The Digital Transformation of Product Formulation: Concepts, Challenges, and Applications for Accelerated Innovation [Hardcover]

This book offers practical guidance on how to implement data-driven, accelerated product development through concepts, challenges, and applications. It describes activities related to creating new or improved functional material products by discovering new ingredients or new ingredient combinations resulting in targeted quality properties.

Section 1: Getting Started. 1. The Digital Transformation of R&D Labs. 2. Product Formulation Fundamentals. 3. Defining a Successful Predictive Formulation Project. Section 2: Preparing Your Data. 4. Challenges with Formulation Datasets. 5. Feature Engineering: Enhancing Your Data with Descriptors. 6. Machine Learning for Analysis of Structural Characterization. Section 3: Predictive Modeling. 7. Machine Learning Techniques for Predicting Properties of Formulations. 8. Modeling of Product Formulations Using a Latent Variable Approach. 9. Gaining Trust in Your Model. Section 4: Optimization and Inverse Design. 10. Introduction to Formulation Optimization. 11. Adaptive Experimental Design. 12. Inverse Design via PLS Model Inversion. Section 5: Case Studies and Special Topics. 13. Case Studies. 14. Special Topics. 15. Conclusion.

In competitive manufacturing industries, organizations embrace product development as a continuous investment strategy since both market share and profit margin stand to benefit. Formulating new or improved products has traditionally involved lengthy and expensive experimentation in laboratory or pilot plant settings. However, recent advancements in areas from data acquisition to analytics are synergizing to transform workflows and increase the pace of research and innovation. The Digital Transformation of Product Formulation offers practical guidance on how to implement data-driven, accelerated product development through concepts, cl£