fuel consumption pattern and generator usage pattern for each one of the sites.
Multi Unit Display
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Less Than 1 Week Until Next Refuel
The number of units that required refueling within one week.
More Than 1 Week Until Next Refuel
The number of units that need to be refueled after one week.
Units Lacking Available Data
The number of units for which no data is available. To ensure accurate results, units must have valid data, including sensors availability and fuel consumption data for the past week.
Generators Average Fuel Consumption [Liter/Hour]
Average fuel consumption for generators refers to the amount of fuel a generator uses to produce a certain amount of electrical power over time.
5 Top Units in Need of Urgent Refueling
In accordance with the estimated days to the next refueling, here are five units that require an urgent refueling.
Estimated Days to Maintenance per Unit
Estimated days to maintenance per unit refers to the calculated time remaining before a specific generator or equipment requires maintenance. It is based on usage hours, load, and operational conditions, helping to predict when service is needed to prevent breakdowns and ensure efficient performance.
Single Unit Display
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Estimated Days to Empty Tank
Estimated Days to Empty Tank refers to the projected time remaining before a fuel tank is completely depleted. It is calculated based on the current fuel level and the average fuel consumption rate of the generator.
Generator KVA
The KVA category can be set in My Units –> Generators.Generator 1,2.KVA
Average Engine Hours per Day
The average generator run hours within the chosen time frame.
Average Fuel Consumption Rate
The average fuel consumption rate, based on the summary field Generator Load Based Consumption. Whenever there's an illogical result in the fuel consumption parameters, the field calculates an estimated consumption based on the generator's load and the KVA.
Fuel Consumption and Engine Hours Trend
The cumulative engine hours of the generator daily, coupled with the fuel level measured at the day's end (derived from the Generator Final Fuel Level summary field).
Total Consumption, Refuels and Drops
Consumption distribution based on refueling and drops.
Maintenance Visits Planner Dashboard
Based on predictive analytics, this dashboard determines the number of days until your generator requires a maintenance visit.
Key Takeaways:
In order to predict the number of days until maintenance, the system analyzes the generators’ run hours pattern for each one of the sites.
The dashboard displays the number of days left until maintenance for each unit, and helps prioritizing units that require immediate attention.
Required Configuration
To ensure accurate results, verify that units' maintenance requirements are properly defined in My Units > Configuration > Maintenance:
Next Maintenance Date, Next Maintenance Engine Hours – for generator 1
Next Maintenance Date 2, Next Maintenance Engine Hours (for generator 2, if exists)
For automatic updates of the maintenance configurations, it is recommended to use the “Generator Maintenance Update” automation - https://galooli.atlassian.net/wiki/spaces/KP/pages/2889744511/Automation+Scripts+List#Generator-Maintenance-Update
The automation will update the configurations fields automatically once the maintenance due hours are reached.
Multi Unit Display
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Less Than 1 Week Until Next Maintenance
The number of units that require a maintenance visit within one week.
More Than 1 Week Until Next Maintenance
The number of units that require a maintenance visit within more than one week.
Units Lacking Available Data
The number of units for which no data is available. To ensure accurate results, units must have valid data, including sensors availability and fuel consumption data for the past week.
Average Engine Hours
The average running hours of the generator per unit per day.
5 Top Units in Need of Urgent Maintenance Visit
In accordance with the estimated days to the next maintenance, here are five units that require an urgent maintenance visit.
Estimated Days to Maintenance per Unit
A list of all the generators selected by the user to appear on the dashboard, with details of the unit name, the number of days until the next maintenance, the current engine hours reading, and the next maintenance requirements (hours, date) as configured for the unit.
Single Unit Display
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Estimated Days to Next Maintenance
The number of days until the fuel in the tank runs out, based on the run hours patterns and the fuel consumption rate of the generator.
Generator KVA
The KVA category can be set in My Units –> Generators.Generator 1,2.KVA
Total Engine Hours
The total generator run hours within the chosen time frame.
Engine Hours vs Maintenance Due
The cumulative engine hours of the generator daily, compared to the maintenance due hours.