Edge Application MELSOFT MaiLab

MaiLab

Edge Computing Software

MELSOFT MaiLab

Edge Application MELSOFT MaiLab

New value for production sites through data collection and utilization

MaiLab offers a variety of machine learning and statistical analysis methods, including AI features such as deep learning and multiple regression analysis so that data analysis can be used for various purposes.

In addition, no programming is required, making data analysis solutions easy to implement.

Although automation of equipment is advancing, there are still many processes that rely on the intuition and experience of on-site workers. By digitizing such knowledge, skill succession, dealing with labour shortages, cost reduction, improved productivity and quality, etc. can be achieved.

Mitsubishi Electric’s Data Science Tool MELSOFT MaiLab is a data science tool that further improves manufacturing by replacing “human experience and intuition” with digital technology and enabling it to be easily incorporated into control systems.

This software alone covers the phase of analysis of production data in the office and the phase of diagnosis in production based on these analysis results so that it is possible to apply the learning models obtained from data analysis directly online in the production.

One software for all types of data analysis

Edge Application MELSOFT MaiLab
Edge Application MELSOFT MaiLab 5

AI data scientist – an AI-based analysis supporting system for everyone

  • A very short training phase for the software as no specialized knowledge is required, anyone can do data analytics
  • MaiLab is supporting the customer in all phases of the data analysis project
  • Customers that lack manpower will benefit from MaiLab for data analyzing
  • Customers are empowered to improve their production efficiency quickly and efficiently

A UI bringing you data analytics with a great experience

  • Quick Return-on-invest as MaiLab Software is a single tool for both Offline Analysis and Real-time diagnostic including direct feedback to the production site. Rich possibilities for data visualization.
  • Longevity and future-proof design and operation of MaiLab through integrated open concepts like Python programming language or web-based environment.
  • Flexibility through different licensing schemes available (Yearly subscription for OPEX, perpetual model for CAPEX) and many different application scenarios.
Data Analytics

Data collection and diagnosis can be started in MELSOFT MaiLab with just a basic license. In addition, systems can be freely configured according to the scale of facilities, increases in the number of analysis users, etc. In the minimum operating environment, it is possible to execute methods such as multiple regression analysis, etc. with relatively low calculation processing when no other tools are running. To execute methods such as deep learning, etc. that require lots of calculation processing, the recommended operating environment is necessary.

Analysis Process

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

Offline analysis

Step 1: 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 human eyes can easily check it before performing a diagnosis using AI.

Step 2: AI creation

MailLab AI creation
Edge Application MELSOFT MaiLab 6

Learning from the data set is performed. A model enabling unknown data diagnosis 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”.

Real-time diagnosis

Step 3: Task creation

MailLab Task creation
Edge Application MELSOFT MaiLab 7

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.

Step 4: Task execution and monitoring

MailLab Task execution and monitoring
Edge Application MELSOFT MaiLab 8

You can execute tasks and monitor the diagnosis status of unknown data. Deployment to equipment can be easily performed with just a click. The learning server can confirm data flow and good or bad judgment status on a graphical display. To analyze the data and create the diagnosis model, it is necessary to register the data subject to analysis in MELSOFT MaiLab. A group of registered data is called a “data set”. By registering the data set, the data can be visualized in tables or graphs, and diagnosis models can be created.

When the data sources are multiple files, data sources can be combined and registered as a single data set. This is used in cases such as connecting both equipment data” measured by sensors at the time of manufacture and “inspection data” recorded from inspections after manufacturing and performing learning.

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