List of widgets

The aim of this article is to introduce the various widgets and give a brief explanation of their usefulness. Modifying each widget is covered in the article Parameterising a widget.

Time series

This widget allows you to view the evolution of one or more datasets over time. You can choose different types of display: curves, bars, levels, areas, etc. Two Y axes can be used.

When to use it: to graphically display values ​​that evolve over time, and to possibly compare them to other values ​​(historical data, targets, etc).

Examples of use:
- daily gas consumption over a year
- average temperature hour by hour of an oven over a month
- evolution of the power of a compressor over a week, compared to the flow of compressed air produced
- visualization of the consumption base load

Timeseries Table

This widget displays the numerical values of one or more datasets, ordered by date.

When to use it: to digitally display values ​​that change over time, and to possibly compare them to other values ​​(historical data, targets, etc).

Examples of use:
- monthly steam production
- total weekly electricity consumption
- daily quantity of parts produced
- daily performance indicator (kWh/part) with colored dot according to an objective

Scatter Plot

This widget allows you to display data on two or three axes: X, Y and Z. This allows one set of data to be viewed in relation to another set of data. The third Z axis can be displayed using the colour gradient. It can be used in 2 different ways:

• display one dataset in X and several datasets in Y
• display one dataset on each axis (X, Y, Z=colour scale) to represent up to 3 dimensions

When to use it: to analyze the influence of one parameter on another, and possibly to define a mathematical relationship between these two parameters.

Examples of use:
- gas consumption (Y) depending on the outside temperature (X)
- gas consumption of a boiler (Y) depending on the pressure (X)
- electricity consumption of a cooling unit (Y) depending on the chilled water produced (X), colored by the outside temperature (Z)

Proportion graph

This widget allows you to view the relative share of multiple datasets compared to the sum of those datasets.

When to use it: to display the distribution of a quantity and identify the most important parts.

Examples of use:
- distribution of electricity consumption by workshop
- Share of CO2 of each energy in the total consumption of the factory
- share of consumption baseload in total consumption

Statistic

This widget allows you to perform aggregation calculations on a meter or formula using existing statistics functions. The statistic can be a sum, an average, a maximum, a minimum, a standard deviation, etc.

When to use it: to calculate a total, average, or other statistics over a period. It can also be used to display any important indicator.

Examples of use:
- total electricity consumption over the month
- average efficiency of a boiler
- average daily compressed air production ratio
- difference in consumption compared to the previous year

Statistics chart

This widget displays, in histogram form, one or more statistics for one or more datasets. Datasets are displayed on the X axis, and statistics are displayed on the Y axis. Statistics can be a sum, an average, a maximum, a minimum, a standard deviation, etc.

When to use it: to graphically display statistics across multiple data streams, and be able to visually compare them to each other.

Examples of use:
- total consumption of the different cooling units in the building
- statistics on the temperatures of three ovens

 

Statistics table

This widget allows you to calculate and display in tabular form one or more statistics for one or more datasets. The statistics can be a sum, an average, a maximum, a minimum, a standard deviation, etc.

When to use it: to digitally display statistics across multiple data streams, and be able to compare them numerically with each other.

Examples of use:
- total consumption of the different cooling units in the building
- statistics on the temperatures of three ovens

Correlation matrix

This widget calculates and displays in matrix form the correlation coefficients between several datasets.

When to use it: to analyze the influence that each parameter has on many other parameters, and visually identify links of significant influence.

Examples of use:
- analysis of the links of influence between the different parameters of a production line
- analysis of the influence of meteorological factors on different energy consumption

Text and images

This widget is a free text area, in which it is possible to write text, insert images, add hyperlinks, display variables, etc. The widget can also contain dataset statistics, dynamically calculated over the defined step and time range.

When to use it: to add a title, description, image, comment, etc. It also allows you to add dates to a PDF report.

Examples of use:
- title and dates of the monthly electricity consumption report
- comments area to complete before generating the compressed air report
- image of the steam distribution plan in the factory

Sankey

This widget allows you to represent the distribution of the sum of the values of several datasets in a hierarchical structure.

When to use it: to visualize the distribution of consumption and the metering structure (counters and sub-meters).

Examples of use:
- distribution of general electricity consumption
- share of each item in total CO2 emissions

Speedometer

This widget displays the result of a statistical calculation (sum, average...) on a data set, located between minimum and maximum boundary values. Coloured areas based on numerical thresholds can also be configured.

When to use it: to display an indicator and check that it does not exceed one or more value thresholds (limits, objectives, etc).

Examples of use:
- Specific consumption KPI (kWh/part) with a minimum objective
- performance of a compressor (Wh/Nm3) compared to the standard performance of 120 Wh/Nm3
- average pressure per hour within minimum limits of 6.9 bar and maximum of 7.1 bar

Heatmap

This widget displays the values of a dataset, in the form of colours, grouped by time interval. For the X and Y axes, select the time range to be displayed. For X, this can be hours, weeks, or months and for Y, days of the week, months, days of the year or weeks.

Finally, it is possible to define value thresholds for colour gradients.

When to use it: to have an overview of periods of intense consumption.

Examples of use:
- Heatmap of the average power called per hour over a week
- Intensive water consumption map: hourly consumption over the week
- Gas consumption per week over the year

Histogram

This widget can be used to represent the statistical distribution of values in one or more datasets.

The X axis represents the different classes (rectangles) in the dataset. Changing the number of classes refines the granularity of the X axis.

The Y axis represents the number of occurrences of values present between the lower and upper bounds of the class.

When to use it: to analyze the ranges of values ​​in a data flow.

Examples of use:
- Compressor power zones in operation
- Distribution of the pressure level in the steam network

Waterfall chart

This widget lets you visualize the relative share of several datasets in relation to the whole dataset. The distribution can be based on a sum or another statistic (average, number of points, etc).

The X axis represents the different datasets. Datasets can be arranged in ascending or descending order.

The Y axis represents the share of each dataset, cumulated with the other shares until the total of these datasets is reached (the sum of the total, the average of the total, etc.).

The percentage of each share in the total can be displayed. Similarly, zero values can be ignored in the distribution calculation.

NB: The waterfall graph can fulfil the same role as the proportion graph. It takes up more space, but improves the readability of small values.

When to use it: to visualize the distribution of consumption between several consuming elements.

Examples of use:
- Breakdown of total consumption by site
- share of each compressor in the total electricity consumption for compressed air

Synoptic

This widget allows you add dynamically calculated statistics to a background image.

This widget does not have an axis; each set of data is added in a cell that can be freely placed in the widget area. The data can come from meters or formulas, and can be coloured using conditional formatting.

When to use it: to get an overall view of a process, with dynamic indicators for each part of the process.

Examples of use:

• Overview of the electricity consumption of workstations on a process line
• Monitoring temperatures and pressures in a steam network
• Monitoring boiler inlet and outlet parameters