Whitepaper
Formulating. Testing. Deciding.
Digitalisation and AI in Detergent and Cleaning Product Development
A practical guide to digital formulation management, laboratory data management and AI in detergent and cleaning product development.
The whitepaper explores how formulation data can be structured, experimental data analysed and development knowledge systematically reused – from formulation management and experimental design to AI-supported formulation development.
- Starting point: Formulation, stability and laboratory data are distributed across Excel, LIMS, ELN and other systems, making them difficult to search, compare and reuse.
- Formulation management: Structure and connect formulations, raw materials, formulation variants and test results.
- Laboratory data management: Integrate laboratory instruments and existing IT systems to make experimental data centrally available for detergent and cleaning product development.
- Experimental design and DoE: Plan development experiments systematically and use historical data to identify promising formulations more effectively.
- AI in formulation development: Use machine learning and Bayesian optimisation to identify relationships between formulation variables and product properties and select the most promising next experiments.
- Results: Fewer iterations, less documentation effort and faster access to relevant development data.
