MaiLab
Edge Computing Software
Edge Application MELSOFT MaiLab
New value for production sites through data collection and utilisation
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 digitising 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 production.
One software for all types of data analysis
AI data scientist – an AI-based analysis supporting system for everyone
- A very short training phase for the software, as no specialised knowledge is required; anyone can do data analytics
- MaiLab is supporting the customer in all phases of the data analysis project
- Customers who lack manpower will benefit from MaiLab for data analysing
- Customers are empowered to improve their production efficiency quickly and efficiently
A UI bringing you data analytics with a great experience
- Quick Return-on-investment as MaiLab Software is a single tool for both Offline Analysis and Real-time diagnostics, including direct feedback to the production site. Rich possibilities for data visualisation.
- Longevity and future-proof design and operation of MaiLab through integrated open concepts like the Python programming language or a web-based environment.
- Flexibility through different licensing schemes available (Yearly subscription for OPEX, perpetual model for CAPEX) and many different application scenarios.
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, a 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 analysed into MELSOFT MaiLab and register it. 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
Learning from the dataset 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
Settings for performing the 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
You can execute tasks and monitor the diagnosis status of unknown data. Deployment of the 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 analyse 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 dataset, the data can be visualised in tables or graphs, and diagnosis models can be created.
When the data sources are multiple files, the datasources can be combined and registered as a single dataset. 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.