03483nam a22003854u 4500 10.1002/9781119825920 Wiley 20251030120313.0 cr nn 008mam|a 240126t2024||||xxu fs| |0|| 0|eng|| 9781119825920 electronic 10.1002/9781119825920 doi eng Artificial Intelligence in Process Fault Diagnosis Methods for Plant Surveillance [electronic resource] Edited by Richard J. Fickelscherer. 1 Wiley 2024 Wiley 2024 432pp.; text txt rdacontent computer c rdamedia online resource cr rdacarrier text file rdaft PDF Artificial Intelligence in Process Fault Diagnosis A comprehensive guide to the future of process fault diagnosis Automation has revolutionized every aspect of industrial production, from the accumulation of raw materials to quality control inspections. Even process analysis itself has become subject to automated efficiencies, in the form of process fault analyzers, i.e., computer programs capable of analyzing process plant operations to identify faults, improve safety, and enhance productivity. Prohibitive cost and challenges of application have prevented widespread industry adoption of this technology, but recent advances in artificial intelligence promise to place these programs at the center of manufacturing process analysis. Artificial Intelligence in Process Fault Diagnosis brings together insights from data science and machine learning to deliver an effective introduction to these advances and their potential applications. Balancing theory and practice, it walks readers through the process of choosing an ideal diagnostic methodology and the creation of intelligent computer programs. The result promises to place readers at the forefront of this revolution in manufacturing. Artificial Intelligence in Process Fault Diagnosis readers will also find: Coverage of various AI-based diagnostic methodologies elaborated by leading experts Guidance for creating programs that can prevent catastrophic operating disasters, reduce downtime after emergency process shutdowns, and more Comprehensive overview of optimized best practices Artificial Intelligence in Process Fault Diagnosis is ideal for process control engineers, operating engineers working with processing industrial plants, and plant managers and operators throughout the various process industries. Computer-Aided Engineering 66003 Artificial Intelligence 58441 Industrial Chemistry 69611 Artificial Intelligence; process fault diagnosis; Machine learning; data science; data analysis; process control; process monitoring; Fuzzy logic; emergency process shutdowns; diagnostic strategy; petroleum processing; chemical processing; nuclear processing; operations engineering Fickelscherer, Richard J. edt 91884 Printed edition: 9781119825890 https://doi.org/10.1002/9781119825920 Wiley Online Library https://onlinelibrary.wiley.com/action/showBook?doi=10.1002%2F9781119825920 Wiley Online Library Cover Image https://onlinelibrary.wiley.com/cms/asset/03eb8af9-fc7e-41a7-ab11-7c559a60bca7/9781119825920.cover.gif Wiley Online Library 67131 67131