Foreword by Ron Lambert -- About the Author -- Acknowledgments -- Disclaimer -- 1 Optimizing a Process Plant -- 1.1 High-Level Business Goals -- 1.2 Profit -- 1.3 Each Plant Is Unique -- 1.4 Plant Optimization Nirvana -- 1.5 Process/Asset Views of the Business Need Alignment -- 1.6 Optimization Technologies on the Process Side of the Business -- 1.7 Optimization Technologies on the Asset Side of the Business -- 1.8 Conclusion -- 1.9 Future Chapters -- 2 Gen 1 - Transitioning from Reliability to Asset Management -- 2.1 Reliability's Early Days -- 2.2 Rebranding Reliability to be Asset Management -- 2.3 Changing the Reliability Management Structure -- 2.4 Where Did Gen 1 Fall Short? -- 2.5 Adoption of Monte Carlo Simulation Technology Has Struggled -- 2.6 Asset Optimization Nirvana - The Future -- 2.7 Conclusion -- 3 Gen 2 - Plant Optimization Using Asset Modeling Methodologies -- 3.1 Gen 2 Philosophy -- 3.2 Gen 2 Asset Optimization Applications -- 3.3 Conclusion -- 4 Selecting the Best Improvement Projects - Optimal Process Unit Availability -- 4.1 Industry Challenge -- 4.2 Improvement Projects -- 4.3 Asset Optimization Technologies -- 4.4 Optimizer Definition -- 4.5 Optimization Example -- 4.6 More General Optimization -- 4.7 Does Reducing Availability Make Sense for Any of Our Process Units? -- 4.8 Conclusion -- 5 Monte Carlo Simulation Overview -- 5.1 Reliability Block Diagram (RBD) -- 5.2 Rolling the Dice -- 5.3 Histories within a Model Run -- 5.4 Results -- 5.4.1 Probability Distributions -- 5.5 Submodel - Detailed Process Unit Model -- 5.6 What Level of Detail Is Required? -- 5.7 Definitions -- 5.8 RAM Software Tools -- 5.9 Challenge to Monte Carlo Simulation Vendors -- 5.10 Conclusions -- 6 Optimizer Overview -- 6.1 Independent Variables -- 6.2 Dependent Variables -- 6.3 Constraints -- 6.4 Objective Function -- 6.5 Optimizer Problem Definitions -- 6.6 Conclusions -- 7 The Consultation Process - The Main Work Process -- 7.1 Nobody Has Excellent Data in the Process Industries -- 7.2 Why Operating Conditions Are so Important in the Process Industries -- 7.3 Tapping into Your Company's Innate Knowledge -- 7.4 Golden Opportunity To Test the Approach -- 7.5 Consulting Meeting Details -- 7.6 Monte Carlo Modeler Software Inputs -- 7.7 Data from Asset Management Systems -- 7.8 Data Storage/Structure -- 7.9 Conclusion -- 8 Turnaround Considerations -- 8.1 Example Problem Overview -- 8.2 Results Expectations -- 8.3 Solution Approach -- 8.4 First Problem - Fixed Start Date and Duration -- 8.5 Second Problem - Fixed Start Date, but Flexible Duration -- 8.6 Last Problem - Flexible Start Date -- 8.7 Conclusion -- 9 What About Process Conditions? -- 9.1 Examples Where Feed Quality and Process Conditions Play a Major Role -- 9.2 Operating Condition Effect on Failure Data -- 9.3 Example Incorporating Process Conditions into Our Problem Definition -- 9.4 Conclusion -- 10 Opportunistic Maintenance Optimization -- 10.1 Modeling Maintenance Plan Options -- 10.2 Example Problem Data -- 10.3 Single Equipment Opportunistic Maintenance Optimization -- 10.4 Intra Unit Opportunistic Maintenance Optimization -- 10.5 Inter Unit Opportunistic Maintenance Optimization -- 10.6 Conclusion -- 11 Spare Parts Optimization -- 11.1 Spares Parts Dependence Often Masks Other Equipment Issues -- 11.2 Typical Methods for Estimating Spare Parts -- 11.3 Logistical Challenges -- 11.4 Lead Times/Price/Vendor Issues -- 11.5 Prioritization -- 11.6 Example Problem Data -- 11.7 Effect of Failure Standard Deviation -- 11.8 Optimization Problems Overview -- 11.9 Single Equipment Spares Optimization -- 11.10 Intra-Unit Spares Optimization -- 11.11 Inter-Unit Spares Optimization -- 11.12 Common Spare Across Multiple Units -- 11.13 Full-time Spare Parts Engineer Position -- 11.14 Conclusion -- 12 Task/Resource Optimization -- 12.1 Example Problem Data -- 12.2 General Approach -- 12.3 Single Equipment Task Optimization -- 12.4 Intra-Unit Equipment Task Optimization -- 12.5 Inter-Unit Equipment Task Optimization -- 12.6 Conclusion -- 13 Tankage Determination/Optimization -- 13.1 Why Tankage Size Matters -- 13.2 Example Problem Overview -- 13.3 Same Availability for both Upstream and Downstream Process Units -- 13.4 Downstream Availability Variable with Constant Upstream Availability -- 13.5 Conclusion -- 14 Improving Availability -- 14.1 Options to Improve Availability -- 14.2 How Reliability and Process Configuration Effects Availability Results -- 14.3 Which Option Is the Best? -- 14.4 Conclusion -- 15 Equipment Reliability Optimization -- 15.1 General Approach -- 15.2 Example Problem Data -- 15.3 First Impressions of Example Data - Impact on Problem Solution -- 15.4 Effect of Failure Standard Deviation -- 15.5 Single Equipment Design Optimization -- 15.6 Intra-Unit Design Optimization -- 15.7 Inter-Unit Design Optimization -- 15.8 Scenario Final Thoughts -- 15.9 Conclusion -- 16 Plant Optimization Within the Design Process -- 16.1 Combining Process Simulation with Monte Carlo Simulation -- 16.2 Balancing the Short/Long Term within the Design Process -- 16.3 Improvement Project -- 16.4 Debottlenecking Project -- 16.5 Changes to Plant-Level Model for Grassroots Process Design -- 16.6 Grassroots Process Unit Design -- 16.7 Design Considerations -- 16.8 Conclusion -- 17 Combined Optimization -- 17.1 Combination of Improvement Projects and Crude Feed Mix Optimization -- 17.2 Combining Turnaround and Future Feed Composition -- 17.3 Conclusion -- 18 Mapping Models to Optimization Problems -- 18.1 Mapping Between Optimization Problem and Model(s) Required -- 18.2 Selection of Optimal Improvement Projects -- 18.3 Storage Optimization -- 18.4 Turnaround Timing/Duration and Equipment Restoration Selection -- 18.5 Maintenance Plan Options Optimization -- 18.6 Spares Optimization -- 18.7 Task Optimization -- 18.8 Asset Design Optimization -- 18.9 How to Kickstart Your Program -- 18.10 Standard Models or Not? -- 18.11 Process Unit Models -- 18.12 Site or Plant Models -- 18.13 Equipment Models -- 18.14 Responsibility for Equipment Models -- 18.15 Conclusion -- 19 Creating a Program Master Plan -- 19.1 Opportunity Assessment -- 19.2 Project Selection -- 19.3 Project Phases -- 19.4 Resources -- 19.5 Consultation Process -- 19.6 Data - and Its Implications -- 19.7 Technologies -- 19.8 Work Processes -- 19.9 Training -- 19.10 Conclusion -- 20 Conclusion -- 20.1 The Need for a Complex Asset Base -- 20.2 High-Level Business Goals -- 20.3 Asset Decisions that Can Drive Optimal Profit -- 20.4 A Side Benefit → Combining the Process and Equipment Views of the Business -- 20.5 How to Move Forward with Your Program -- 20.6 Limitations of Asset Modeling -- 20.7 Comparing Process and Asset Optimization -- 20.8 The Future of Optimization -- Appendix A Nuts and Bolts of Monte Carlo Simulation -- Appendix B Refinery Example Process Description -- Notes -- Index.