Analytical Process

Analysis Process

Easy analysis/diagnosis in 4 steps

MELSOFT MaiLab is a tool that enables easy data analysis in 4 basic steps.

Data collection

Data collection

Examine what data should be collected and how they should be collected.

Offline analysis

Data set creation

First, read the data to be analyzed into MELSOFT MaiLab and register them. A group of registered data is called a “data set”.
The data set can be shown in various kinds of graphs, so that it can also be easily checked by human eyes before performing diagnosis using AI.

First, data visualization.
Graph displays for easy understanding.
(Go to Offline Analysis)

AI creation

Learning from the data set is performed.
A model that enables diagnosis of unknown data is called “AI”.
When “What you want to do (objective)” is selected, the regularity and rules of the data are automatically derived, and MELSOFT MaiLab creates the “AI”.

AI for automatic support.
Automatic AI creation from what you want to do.
(Go to Offline Analysis)

Real-time diagnosis

Task creation

Settings for performing diagnosis of unknown data are called a “task”.
MELSOFT MaiLab will define the data input/output methods and threshold values for whether diagnostic results are good or bad. The accuracy is displayed as a score, which serves as a guideline for judgment.

Create tasks from learning.
Scores and contribution rate make accuracy also clear at a glance.
(Go to Real-time diagnosis)

Task execution and monitoring

You can execute tasks and monitor the diagnosis status of unknown data.
Deployment to equipment can be easily performed with just a click. Data flow and good or bad judgment status can be confirmed on a graphical display via the learning server.

Linking with site is also easy.
Apply to equipment with a single click.
(Go to Real-time diagnosis)

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