Artificial Intelligence in Chemical Engineering

Capture the future of process design with Artificial Intelligence in Chemical Engineering by Farooq Sher — a clear, practical guide that bridges advanced AI techniques and real-world chemical engineering challenges. This authoritative volume immediately engages professionals and students who want AI-driven solutions that work on the plant floor and in research labs.

Explore how modern machine learning, deep learning, and data-driven modeling can transform process modeling, control, optimization, and fault detection. Farooq Sher presents algorithms and workflows in a readable, application-focused style, supported by industry-relevant examples and case studies that make complex concepts accessible to practicing engineers, graduate students, and researchers.

Designed for immediate use, the book emphasizes practical strategies for deploying AI across the chemical value chain: predictive maintenance, process intensification, energy efficiency, and sustainable operations. Readers gain actionable insights on building robust models from noisy plant data, integrating physics-based constraints, and scaling solutions for pilot and production environments.

Whether you’re in academia, a multinational chemical plant in North America, Europe, or Asia, or leading a start-up focused on green chemistry, this book equips you to convert data into competitive advantage. Clear diagrams, step-by-step methodologies, and a focus on reproducible outcomes make it an essential reference.

Add Artificial Intelligence in Chemical Engineering to your professional library today to accelerate innovation, reduce operating costs, and lead smarter, safer process development. Order now and start applying AI where it matters most.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.