Research Information Management for Process Industries:BIOVIA Notebook/BIOVIA Pipeline Pilot

B-EN-G will contribute to promoting the digitalization of R&D departments by supporting the implementation of Dassault Systèmes' "BIOVIA Notebook" and "BIOVIA Pipeline Pilot" for customers dealing with functional materials. In addition, we will support the creation of a manufacturing process data collection platform, data integration with ERP and MES, and the creation of a platform for digitalization in the processes of prototyping, mass production, and manufacturing process improvement, as well as the utilization of data science.

Overview

"BIOVIA" is one of the brands offered by Dassault Systèmes, and provides solutions to the research and development departments of the materials science industry. It is used in a wide range of industries, including chemicals, materials, daily necessities, food and beverages, cosmetics, batteries, semiconductors, electronic components, pharmaceuticals, and tires and rubber. BIOVIA has a history of over 25 years as a product and is used by more than 2,000 companies and more than 1.4 million users around the world.
Based on the concept of "Virtual Twin," we aim to shorten and accelerate research and development by combining scientific tools (Virtual Lab) with scientific data management and lab solutions (Real Lab), and turn dark data into reusable knowledge, enabling more models to explore more options and fewer tests and experiments to avoid expensive routine work and duplication.

function

BIOVIA Notebook: This is an electronic experiment notebook that records the purpose, procedure, results, and considerations of experiments, and also centrally records and accumulates ideas, research data, and experimental processes.
It supports drag-and-drop file insertion, powerful search functions (searching between notes, within attachments, and for chemical structures), template creation, and handling of chemical structures and reaction formulas.

BIOVIA Pipeline Pilot: This is data science software that allows you to create data processing and analysis protocols, including statistical analysis and machine learning, using low code.
It has functions such as data extraction and merging, property calculation and filtering, report creation, predictive modeling, and image analysis.
Data from electronic experiment notebooks can be automatically extracted and used to build business support processes, such as automatically creating weekly and monthly reports, and can also be used for analysis using data science and AI (property prediction, formulation optimization, etc.).

Features

■ Integrated management and database creation of research data
Using Notebook as a central point, you can centrally manage experimental records and related data that tend to be scattered, and build a knowledge database that is easy to use. You can attach files in various formats, and perform powerful searches by keywords, tags, and chemical structures.

■Intuitive and easy-to-use interface
Notebook in particular has a simple and intuitive interface, making it easy to get started.

■ Utilizing data through collaboration with data science and AI
By linking with Pipeline Pilot, experimental data and related data accumulated in Notebook and other systems can be automatically extracted and processed, and used for materials informatics (MI) using data science, AI, etc.

■ Compliance support
With features such as proof of fairness and authenticity of experiment records, intellectual property protection, electronic signatures, and audit capabilities, it helps you meet strict regulations and compliance requirements.

Implementation Results

■ Shortening and accelerating research and development time
By streamlining processes, quickly sharing information, and promoting data utilization, we can shorten product development times and speed up research and development.

■Improve business efficiency and reduce costs
It reduces the workload of researchers by reducing the time spent searching for information and recording work, and automating routine tasks.

■ Sharing and passing on knowledge and know-how
Sharing research records and knowledge across the organization prevents information from becoming personal and makes it easier to pass on technology.

■ Maximizing data utilization
By utilizing systematically accumulated data in data science and AI, we can gain new knowledge and discover optimal solutions, maximizing the value of research data.

B-EN-G Implementation Support Services

Total digitalization support for product development

B-EN-G supports the construction of a digital infrastructure for the research, development and mass production of functional materials.
In addition to providing BIOVIA digital transformation support for R&D departments, we also offer solutions to support digital transformation for the entire manufacturing process, including the deployment of process informatics, in combination with the introduction of ERP, MES, LIMS, and historian products, as well as support for the digitalization of manufacturing sites (smart factories).