[Available for preview] ★ Machine learning, soft sensors, Bayesian optimization, generative AI, experimental automation/autonomy
Book Title: Data Analysis, Modeling, and Application Development in Process Informatics
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Understanding where to apply the latest technologies to change processes through data-driven approaches
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■ Key Points of This Book: A practical guide filled with actionable know-how for practitioners
◆ "From Basics to Applications" of Data Analysis and Modeling
~ Variable selection, model building, sensor design, Bayesian optimization, autonomous experiments
◆ Reasons Why Process Informatics "Fails" and How to Address Them
~ Challenges in the implementation process, data shortages, examples of variable selection failures
◆ How to "Transform Data into Usable Forms?"
~ Data alignment between experiments and manufacturing, equipment integration, real-time analysis
◆ Richly includes case studies of implementation and deployment by process area and stage!
~ Specific examples of "which industries," "what equipment or processes," and "how they were designed"
■ Manufacturing Processes Covered in This Book
- Synthesis, drying processes, crystallization, granulation, stirring, cultivation, freezing, coating, film formation, rolling, pressing, fluid dynamics, reactions, gas absorption, fermentation