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Table of Contents
1 Cover
4 Preface Overview of Contents
5 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
6 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? 2.4 Using Advanced Analytics to Boost Productivity and Profitability in Chemical Manufacturing 2.5 Achieving Business Impact with Data 2.6 From Dull Data to Critical Business Insights: The Upstream Processes 2.7 From Valuable Data Analytics Results to Achieving Business Impact: The Downstream Activities References
7 3 Profit Maximization Project (PMP) Implementation Steps 3.1 Implementing a Profit Maximization Project (PMP) References
8 4 Strategy for Profit Maximization 4.1 Introduction 4.2 How is Operating Profit Defined in CPI? 4.3 Different Ways to Maximize Operating Profit 4.4 Process Cost Intensity 4.5 Mapping the Whole Process in Monetary Terms and Gain Insights 4.6 Case Study of a Glycol Plant 4.7 Steps to Map the Whole Plant in Monetary Terms and Gain Insights Reference
9 5 Key Performance Indicators and Targets 5.1 Introduction 5.2 Key Indicators Represent Operation Opportunities 5.3 Define Key Indicators 5.4 Case Study of Ethylene Glycol Plant to Identify the Key Performance Indicator 5.5 Purpose to Develop Key Indicators 5.6 Set up Targets for Key Indicators 5.7 Cost and Profit Dashboard 5.8 It is Crucial to Change the Viewpoints in Terms of Cost or Profit References
10 6 Assessment of Current Plant Status 6.1 Introduction 6.2 Monitoring Variations of Economic Process Parameters 6.3 Determination of the Effect of Atmosphere on the Plant Profitability 6.4 Capacity Variations 6.5 Assessment of Plant Reliability 6.6 Assessment of Profit Suckers and Identification of Equipment for Modeling and Optimization 6.7 Assessment of Process Parameters Having a High Impact on Profit 6.8 Comparison of Current Plant Performance Against Its Design 6.9 Assessment of Regulatory Control System Performance 6.10 Assessment of Advance Process Control System Performance 6.11 Assessment of Various Profit Improvement Opportunities References
11 7 Process Modeling by the Artificial Neural Network 7.1 Introduction 7.2 Problems to Develop a Phenomenological Model for Industrial Processes 7.3 Types of Process Model 7.4 Emergence of Artificial Neural Networks as One of the Promising Data‐Driven Modeling Techniques 7.5 ANN‐Based Modeling 7.6 Model Development Methodology 7.7 Application of ANN Modeling Techniques in the Chemical Process Industry 7.8 Case Study: Application of the ANN Modeling Technique to Develop an Industrial