Artificial Intelligence in Process Fault Diagnosis 1st Edition

Artificial Intelligence in Process Fault Diagnosis, 1st Edition by Richard J. Fickelscherer is a definitive resource for engineers, plant managers, and researchers seeking practical, AI-driven solutions to complex industrial diagnostics. This authoritative volume opens with clear explanations of core principles — from neural networks and fuzzy logic to expert systems and pattern recognition — and shows how they apply to detecting, isolating, and predicting process faults in real-world operations.

Through focused chapters, the book bridges theory and practice: you’ll find step-by-step methodologies, algorithmic insights, and case-oriented examples tailored to chemical, petrochemical, power generation, and manufacturing environments. Emphasis on robust model development, data-driven fault detection, and scalable diagnostic strategies makes it ideal for consultants and maintenance teams aiming to reduce downtime and improve safety and efficiency across plants worldwide.

What sets this 1st Edition apart is its pragmatic orientation. Richard J. Fickelscherer combines engineering rigor with approachable explanations, enabling readers from academia and industry to implement AI techniques without getting lost in unnecessary abstraction. Whether you are optimizing control systems, deploying predictive maintenance programs, or researching advanced diagnostics, this book supplies the operational guidance and technical depth needed to deliver measurable results.

Add this essential reference to your professional library and equip your team with proven AI methods to enhance reliability and cut operational costs. Order your copy today and start transforming process fault diagnosis with intelligent, data-driven strategies trusted by practitioners around the globe.

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