Digitalization and Analytics for Smart Plant Performance: Theory and Applications - Hardcover

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Frank (Xin X.) Zhu, PhD, is Senior Engineering Fellow and Leader of Engineering Innovations at Honeywell UOP. He has made significant contributions to the theoretical framework, the computational tools, and applications in the fields of data analytics, production planning, operation scheduling, process modeling, design and optimization. He has published seminal journal articles and widely used books especially in the areas of process operations, process design and energy systems. He holds 68 US patents, is the co-founder and chair of ECI International Conference: CO2 Summit, and the recipient of prestigious AICHE Energy Sustainability Award.

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Provides a digital and analytic solution platform for integrating business and technical activities to enhance profit, reliability, safety, and performance for manufacturing plants via Connect Plant—covers data science theory, digital tools, and industrial applications

The Connected Plant is a suite of digital applications integrating data sources and advanced analytics to make intelligent predictions to guide decisions in order to run production processes more efficiently, safely and create new value. Furthermore, Connect Plant can digitalize workforce and work processes so that complex tasks can be accomplished automatically while plant staff can have more time on decision-making. Collecting real-time data, the Connected Plant enables continuous monitoring, optimization, and control of key plant operating parameters—connecting people, processes and assets much better than traditional digital solutions. Digitalization and Analytics for Smart Plant Performance is the first book to focus solely on digitalization and analytics for the process industries, explaining the principles and practices necessary for successful transformation to Smart Plant performance and intelligent workforce.

The book demystifies digitalization and data science for industrial application, and explains the next-generation digital solutions that enhance business capabilities, improve asset management, optimize workflow management, and turn data from multiple sources into actionable insights. Working with other subject matter experts in the field, the author Frank Zhu, a pioneer for key indicator-based operation optimization and molecular analysis based process synthesis, provides step-by-step guidance on analytics modeling and optimization models, data infrastructure, implementation strategies, and much more. Frank sheds much light onto digital twin—a virtual plant, which is a digital platform consisting of rigorous and analytics models and multi-sourced data to mimic the real plant. More importantly, digital twin can analyze “what-if” scenarios, predicting “what’s wrong” events and determining “what’s best” conditions to achieve smart plant performance.

Offering timely and authoritative coverage of all vital aspects of industrial digitalization, this book:

Digitalization and Analytics for Smart Plant Performance: Theory and Applications is required reading for corporate and plant managers, process and control engineers, and data scientists, as well as operators working in process industries worldwide. This book could be excellent reading for university professors and students to understand how to apply data science and Big Data theory for practical applications in the process industries.