Kukdo Chemical

Our world is held together by chemical materials. Epoxy resins and polyurethanes are used to strengthen bridges, marine-grade coatings defend vessels from corrosion, acrylic materials insulate buildings and high-purity resins protect the electronics that are a vital part of modern life.

One company that specializes in developing these chemical materials is Korea-based Kukdo Chemical, a leading epoxy resin manufacturer. Since 1972, it has led the way in material science and engineering, supplying high-functioning products that are indispensable to many of today’s most advanced industries, including electronics, automotive, construction, mobility and energy.

As the importance of leveraging artificial intelligence (AI) continues to grow, Kukdo Chemical has launched a major transformation of its research and development (R&D) operations to keep up with the pace of change – all enabled by Dassault Systèmes’ 3DEXPERIENCE platform.

As its global footprint expanded, Kukdo Chemical recognized that its traditional, document-based approach to research could limit its ability to innovate in the future.

Without a centralized way of managing information, its research data was stored on personal devices in disconnected files, with some findings remaining as handwritten notes. This made it difficult to trace important past experiment records or confidently reuse previous work. Differences in terminology use – sometimes notes were made in English, sometimes Korean, sometimes an acronym – meant that identical raw materials were often recorded in multiple ways, undermining the consistency needed for meaningful analytics.

This fragmented way of working led to repeated experiments, slower development cycles and a loss of valuable know-how whenever experienced researchers moved teams or retired. It also made it challenging to understand how a change in raw materials or supplier might affect product performance – a critical capability in highly regulated markets. 

Following a thorough evaluation of the software available on the market, Kukdo Chemical chose the 3DEXPERIENCE platform, recognizing its proven track record in the manufacturing industry. The implementation was supported by local Dassault Systèmes business partner Atis System, who provided in-depth assistance from the outset, holding a series of comprehensive meetings with Kukdo Chemical to understand its requirements and determine which Dassault Systèmes applications would best meet them.

Following this initial customer engagement and requirement mapping stage, Atis System was able to help Kukdo Chemical leverage the 3DEXPERIENCE platform as the basis for a comprehensive R&D data system. This brings together master data on thousands of raw materials, together with information on formulation development, as well as data from its research and experiments – all of which would help it to understand the interactions between different substances and combine and optimize formulas.

ENOVIA was selected to help standardize the management of raw materials and processing specifications in the data system and to manage formulations at all levels, from the experimental batch level through to the finalized bill of materials (BOM). Meanwhile, BIOVIA was chosen to replace paper-based experiment tracking with a digital, structured environment where researchers can design experiments, record batch data and analyze results of different formulations and combinations with full traceability. Together, these capabilities transform research information into consistently structured, searchable and shareable digital data with easy access from a single environment.

Atis System also leveraged the 3DEXPERIENCE platform’s configuration capabilities to customize dashboards and workflows to match Kukdo Chemical researchers’ daily needs and operational flow. This customization effort was key to driving user adoption and satisfaction as it’s intuitive to use and the platform is fully integrated into the researchers’ standard work environment.

With the platform now fully deployed, Kukdo Chemical is seeing its R&D environment evolve from fragmented experiments and documentation into an interconnected network of digital research intelligence powered by data science. Raw materials, formulations and performance data are recorded consistently, creating a pool of high-quality information that is easily searchable thanks to BIOVIA’s chemical structure-based search engine.

Multiple new capabilities arise as a result. For example, when developing a new epoxy resin with specific performance needs, a researcher can quickly find existing experimental batches with the same underlying chemical structure or functional attributes. This significantly reduces manual work and accelerates formulation development.

Researchers can also now compare the properties of different formulation batches side-by-side. When a raw material changes or a supplier shifts, variations in the material’s characteristics – like the purity or particle size – can impact existing formulations. By tracing these effects immediately, researchers can ensure batch consistency, improve compliance and better rationalize R&D decisions.

Having a unified repository of formulation, raw material and experimental data has also strengthened collaboration. Research planning, laboratory operations, procurement and quality teams now work from the same information – which they can access from anywhere. As a result, the need for repeated work is reduced and decision-making is much easier.

In the coming months, Kukdo Chemical plans to leverage BIOVIA’s molecular modeling and simulation capabilities to run in silico tests before conducting physical experiments, helping reduce both time and cost in new material development. The company is also evaluating the integration of a chemical management system to strengthen regulatory reporting and compliance with international requirements, including the stringent Korean Chemical Control Act.

The company is also preparing to advance toward AI-powered R&D, and plans to adopt further BIOVIA capabilities. The aim is to benefit from machine learning-driven formulation optimization. By using generative formulation based on trained AI models, the company expects to learn the complex relationship between raw material properties, formulation compositions and final product performance.

An initial proof of concept showed positive results: using multiple sets of its historical batch experiment data, Kukdo Chemical was able to see how its researchers could predict performance outcomes before conducting experiments, explore new formulations guided by data science and even reverse-engineer material compositions from target properties. Its data now quickly uncovers how materials might perform in practice, empowering Kukdo Chemical’s long-term vision: that the 3DEXPERIENCE platform will prepare it for an AI-enabled future.