AI in Chemical Engineering: Unlocking the Power Within Data
暫譯: 化學工程中的人工智慧：釋放數據的潛力
Romagnoli, José A., Briceño-Mena, Luis, Manee, Vidhyadhar
相關主題
商品描述
Industry 4.0 is revolutionizing chemical manufacturing. Today's chemical companies are swiftly embracing the digital era, recognizing the significant benefits of interconnected products, production equipment, and personnel. As technology advances and production volumes grow, there is an increasing need for new computational tools and innovative solutions to address everyday challenges. AI in Chemical Engineering: Unlocking the Power Within Data introduces readers to the essential concepts of machine learning and their application in the chemical and process industries, aiming to enhance efficiency, adaptability, and profitability. This work delves into the transformation of traditional plant operations into integrated and intelligent systems, providing readers with a foundation for developing and understanding the tools necessary for data collection and analysis, thereby gaining valuable insights and practical applications.
- Introduces the principles and applications of unsupervised learning and discusses the role of machine learning in extracting information from plant data and transforming it into knowledge.
- Conveys the concepts, principles, and applications of supervised learning, setting the stage for developing advanced monitoring systems, complex predictive models, and advanced computer vision applications.
- Explores implementation of reinforced learning ideas for chemical process control and optimization, investigating various model structures and discussing their practical implementation in both simulation and experimental units.
- Incorporates sample code examples in Python to illustrate key concepts.
- Includes real-life case studies in the context of chemical engineering and covers a wide variety of chemical engineering applications from oil and gas to bioengineering and electrochemistry.
- Clearly defines types of problems in chemical engineering subject to AI solutions and relates them to subfields of AI.
This practical text, designed for advanced chemical engineering students and industry practitioners, introduces concepts and theories in a logical and sequential manner. It serves as an essential resource, helping readers understand both current and emerging developments in this important and evolving field.
商品描述(中文翻譯)
工業4.0正在徹底改變化學製造業。當今的化學公司迅速擁抱數位時代，認識到互聯產品、生產設備和人員所帶來的重大好處。隨著技術的進步和生產量的增長，對於新的計算工具和創新解決方案的需求日益增加，以應對日常挑戰。《AI在化學工程中的應用：釋放數據中的潛力》向讀者介紹了機器學習的基本概念及其在化學和過程工業中的應用，旨在提高效率、適應性和盈利能力。本書深入探討了傳統工廠運營向集成和智能系統的轉型，為讀者提供了開發和理解數據收集與分析所需工具的基礎，從而獲得有價值的見解和實用應用。
- 介紹無監督學習的原則和應用，並討論機器學習在從工廠數據中提取信息並將其轉化為知識中的作用。
- 傳達監督學習的概念、原則和應用，為開發先進的監控系統、複雜的預測模型和先進的計算機視覺應用奠定基礎。
- 探索強化學習理念在化學過程控制和優化中的實施，研究各種模型結構並討論其在模擬和實驗單元中的實際應用。
- 包含Python中的示例代碼，以說明關鍵概念。
- 包括化學工程背景下的實際案例研究，涵蓋從石油和天然氣到生物工程和電化學的各種化學工程應用。
- 清楚定義化學工程中適用於AI解決方案的問題類型，並將其與AI的子領域相關聯。
這本實用的文本旨在為高級化學工程學生和行業從業者介紹概念和理論，邏輯性和連貫性強。它作為一個重要資源，幫助讀者理解這一重要且不斷發展領域中的當前和新興發展。
作者簡介
Jose A. Romagnoli is the Gordon & Mary Cain Endowed Chair Professor of Process Systems Engineering, Department of Chemical Engineering, Louisiana State University. He received his Ph.D. from University of Minnesota.
Luis A. Briceno-Mena works at Dow on their Machine Learning Optimization and Statistics team. He received his Ph.D. in Chemical Engineering from Louisiana State University.
Vidhyadhar Manee is a Senior Scientist in Process Research at Boehringer Ingelheim Pharmaceuticals Inc. He received his Ph.D. in Chemical Engineering from Louisiana State University.
作者簡介(中文翻譯)
Jose A. Romagnoli 是路易斯安那州立大學化學工程系的戈登與瑪麗·凱恩講座教授，專注於流程系統工程。他在明尼蘇達大學獲得博士學位。
Luis A. Briceno-Mena 在道達爾（Dow）擔任機器學習優化與統計團隊的成員。他在路易斯安那州立大學獲得化學工程博士學位。
Vidhyadhar Manee 是百靈達（Boehringer Ingelheim Pharmaceuticals Inc.）流程研究部的高級科學家。他在路易斯安那州立大學獲得化學工程博士學位。
