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Sandip K. Lahiri
Profit Maximization Techniques for Operating Chemical Plants
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Вернуться на страницу книги Profit Maximization Techniques for Operating Chemical Plants
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Страница 1
Table of Contents
List of Tables
List of Illustrations
Guide
Pages
Profit Maximization Techniques for Operating Chemical Plants
Страница 8
Страница 9
Preface
Overview of Contents
Concept of Profit Maximization
Big Picture of the Modern Chemical Industry
Profit Maximization Project (PMP) Implementation Steps
Strategy of Profit Maximization
Key Performance Indicators and Targets
Assessment of Current Plant Status
Process Modeling by an Artificial Neural Network
Optimization of Industrial Processes and Process Equipment
Process Monitoring
Fault Diagnosis
Optimization of the Existing Distillation Column
New Design Methodology
Genetic Programing for Modeling of Industrial Reactors
Maximum Capacity Test Run and Debottlenecking Study
Loss Assessment
Advance Process Control
150 Ways and Best Practices to Improve Profit in Running a Chemical Plant
1 Concept of Profit Maximization 1.1 Introduction
1.2 Who is This Book Written for?
1.3 What is Profit Maximization and Sweating of Assets All About?
1.4 Need for Profit Maximization in Today's Competitive Market
1.5 Data Rich but Information Poor Status of Today's Process Industries
1.6 Emergence of Knowledge‐Based Industries
1.7 How Knowledge and Data Can Be Used to Maximize Profit
References
2 Big Picture of the Modern Chemical Industry 2.1 New Era of the Chemical Industry
2.2 Transition from a Conventional to an Intelligent Chemical Industry
2.3 How Will Digital Affect the Chemical Industry and Where Can the Biggest Impact Be Expected?
2.3.1 Attaining a New Level of Functional Excellence
2.3.1.1 Manufacturing
2.3.1.2 Supply Chain
2.3.1.3 Sales and Marketing
2.3.1.4 Research and Development
2.4 Using Advanced Analytics to Boost Productivity and Profitability in Chemical Manufacturing
2.4.1 Decreasing Downtime Through Analytics
2.4.2 Increase Profits with Less Resources
2.4.3 Optimizing the Whole Production Process
2.5 Achieving Business Impact with Data
2.5.1 Data's Exponential Growing Importance in Value Creation
2.5.2 Different Links in the Value Chain
2.5.2.1 The Insights Value Chain – Definitions and Considerations (Holger Hürtgen, 2018)
2.6 From Dull Data to Critical Business Insights: The Upstream Processes
2.6.1 Generating and Collecting Relevant Data
2.6.2 Data Refinement is a Two‐Step Iteration
2.7 From Valuable Data Analytics Results to Achieving Business Impact: The Downstream Activities
2.7.1 Turning Insights into Action
2.7.2 Developing Data Culture
2.7.3 Mastering Tasks Concerning Technology and Infrastructure as Well as Organization and Governance
References
3 Profit Maximization Project (PMP) Implementation Steps 3.1 Implementing a Profit Maximization Project (PMP)
3.1.1 Step 1: Mapping the Whole Plant in Monetary Terms
3.1.2 Step 2: Assessment of Current Plant Conditions
3.1.3 Step 3: Assessment of the Base Control Layer of the Plant
3.1.4 Step 4: Assessment of Loss from the Plant
3.1.5 Step 5: Identification of Improvement Opportunity in Plant and Functional Design of PMP Applications
3.1.6 Step 6: Develop an Advance Process Monitoring Framework by Applying the Latest Data Analytics Tools
3.1.7 Step 7: Develop a Real‐Time Fault Diagnosis System
3.1.8 Step 8: Perform a Maximum Capacity Test Run
3.1.9 Step 9: Develop and Implement Real‐Time APC
3.1.10 Step 10: Develop a Data‐Driven Offline Process Model for Critical Process Equipment
3.1.11 Step 11: Optimizing Process Operation with a Developed Model
3.1.12 Step 12: Modeling and Optimization of Industrial Reactors
3.1.13 Step 13: Maximize Throughput of All Running Distillation Columns
3.1.14 Step 14: Apply New Design Methodology for Process Equipment
References
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