02 OEE Dashboard

OEE dashboard with the productivity-metrics endpoint.

In this tutorial you build a department dashboard with aggregated OEE metrics, production status for every machine, and a department overview:

What you will learn

• Configure POST requests with the productivity-metrics endpoint

• Create hidden time variables with 10-minute alignment

• Display OEE metrics as a table with color scale

• Visualize machine activity as a state timeline

• Calculate weighted OEE aggregation for department overviews

Prerequisites

• Query the ENLYZE API and Variables completed

• Understanding of transformations (Tutorial 3.2)

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10-minute alignment

The productivity-metrics endpoint requires time ranges aligned to 10-minute intervals (minutes: 0, 10, 20, 30, 40, 50; seconds and milliseconds: 0).

When users select a time range such as "Last 7 days" in Grafana, the time values contain arbitrary seconds. Create two hidden query variables that round the time values automatically.

Create time variables

Create a new dashboard and add two variables under Settings > Variables:

Setting	start	end
Name	start	end
Type	Query	Query
Data source	ENLYZE API	ENLYZE API
Hide	Variable	Variable
Refresh	On time range change	On time range change
Source	Inline	Inline
Data	{"time": ${__from}}	{"time": ${__to}}

Root selector (JSONata, identical for both variables):

(
  $time_millis := $number($.time);
  $time_rounded := $time_millis - ($time_millis % 600000);
  $fromMillis($time_rounded)
)

The expression converts the timestamp to milliseconds, rounds down to the nearest 10-minute interval, and converts back to an ISO date.

For simpler dashboards you can also round to full hours: ${__from:date:YYYY-MM-DDTHH:00:00}+00:00. The 10-minute rounding is more precise, though, and works with all ENLYZE API endpoints.

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OEE by machine (table)

The table shows OEE, Availability, Performance, and Quality for each machine in the department.

Configure the POST request

Create a Table panel and configure the first query:

Setting	Value
Type	JSON
Parser	Backend
Method	POST
URL	machines/141e0927-62b3-4e76-8398-ad82d20f397f/productivity-metrics
Body type	Raw
Body content type	application/json

Body:

{
  "datetime_ranges": [
    {
      "start": "${start}",
      "end": "${end}"
    }
  ]
}

Make sure the Body content type is set to application/json (not text/plain). Otherwise the API responds with HTTP 422.

Columns and computed columns

Set the Root Selector to $.data and add the following Columns under Parsing options & Result fields:

Selector	Title	Type
productivity.score	productivity	Number
availability.score	availability	Number
performance.score	performance	Number
quality.score	quality	Number

Add two Computed Columns to identify the machine:

Selector	Title	Type
"141e0927-62b3-4e76-8398-ad82d20f397f"	machine_uuid	String
"Kiefel"	Machine	String

Additional machines

Repeat the query for each machine in the department (Macchi, Alpine, Reifenhäuser, W&H Varex). Change the UUID in the URL and in the computed columns accordingly.

Transformations

1. Merge combines all queries into a single table

2. Organize fields hides machine_uuid and renames the columns (productivity to OEE, availability to Availability, etc.)

Visual styling

Configure the table under Standard options:

• Unit: Percent (0.0-1.0)

• Color scheme: Continuous - RdYlGr

• Min: 0, Max: 1

Create Field Overrides for the OEE, Availability, Performance, and Quality columns:

• Cell type: Gauge (basic, color display)

Enable the Table Footer with Calculation Mean for the department averages.

Add a Value mapping:

• Type: Special > Null

• Display text: NO DATA

• Color: Text

Not all machines provide quality data. In the demo account, Quality is 1 (100%) for all machines. The null mapping ensures that machines without data in the selected time range show "NO DATA" instead of an error.

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Machine activity (state timeline)

The state timeline shows at a glance when each machine was in production and when it was idle.

Use the ENLYZE data source

Create a State Timeline panel with the ENLYZE data source (not ENLYZE API). Create a query for each machine and select the Durchsatz (throughput) variable.

Configure Field Overrides for each query (by Frame refID) to set the Display Name to the machine name (e.g. "Kiefel", "Macchi", etc.).

Value mappings

Create two range mappings to convert the throughput value into an operating status:

From	To	Text	Color
-1000	1	IDLE	Red
1	10000	PRODUCING	Green

The logic: if throughput is at or near 0, the machine is idle. If it is above 1, it is producing.

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Department overview

Four stat panels show the aggregated OEE metrics for the entire department: OEE, Availability, Performance, and Quality.

OEE and Availability (mean)

Create a Stat panel for the Department OEE. Configure 5 queries (one per machine) with the same POST requests as in the table, but with a different root selector and columns:

• Root Selector: $.data

• Column: productivity.score as "OEE" (Number)

Add a Merge transformation. Under Value options > Calculation, select Mean.

Configure:

• Color mode: Background

• Unit: Percent (0.0-1.0)

• Thresholds: Red (base), Yellow (0.6), Green (0.8)

• Value Mapping: null to "NO DATA"

Create a second panel for Availability following the same pattern, with Column availability.score.

Performance and Quality (weighted)

For Performance and Quality, a simple mean is not sufficient. When machines run for different amounts of time, the values must be weighted by Availability.

Formula:

$$\text{Dept. Performance} = \frac{\sum_{i} \text{Availability}_i \times \text{Performance}_i}{\sum_{i} \text{Availability}_i}$$

Create a Stat panel for Performance. The 5 queries use a JSONata root selector:

$map($.data, function($v) {
  {
    "avail": $v.availability.score,
    "weighted_perf": $v.availability.score * $v.performance.score
  }
})

Each query returns the Availability and the weighted product (Availability x Performance).

Transformations:

1. Merge combines all queries

2. Reduce with Mode Reduce fields and Calculation Sum sums both columns

3. Add field from calculation with Mode Binary operation: weighted_perf / avail, Alias "Performance", Replace all fields enabled

For Quality, follow the same pattern with this root selector:

$map($.data, function($v) {
  {
    "avail": $v.availability.score,
    "weighted_quality": $v.availability.score *
      ($exists($v.quality) ? $v.quality.score : 1)
  }
})

The $exists fallback ensures that machines without quality data are treated as Quality = 1 (100%).

The weighted aggregation ensures that machines with high availability contribute more to the department metrics than machines that barely ran. For more on OEE calculation, see the ENLYZE documentation.

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Tips

• 10-minute variables: The hidden start and end variables work in any dashboard that uses the productivity-metrics endpoint. Copy them to other dashboards as needed.

• production-runs vs. productivity-metrics: Use production-runs (GET, Tutorial 4.2) for OEE per production run. Use productivity-metrics (POST) for aggregated shift or daily reports.

• 422 Unprocessable Entity: The time values are not correctly aligned. Check the hidden variables and make sure the body content type is set to application/json.

• Single machine: For a dashboard with the live status of a single machine, see Production status dashboard.

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Next steps

• Downtime reporting -- Analyze and visualize machine downtimes