In this scenario, a bakery has recognized the need to address its energy consumption, particularly its reliance on natural gas. The bakery has relied heavily on natural gas to fuel its ovens. While the site knows it uses large amounts of energy, the precise amount of energy and where it may be used is unknown. With better reporting tools and dashboards, the site will be able to better track their energy use.
Background
The bakery operates two production lines, each equipped with two ovens. To better understand and optimize their natural gas usage, flow sensors have been installed on all these gas-consuming assets. These sensors feed real-time data to ioTORQ. Over several weeks the bakery has collected data on their natural gas usage and are now hoping to analyze to identify trends and inefficiencies. The bakery's primary goal is to develop a comprehensive dashboard that provides a clear breakdown of natural gas usage by each asset and production line.
Natural Gas - Automatic and Virtual Variables
The first step is to create virtual variables that represent the summed flow rates, allowing for an accurate visualization of total gas usage. There are four automatic variables for natural gas flow in SCF/Min. To convert to volume in SCF, a virtual variable must be created for each. Below is an example for the Oven 1 Natural Gas Flow Rate (scfm) automatic variable.
The equation for this virtual variable is simple since the goal is to show volume in standard cubic feet. The main difference between the virtual and automatic variable for Oven 1 natural gas is the aggregation type. Average aggregation is being used for the automatic variable which is a flow rate and sum aggregation is used for the virtual variable which is a volume.
Once each asset has a virtual variable created for volume, a new total virtual variable can be created summing each of the assets per line to give a full comprehensive balance of the natural gas by line.
The aggregation type for this variable will be sum as well but the equation is more complex. This virtual variable is for the line as a whole, so it sums the totals from ovens 1 and 2. Then it is divided by 1000 to convert to mcf and multiplied by a BTU factor of 1.038 to convert to MMBtu.
Production Rates
With the line variables in MMBtu created, the next step is to convert the line production rates in lb/hr to productions totals in lbs. The production rate automatic variable is divided by 60 to convert the hourly rate into a total sum with minute frequency.
Intensity Variables
The last set of variables to create are the natural gas intensity variables where the total line natural gas is divided by the total production.
For these intensity variables, the aggregation type will be Ratio since the goal is to look at the quotient between the summed totals of each variable over time and not the average quotient. The below formula converts the energy units to Btu and divides by pounds of production for the line to create the intensity data in Btu/lb.
Creating Intensity Targets
Targets can be added to each variable to compare the process variable to some other metric. Targets can be used to set a threshold for good vs bad performance, observe variable trends over time, define a cutoff for setting an alert, provide visual comparisons against a benchmark value, and much more. The Targets overview section of the help center provides more details about each target type.
In this example, a target of natural gas intensity per pound of product will allow the site to track actual performance vs targeted performance. A simple Equation target will be added to each virtual variable with a constant value. In the variable below, a constant value of 300 btu/lb is set, and the "Show on graph" option is toggled, which will display a flat line to compare to the real time variable data.
Visualizing and Monitoring Natural Gas at a Line Level
With all preliminary data variables established, the bakery is ready to create a comprehensive dashboard to visualize their natural gas usage by line. This dashboard will allow them to track overall flow rates and compare the consumption of different natural gas assets within each production line. To achieve this, they will employ a combination of charts:
- a line chart with multiple variables to illustrate the total gas flow for each production line over time, and
- a donut chart to compare the gas volume used by individual assets.
First, overall graphs showing oven gas usage are created. To create a line graph, each of the four oven flow rates are selected - be sure to select variables with the same units. The Line Chart help center article provides more details about each setting.
Similar steps can be used to create a donut chart for the volume of gas usage for each oven in that time. In this case, the variables used are the total volumes of gas. This distinction is important because the Donut chart aggregates the data in each variable regardless of Frequency; selecting variables with units of flow rates will show a single average flow rate over the course of a month - a less useful metric than total volume of gas over a month. The Pie & Donut Charts help center article provides more details about each setting.
The first portion of this natural gas balance dashboard is now complete. The next section of this tutorial covers more detailed line-level monitoring.
Line-Level Natural Gas Performance
With gas intensity variables and targets for each line, charts can be created to visualize and compare performance.
Four charts will be used to show the efficiency of each line and oven.
- A simple line chart to show the intensity of the production line compared to its target. Create a line chart, add the appropriate variable, and be sure to select the corresponding target to display on the graph.
- A gauge chart to provide an instant read of "in spec" vs "out of spec" for operators. Create a new gauge chart, select the appropriate variable, and add the target created in a prior step. Gauge charts cannot be created without selecting a target. Gauge charts do not require a Frequency to be selected, as they will automatically aggregate the data over the selected timeframe to display a single value. The Gauge Charts help center article provides more details about each setting.
- A stacked bar chart comparing the natural gas usage of each oven on the line. Stacked bar charts are useful to see both total usage of a utility as well as the breakdown between multiple assets in a single chart. Unlike donut charts, bar charts have a Frequency selection to control how much data will be aggregated in each bar. The Stacked Bar Charts help center article provides more details about each setting.
- A matrix showing the last two weeks of values for each oven and the line intensity.
Leveraging the Data for Improved Efficiency
With comprehensive dashboards in place, the bakery can now use the data to drive efficiency and sustainability. The bakery can quickly see that one of their ovens is significantly less efficient than its counterpart and justify the investment in a new, energy-efficient oven.