How To Analyze Quality Inspection Checklists with a "Multiple Variables" Analysis

How To Analyze Quality Inspection Checklists with a "Multiple Variables" Analysis

Use this guide to analyze the common points of failure in a quality inspection.

In Tulip, a "quality inspection checklist" is usually composed of a series of steps with images and descriptions, and then a "Pass" and "Fail" button.

Like this:

This can be organized in an individual app, or in a step group at the end of a work instructions app, for example.

Either way, after operators have been using this digital inspection for a few days, you will be able to see the common reasons that parts fail inspection.

With this data, you should be able to improve the design of your product, or improve a specific step in the manufacturing process that is leading to defective parts.

This guide will show you how to analyze the results of your quality inspection checklist in a line chart format.

Before using this guide, you should understand the concept of "app completions because that is how data will be generated from the app.

Structuring Your App

In a quality inspection checklist, you will want to use a separate variable to track the results of each step in the quality inspection. That way, you can track each step individually and visualize the pass/fail rate independently.

So, in the example shown above, here is the logic that might run when an operator presses the "Matches" button.

• "Data Manipulation" "Store" data: "Static Value" "boolean" "yes" location: "fan_check"
• "Go To Step" "Next"

On the "Does Not Match" button, you could use the same logic, but store "boolean" "no" instead. Then, you might send an operator to the next step or into a series of rework steps.

You can repeat this patten across every step with a different variable on each step. Here's how you might store the result when a part fails the thickness measurement step.

• "Data Manipulation" "Store" data: "Static Value" "boolean" "no" location: "thickness_measurement"
• "Go To Step" "Next"

At the end, you should have a new variable for each step.

Structuring The Analysis

You could create multiple kinds of analyses with this data. In this case, we want to see which quality checks fail most often. This will help us pinpoint issues in our manufacturing process.

To accomplish this, we need to compare the boolean variables that are being tracked on each step.

In the app of your choice, click the "Analytics" tab on the App Summary View, then choose "New Analysis".

Then, choose the "Compare Variables" analysis and choose the "Compare Boolean Variables" option:

You will see 6 options in the Context Pane:

In this case, we will focus on the "X Axis" and "Y Axis" fields.

Click the "X Axis" field , and then select all the boolean variables from the app that are related to quality inspections. In the example below, we will select three variables.

Each of these variables will now appear as a separate bar in a bar chart. To change the format to a line chart, select the "Display" dropdown at the top and choose "Line Chart".

Next, let's adjust the Y axis. Select the "Y Axis" field, and you will see two options.

We will continue to use "Percent Where True". This will show the percentage of app completions where each variable was set to "true". If the percentage is low, that means that the particular check does not pass the quality inspection test very often.

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