# Production context

Machine data shows **how** production happened. Order data shows **what** was produced. Together, they form the production context, which is the foundation for meaningful analyses.

## What machine data shows

Time series from controllers answer questions like:

* How fast was the machine running?
* What temperatures and pressures were present?
* When were there interruptions?
* How long did certain phases last?

## What machine data doesn't show

Without context, important questions remain unanswered:

* **Which product** was being manufactured?
* **For which order** was production running?
* **What product specifications** apply (setup sheet)?
* **Was an interruption** planned (changeover) or unplanned (breakdown)?

This information comes from the ERP or MES system and is transferred to ENLYZE as order data.

## What order data contains

An order describes a time period in which a specific product is manufactured on a machine. The key information:

| Attribute                 | Description                                   |
| ------------------------- | --------------------------------------------- |
| **Order number**          | Unique identifier of the production order     |
| **Product**               | What is being produced                        |
| **Start and end**         | Time range of the order                       |
| **Machine**               | On which equipment production takes place     |
| **Quantities** (optional) | Good quantity, scrap quantity, total quantity |

## Machine data + order data = production context

When order data overlays machine data as time windows, everything makes sense:

* A speed change becomes explainable because a product changeover took place.
* An interruption becomes recognizable as a planned changeover.
* The actual machine settings can be compared to the product specifications from the setup sheet.

## Analyses enabled by production context

| Analysis                   | Prerequisite                                           | Result                                       |
| -------------------------- | ------------------------------------------------------ | -------------------------------------------- |
| **OEE**                    | Machine data + order data + configuration              | Availability, performance, quality per order |
| **Setup sheet comparison** | Machine data + product specifications from setup sheet | Detect deviations from defined bounds        |
| **Product analysis**       | Machine data + order data                              | Compare all orders of a product              |
| **Energy KPIs**            | Power data + quantity data + order data                | kWh per kg, per order, or per product        |
| **Downtime analysis**      | Machine data + downtime categorization                 | Causes, durations, and frequencies           |

## Valuable even without order data

Order data is not strictly required. Even with machine data alone, many analyses are possible:

* Live monitoring of process parameters
* Historical trends and patterns
* Alerts on threshold violations
* Comparison of time ranges
* Correlation analyses between variables

Starting with machine data alone is sensible. Order data can be added later when the need arises.

{% hint style="info" %}
How to connect order data with ENLYZE is described under [IT-Connectivity](https://docs.enlyze.com/en/connect/it-connectivity).
{% endhint %}

## Related topics

* [Understanding OEE](https://docs.enlyze.com/en/concepts/understanding-oee): How OEE is calculated from the production context.
* [IT-Connectivity](https://docs.enlyze.com/en/connect/it-connectivity): Connecting order data (guide).
* [Downtimes](https://docs.enlyze.com/en/concepts/downtimes): How downtimes are classified in the production context.