Computer Aided Formulation

Formulation chemists and engineers, along with their research managers, have long known the difficult nature of formulation problems. This book is a manual to help them to identify key issues, design efficient experiments, and develop math models to resolve conflicting objectives. Specific solved examples, co-authored by chemists, show how well these methods work on industrial-strength problems and document the power and efficiency of computer aided formulation.
This book is the first one to combine techniques of operations researching decision science, and statistics to solve formulation problems. Readers will appreciate its chapters on experimental design, which are easy to read and enjoyable.1. Das Buch spricht ein Thema an, das die gesamte produzierende chemische Industrie betrifft: Die Herstellung qualitativ hochwertiger Produkte, die durch Mischen mehrerer Komponenten hergestellt werden.
2. Hier werden Computer-Modelle und -Programme vorgestellt, mit denen die vielfaltigen Probleme der Formulierung angegangen werden konnen.
3. Das Buch beschreibt Fallstudien, die Moglichkeiten und Nutzen der hier dargestellten Methoden zeigen.
4. Das Buch zeigt, wie die hier beschriebenen Methoden zu einem intelligenten Experten-System vereinigt werden konnen Author’s Note on Text

Contributors

Chapter 1

The Formulation Problem

Introduction

Basic Principles of Formulating

Many Ingredients

Measuring Product Quality

Conflicting Goals

Additional Challenges

Identifying Experimental Variables

Implicit Formula and Process Constraints

Alternate Forms of Independent Variables

Controlling the Effects of Background Noise

Approaches to Formulation

The Artsy Approach

The Modeling-Graphical Approach

The Math-Programming Approach

Interactive Goal Programming

Prioritizing Goals

Math-Programming Format

Computer Aided Formulation

Expert Systems

Other Expertise Needed

Implementation

Summary

Definitions

Bibliography

Chapter 2

The Experimental Process

Introduction

Defining the Experimental System

Independent Variables

System Parameters

Uncontrolled Variables

System Constraints

Summary

Definitions

Bibliography

Chapter 3

Experimental Design

Introduction—Experimental Models

One-Factor-at-a-Time (OFAT) Designs

Search Approaches to Experimental Design

Two-Factor-at-a-Time (TFAT) Designs

Factorial Designs

Partial Factorial Designs

Practical Considerations

Box-Wilson Designs

Simplex Centroid Designs

Summary

Definitions

Bibliography

Chapter 4

Fundamentals of Math Programming

Introduction

Math Programming

Linear Programming

Product Mix

Blending

Transportation

Multiperiod Scheduling

Portfolio Selection

Covering

Linear Programming Modeling

Linear Programming Formulation

The Graphical Solution

Sensitivity Analysis

Economic Impact of Changes to Right-Hand-Side Values

Computation of Dual Prices

Computation of Right-Hand-Side Ranges

Reduced Costs

Nonlinear Programming

Multiple Objectives Models—Goal Programming

Summary

Definitions

Bibliography

Chapter 5

Multiple Goal Decision Methods

Introduction

Multiple Objective Scenarios

Multiobjective Optimality

Finding Efficient Solutions

Decision Space versus Objective Space

Utility Analysis

Problems in Comparing Alternatives

What Is Utility?

Assessing Single Objective Utility

Using Utility to Compare Alternatives

Preference Structure

Ranking and Weighting

Utility Curves

Multiobjective Decision Approaches

The Weighting Method

The Goal Approach

Multiattribute Utility Analysis

Summary

Definitions

Bibliography

Chapter 6

Expert System Design

Principles and Solved Example

Developing Effective Regression Models

Solved Example

Background

Experimental Objective

Working Hypothesis

Experimental System

Testing

Regression Modeling

Measured Moistness versus Variables Listed

Interactive Nonlinear Goal Programming

Objective Function

Constraints

Goal Constraints

Interactive Process

Conclusion

The Integrated Expert System

Summary

Definitions

Bibliography

Appendix 6.1

Appendix 6.2

Chapter 7

An Analytic Hierarchy Approach for Evaluating Product Formulations

Introduction

The Analytic Hierarchy Process

An Example of the Process

Extensions to the Analytic Hierarchy Process

An Alternative Approach to Evaluate Product Formulations

Summary

Definitions

Bibliography

Appendix 7.1

Chapter 8

Plastics Compounding and Formulation

Introduction

Getting Started

Overview of the Formulation Problem

Selection of the Polymer

A General Overview of Polymers

Polymer Properties and Screening Tests

Additives Used in Compounding Plastics

Some Tips to Speed the Work

Solved Example

Summary

Definitions

Bibliography

Chapter 9

Formulating Laundry Detergents

Detergent Performance

Bleaching and Brightening

Freshening

Fabric Softening

Soils

Fabrics

Product Safety

Product Stability

Processing

Formulating Fundamentals

Particulate Soils

Oily Soils

Starchy Soils

Fatty Soils

Proteinaceous Soils

Fabrics

Cleaning Considerations

Surfactants

Water Hardness

Alkalinity

Application Method

Solved Example

Background

Procedure

Laboratory Confirmation

Summary

Definitions

Bibliography

Chapter 10

Case Study: Silica-Based Defoamers

Introduction

Definitions

Foam Problems in Industry

Mechanisms of Defoamers

Side Effects

Silica in Defoamers

Forms of Silica

Making Silica Hydrophobic

Prior State of the Art

Objectives

Properties of the Perfect Antifoam

Optimizing In-Situ Silica Formulations

Experimental Design

Dependent Variables

Independent Variables

Uncontrolled Variables

System Parameters

System Constraints

Results

Development of a Performance Index

Choosing the Silicone

Choosing the Silica

Optimizing the Promoter Level

Optimizing the Silicone Level

Optimizing the Cost-Effectiveness

Optimizing the Mineral Oil Level

Optimizing the Dose Rate

Optimizing the Performance to Cost Ratio

Summary

Definitions

Bibliography

Index

Alan H. Bohl is the author of Computer Aided Formulation: A Manual for Implementation, published by Wiley. A Manual for Implementation Computer Aided Formulation Alan H. Bohl, Editor Computer Aided Formulation is a step-by-step manual for using up-to-date methods of experimental design, operations research and decision science to identify key issues, design efficient experiments and develop math models to resolve conflicting objectives. Using currently-available PC software, formulation professionals can determine if new product requests are technically feasible and if so, find the most cost-effective way of satisfying them. Statisticians and Operations Research professionals who work with formulation chemists and engineers will benefit from this book.