---
title: "Time-based Wear Computation"
slug: "time-based-wear-computation"
updated: 2024-10-23T13:42:48Z
published: 2024-10-23T13:42:48Z
canonical: "learn.servitly.com/time-based-wear-computation"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://learn.servitly.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Time-based Wear Computation

Calculates the wear level of a machine component based on hours of use.

This algorithm takes as input the number of hours a certain component has been used, typically you can use the [Working Time](/docs/working-time-1). Based on standard usage plus a tolerance it returns the wear value reached, which is saved together with the new total of working hours.

An insight metric based on this algorithm is calculated daily, so the input usage metric must provide the amount of working time in milliseconds, during the previous day.

> [!WARNING]
> This feature is available for the following modules:
> 
> VALUE-ADDED DIGITAL SERVICES, CONNECTED FIELD SERVICES, SMART SPARE PARTS & CONSUMABLES

## Inputs

Here is the list of inputs required by this Algorithm.

|  | INPUTS |
| --- | --- |
| *Usage Time Metric* | The metric providing the daily usage time in milliseconds. Type: METRIC **\|** Mandatory **\|** Default: Working Time **\|** Dataset Range: Last 24 hours |

## Outputs

Here is the list of outputs provided by this Algorithm.

|  | OUTPUTS |
| --- | --- |
| *Usage* | The reached usage since the last replacement. Type: FLOAT |
| *Wear* | The reached wear level since the last replacement. Type: FLOAT |

## Wear Metric Configuration

To use this Algorithm in a [Wear Metric](/docs/wear-metrics), you need to:

1. Go to the *Insight / Wear Metrics* page.
2. Select the *Thing Definitions* tab.
3. Select the Thing Definition where to create the wear metric.
4. Click the Add Metric button.
5. Select the *Time-based Wear* algorithm.
6. Configure the required inputs.