Analyzing Downtime Data with the Amper Explore Tool


Once you start collecting Downtime reasons, you will be able to view & analyze them in the Amper web app. This article will go over how to use the Explore tool to view your downtime data.

Navigating to the Explore Tool

To open the Explore module, log into your Amper web app and select Explore from the bar on the left hand side of the page.


You will be presented with different categories within the Explore module. Press Downtime.


Setting Explore Parameters

Before diving into your data, you must select the appropriate parameters based on the information you are looking for.

There are three main parameters to set before viewing your data:

  • Machines
  • Date Range
  • Grouping by Day or Week


In the example above, the user has chosen to view the Downtime Codes for all of their factory's machines from 03/03/2020 to 03/06/2020 and we would like to see the Downtime grouped by day.

Grouping Data by Attribute

Once you have your parameters set, it is time to start diving into the data. Just below the date selector you will find two buttons to select whether you want to view the Total or the Average length of the Downtime Periods for the specified attribute.


Below these button you will find three sets of graphs, each with a parameter for the graph in that section to be grouped by.


Multi-Level Groupings

A powerful feature of the Amper Explore module is the ability to combine these groupings and filter data by selecting entries on the graphs. Lets look at an example with the parameters we specified earlier:


From the Date graph, we can see that one day has a higher amount of Downtime than the others. If someone is interested in seeing if one shift had a greater amount of downtime than the other, they can simply click on the date of interest and selecting Shift as the group by on our second level graph we have quick insight into our Downtime Amounts that day by shift.

You can use any combination of available groupings to fit your specific analytical needs.

Best Practices for Viewing Downtime Data

The Downtime Explorer tool is a great way of both getting an overview of your data and also being able to dive deep into specific data. 

Below are some common ways to view your downtime data, so your staff can start uncovering valuable insights.

Downtime by Reason

Looking at Downtime by reason Helps to identify the leading cause for downtime at the facility and help you to identify solutions to lower the amount of downtime or eliminate it all together

Sub Reasons to investigate:

  • Date>Reason>Sub-reason

Downtime by Machine

Downtime by machine helps to identify which machines would benefit the most from an improvement project.

Sub Reasons to investigate:

  • Machine>Reason>Sub-Reason
  • Machine>Reason or Sub-Reason>Operator
  • Machine>Reason or Sub-Reason>Shift

Downtime by Date

Looking at Downtime by date helps to identify the days or period of time that your factory had more downtime than usual.


Data can be grouped by day or week. When you view by weeks, it's easier to dive into larger sets of data and identify trends.

Sub-Reasons to investigate

  • Date>Shift>Machine
  • Date>Shift>Operator
  • Date>Shift>Part

Downtime by Shift

Downtime by shift helps to identify which shift is having the largest downtime and whether it may be a staffing or training issue.

Sub Reasons to investigate:

  • Shift>Machine>Reason or Sub-Reason
  • Shift>Machine>Operator

Downtime by Part

Looking at Downtime by part you can identify which parts cause the most downtime and identify the reasons associated with it.

Sub Reasons to investigate:

  • Date>Part>Operator
  • Date>Part>Machine

Downtime by Operator

By looking at Downtime by operator, you can identify which operator is causing most downtime, which may allow you to assign them to another set of machines or offer additional training.

Sub Reasons to investigate:

  • Operator>Machine>Reason or Sub-reason
  • Operator>Part>Reason or Sub-reason