1. Value Optimization in a World of Choices Presenters: Timothy J. Havranek, MBA, PMP Leigh A. Hostetter, BA Copyright 2006, Triangle Economic Research, LLC

2. DTC Process Optimization Problem Framing Meeting Optimal Decision Modeling

3. Introduction Client for original model was a chemical manufacturing company This company has developed a number of value improvement processes (VIPs) –Applied to all new projects –Exist for the each phase –Latter phase VIPs are focused on fine tuning the design Model developed to facilitate the Design to Capacity (DTC) VIP.

4. DTC Purpose Maximize capital efficiency Prevent over design that can occur due to: –Allowances for uncertainty (safety factors) –Equipment and materials come in incremental step sizes –Lack of design definition –Uncertain market demand

5. DTC Approach Uses a facilitated framing meeting to: –Challenge the design team –Identify design components that add excess capacity and cost –Develop a list of viable alternatives Alternatives are evaluated in terms of: –Capital and operating costs –Useful equipment life –Manufacturing capacity Recognizes that costs and equipment life are uncertain

6. Framing Meeting Steps Identify Major Equipment Alternatives Provide Equipment Capacities Develop Cost Range Estimates Identify Alternative Constraints

7. Major Equipment Requirements Under the control of the design team Two or more viable alternatives exist Equipment could have impact on system capacity

8. Concerns with Standard DTC Process Assumes that stated design capacity is the optimum capacity Does not include an evaluation of uncertain demand Seeks value improvement without addressing Over the Wall effect

9. Todays Presentation We present the results of a model: –Based on real project –Altered for purposes of demonstration and confidentiality –Evaluates the effect of uncertain demand

10. Optimization and Inputs Optimization: Model Inputs:

11. Framing Meeting Alternatives

12. Model Inputs

13. Input Distributions

14. Modeling Elements

15. Optimization for Lowest Total Cost (Present Value)

16. Optimization for Specified Design Capacity

17. Optimization for Minimum Excess Capacity, Maximum PV of Revenue and Maximum NPV of Profit

18. Optimization Comparisons Optimization NumberOptimization 1Optimization 2Optimization 3 Variable OptimizedNPV of Total CostsSystem Capacity (bbl/day) Capacity Metric, NPV of Revenue, NPV of Profit Optimization CriteriaMinimum ValueExact Value Minimum Value, Maximum Value, Maximum Value Primary Cooling SystemNew UnitRefurbished UnitNew Unit Acid Tower Bottoms Cooler New Shell & Tube Heat Exchanger Refurbished Fin-Fan Heat Exchanger New Shell & Tube Heat Exchanger Product Heat ExchangerExisting Fin-Fan Exchanger New Shell & Tube Exchanger Water Wash TowerMonel Clad Tower Carbon Steel Extra Corrosion Allowance Monel Clad Tower System Capacity (bbl/day)2,600 3,500 Capacity Metric2,100130300 Restricting EquipmentProduct Heat Exchanger Acid Tower Bottoms Cooler Restricting AlternativeExisting Fin-Fan Exchanger New Shell & Tube Heat Exchanger Initial Capital Costs$4.95$3.32$6.03 Initial Installation Costs$1.71$1.66$1.84 PV of Operating & Replacement Costs$12.90$44.84$12.36 PV of Total Costs$19.57$49.82$20.23 PV of Revenue$104.28$104.51$117.85 NPV of Profit$84.71$54.69$97.62

19. Net Present Value Statistics

20. NPV Risk Profiles

21. NPV Histograms

22. Comparison of Cumulative Profit over Time Curves Optimization #1 Optimization #2Optimization #3

23. Summary RISKOptimizer can be used to improve the value of value improvement processes: –Improves decision making under uncertainty –Encourages synergetic analysis rather than a fall back to business axioms –Helps achieve a shared understanding of business alternatives @RISK can be used for detailed evaluation of alternatives identified by RISKOptimizer The effects of uncertain demand and product price must accounted for when attempting to design for maximum capital efficiency