> For the complete documentation index, see [llms.txt](https://help.tillit.cloud/tillit/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.tillit.cloud/tillit/planning/data-gathering/shifts-and-caledars.md).

# Shifts & Calendars

### **Shift templates**

A production shift refers to a scheduled period of time during which a manufacturing or production facility operates. A typical production shift may last between six to twelve hours. Production shifts are often structured around specific products, processes, or customer demand, and are typically organised around a fixed schedule that covers a 24-hour period, with multiple shifts covering different times of day.

In TilliT, a shift refers to a specific period of time during which workers are scheduled to perform a particular set of tasks.

For example: A morning shift that runs from 8:00 am to 12:00 pm with a 15-minute break, followed by an afternoon shift that runs from 1:00 pm to 5:00 pm with a 15-minute break.

**Take note of the details of each shift** which may include information such as the specific tasks or activities to be performed during the shift, the equipment or tools required, and any safety procedures that need to be followed.

These details will later on be transformed into Shift Templates. By using Shift Templates, managers and workers can also identify trends and patterns in production or performance, enabling companies to make data-driven decisions and optimise their operations over time.

### Calendars

In TilliT, calendars are used to define how the Shift Template will be applied, such as the days of the week it runs, and the validity start and end dates.

Once shifts and calendars are set up in TilliT, they can be assigned to specific assets, such as equipment or machines. This enables the calculation of availability for Overall Equipment Effectiveness (OEE) and allows activities to be triggered at the start and end of each staff shift pattern.

{% hint style="info" %}
*To get the most accurate OEE, we need to be able to exclude planned downtime events.*
{% endhint %}


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