16.885 Aircraft Systems Engineering Cost Analysis Karen Willcox MIT Aerospace Computational Design Laboratory AEROSPACE COMPUTATIONAL DESIGN LABORATORY 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Outline ? Lifecycle cost ? Operating cost ? Development cost ? Manufacturing cost ? Revenue ? Valuation techniques 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Lifecycle Cost Lifecycle : Design - Manufacture - Operation - Disposal Lifecycle cost : Total cost of program over lifecycle 85% of Total LCC is locked in by the end of preliminary design. 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Lifecycle Cost 0 20 40 60 80 100 65% Conceptual design Preliminary design, system integration Detailed design Manufacturing and acquisition Operation and support Disposal Time Impact on LCC (%) 85% 95% (From Roskam, Figure 2.3) 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Operating Cost ? Airplane Related Operating Cost (AROC) ? Passenger Related Operating Cost (PROC) ? Cargo Related Operating Cost (CROC) ? Systems Related Operating Cost (SROC) AROC 70% PROC 18% CROC 2% SROC 10% 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Airplane Related Operating Costs CASH AIRPLANE RELATED OPERATING COSTS: Crew Fuel Maintenance Landing Ground Handling GPE Depreciation GPE Maintenance Control & Communications CAROC 60% 40% Capital Costs CAPITAL COSTS: Financing Insurance Depreciation CAROC is only 60% - ownership costs are significant! 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY CAROC Breakdown per Trip Landing 6% Ground Handling 7% Control & Comm 9% Other 3% Fuel 20% Crew 40% Maintenance 15% Fuel is roughly 20% of 60% of 70% of Total Operating Cost i.e. 8% typical data for a large commercial jet 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Non-Recurring Cost Cost incurred one time only: Engineering - airframe design/analysis - configuration control - systems engineering Tooling - design of tools and fixtures - fabrication of tools and fixtures Other - development support - flight testing Engineering Tooling Other 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Recurring Cost Cost incurred per unit: Labor - fabrication - assembly - integration Material to manufacture -raw material - purchased outside production - purchased equipment Production support -QA - production tooling support - engineering support Labor Material Support 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Learning Curve As more units are made, the recurring cost per unit decreases. This is the learning curve effect. e.g. Fabrication is done more quickly, less material is wasted. n x xYY 0 Y x = number of hours to produce unit x n = log b/log 2 b = learning curve factor (~80-100%) 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Learning Curve 0.55 0 0.2 0.4 0.6 0.8 1 1020304050 Unit number C o s t of uni t b=0.9 Every time production doubles, cost is reduced by a factor of 0.9 Typical LC slopes: Fab 90%, Assembly 75%, Material 98% 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Elements of a Cost Model Non-Recurring Cost Recurring Cost COST MODEL 0 40 80 120 2000 2010 2020 2030 Year N u m b e r o f p l anes Build Schedule Plane Wing Winglet RibsSkin Fuselage Weight RC/lb Subparts/lb NRC/lb Component Breakdown 0 0.4 0.8 1 0 1020304050 Unit number Cost of u n it Learning Curve Engineering Data & Performance 0 1 2 2003 2007 2011 2015 Year NRC ($B) NRC Distribution 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Typical Cost Modeling 1. Take empirical data from past programs. 2. Perform regression to get variation with selected parameters, e.g. cost vs. weight. 3. Apply “judgment factors” for your case. e.g. configuration factors, complexity factors, composite factors. There is widespread belief that aircraft manufacturers do not know what it actually costs to turn out their current products. 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Cost Modeling ? Aircraft is broken down into modules – Inner wing, outer wing, … – Modules are classified by type ? Wing, Empennage, Fuselage, … ? Cost per pound specified for each module type – Calibrated from existing cost models – Modified by other factors ? Learning effects ? Commonality effects ? Assembly & Integration: a separate “module” ? 2 cost categories: development & manufacturing Production run: a collection of modules 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Cost Modeling Plane Centerbody Landing Gear Propulsion Systems Final Assembly Payloads Winglet Outer Wing Inner Wing Wing … WeightIdentifier RC per pound Subparts per pound Area Labor Material & Equipment Support At this level, the degree of detail can range from e.g. “wing” to “rivet”. NRC per pound Tooling Engineering Other NRC time distribution 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Development Cost Data Baseline Engr. Baseline M.E. Baseline Tool Design Baseline ToolFab. Baseline Dev. Labs Baseline QA Baseline QA Baseline Dev. Labs Baseline Tool Fab. Baseline Tool Design Baseline M.E. Baseline Engr. Baseline QA Baseline Dev. Labs Baseline Tool Fab Baseline Tool Design Baseline M.E. Baseline Engr. non-dimensional labor hours non-dimensional time Boeing data for large commercial jet 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Development Cost Model ? Cashflow profiles based on beta curve: ? Typical development time ~6 years ? Learning effects captured – span, cost 11 )1()(   ED tKttc 0 0.01 0.02 0.04 0.05 0.06 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 normalized time Support Tool Fab Tool Design ME Engineering normalized cost (from Markish) 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Development Cost Model Wing 20% Empennage 9% Fuselage 37% Landing Gear 1% Installed Engines 8% Systems 17% Payloads 8% Representative non-recurring cost breakdown by parts for large commercial jet (from Markish). 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Development Cost Data For your reference: $/lb assembled from public domain weight and total cost estimates plus representative NRC breakdown by aircraft part (see Markish). Engineering ME Tool Design Tool Fab Support Totals 40.0% 10.0% 10.5% 34.8% 4.7% 100.0% Wing $7,093 $1,773 $1,862 $6,171 $833 $17,731 Empennage $20,862 $5,216 $5,476 $18,150 $2,451 $52,156 Fuselage $12,837 $3,209 $3,370 $11,169 $1,508 $32,093 Landing Gear $999 $250 $262 $869 $117 $2,499 Installed Engines $3,477 $869 $913 $3,025 $408 $8,691 Systems $13,723 $3,431 $3,602 $11,939 $1,612 $34,307 Payloads $4,305 $1,076 $1,130 $3,746 $506 $10,763 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Manufacturing Cost Model ? Aircraft built ? modules required ? Modules database – Records quantities, marginal costs – Apply learning curve effect by module, not by aircraft Labor Materials Support 85% 95% 95% time 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Manufacturing Cost Model Representative recurring cost breakdown by parts for large commercial jet (from Markish). Wing 27% Empennage 10% Fuselage 28% Landing Gear 3% Installed Engines 9% Systems 6% Payloads 11% Final Assembly 6% 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Manufacturing Cost Data For your reference: $/lb values assembled from public domain weight and total cost estimates plus representative RC breakdown by aircraft part (see Markish). Labor Materials Other Total Wing $609 $204 $88 $900 Empennage $1,614 $484 $233 $2,331 Fuselage $679 $190 $98 $967 Landing Gear $107 $98 $16 $221 Installed Engines $248 $91 $36 $374 Systems $315 $91 $46 $452 Payloads $405 $100 $59 $564 Final Assembly $58 $4 $3 $65 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY NASA Cost Models Online cost models available at http://www.jsc.nasa.gov/bu2/airframe.html e.g. Airframe Cost Model - simple model for estimating the development and production costs of aircraft airframes - based on military jet data - correlation with empty weight, max. speed, number of flight test vehicles, and production quantity 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Revenue Model Revenue model must predict market price and demand quantity. 0 10 20 30 40 50 60 70 80 90 1980 1985 1990 1995 2000 year deliveries A300 A310 A330 A340 747 767 777 MD-11 0 20 40 60 80 100 120 140 160 180 1985 1990 1995 2000 year price ($M) 767-200ER 767-300ER 777-200 777-300 747-400 MD-11 A300 A330 A340 Historical wide body data from Markish. No correlation found between price and quantity. 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Aircraft Pricing Personal aircraft Business jets? Military aircraft Cost-Based Pricing Market-Based Pricing Cost + Profit = Price Performance Operating Cost Competition Passenger Appeal Commercial transport Market Value Source: Schaufele 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Commercial Aircraft Pricing ? Total Airplane Related Operating Costs are fairly constant. ? Aircraft price must balance CAROC. COST/WEIGHT TRADE-OFF CAROC PRICE (Capital costs) Total AROC 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Business Jet Empirical Data Figure A7 in Roskam: AMP 1989 = log -1 {0.6570 + 1.4133 log W TO } AMP 1989 is predicted airplane market price in 1989 dollars Take-off weight: 10,000 lb < W TO < 60,000 lb BUT Gulfstream GIV and 737 BJ versions do not fit the linear trend. 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Commercial Jet Empirical Data Figure A9 in Roskam: AMP 1989 = log -1 {3.3191+ 0.8043 log W TO } AMP 1989 is predicted airplane market price in 1989 dollars Take-off weight: 60,000 lb < W TO < 1,000,000 lb 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Military Aircraft Empirical Data Figure A10 in Roskam: AMP 1989 = log -1 {2.3341+ 1.0586 log W TO } AMP 1989 is predicted airplane market price in 1989 dollars Take-off weight: 2,500 lb < W TO < 1,000,000 lb 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Revenue Model: Price ? Assumption: market price based on 1. Range 2. Payload 3. Cash Airplane-Related Operating Cost (CAROC) ? Regression model: ? Note that speed does not appear. No significant statistical relationship between price and speed was found in available data. )()()( 21 CAROCfRangekSeatskP  D 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Revenue Model: Price 0 10 20 30 40 50 60 70 80 0 1020304050607080 Actual price ($M) E s tim a te d p r i c e ($ M ) y=x Airbus Boeing Narrow bodies Estimated price ($M) Actual price ($M) Narrow bodies: 1.91 0.735( ) 0.427( ) ( )P Seats Range f CAROC  Model from Markish, price data from Aircraft Value News, The Airline Monitor, 2001. 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Revenue Model: Price Wide bodies: 2.76 0.508( ) 0.697( ) ( )P Seats Range f CAROC  0 20 40 60 80 100 120 140 160 0 20 40 60 80 100 120 140 160 Actual price ($M) E s tim a te d p r ic e ($ M ) y=x Airbus Boeing Wide bodies Estimated price ($M) Actual price ($M) Model from Markish, price data from Aircraft Value News, The Airline Monitor, 2001. 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Revenue Model: Quantity ? Demand forecasts – 3 sources: Airbus; Boeing; Airline Monitor – Expected deliveries over 20 years – Arranged by airplane seat category ? Given a new aircraft design: – Assign to a seat category – Assume a market share – Demand forecast ? 20-year production potential 0 500 1000 1500 2000 2500 3000 3500 4000 100 125 150 175+ 200 250 300 350 400 500+ Seat Category Q u a n tity Airbus Airline Monitor Boeing Seat Category Quantity 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Revenue Model: Dynamics ? Expected aircraft deliveries: forecasted ? Actual deliveries: unpredictable ? Observe historical trends: growth rate, volatility y = 94.571e 0.0228x R 2 = 0.3724 y = 52.776e 0.0167x R 2 = 0.4092 0 50 100 150 200 250 300 350 400 1 4 7 10 13 16 19 22 25 28 31 34 37 40 6-mo. period uni t s narrow wide 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Valuation Techniques The top 5 investor questions: ? How much will I need to invest? ? How much will I get back? ? When will I get my money back? ? How much is this going to cost me? ? How are you handling risk & uncertainty? Investment Criteria ? Net present value ? Payback ? Discounted payback ? Internal rate of return 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Net Present Value (NPV) ? Measure of present value of various cash flows in different periods in the future ? Cash flow in any given period discounted by the value of a dollar today at that point in the future – “Time is money” – A dollar tomorrow is worth less today since if properly invested, a dollar today would be worth more tomorrow ? Rate at which future cash flows are discounted is determined by the “discount rate” or “hurdle rate” – Discount rate is equal to the amount of interest the investor could earn in a single time period (usually a year) if s/he were to invest in a “safer” investment 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Calculating NPV ? Forecast the cash flows of the project over Its economic life – Treat investments as negative cash flow ? Determine the appropriate opportunity cost of capital (i.e. determine the discount rate r) ? Use opportunity cost of capital to discount the future cash flow of the project ? Sum the discounted cash flows to get the net present value (NPV)  NPV C 0  C 1 1r  C 2 1r 2 !  C T 1r T 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY NPV example Period Discount Factor Cash Flow Present Value 0 1 -150,000 -150,000 1 0.935 -100,000 -93,500 2 0.873 +300000 +261,000 Discount rate = 7% NPV = $18,400 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Discount Rate ? One of the problems with NPV: what discount rate should we use? ? The discount rate is often used to reflect the risk associated with a project: the riskier the project, use a higher discount rate ? Typical discount rates for commercial aircraft programs: 12-20% ? The higher the discount rate, the more it does not matter what you do in the future... 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Payback Period ? How long it takes before entire initial investment is recovered through revenue ? Insensitive to time value of money, i.e. no discounting ? Gives equal weight to cash flows before cut-off date & no weight to cash flows after cut-off date ? Cannot distinguish between projects with different NPV ? Difficult to decide on appropriate cut-off date 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Discounted payback ? Payback criterion modified to account for the time value of money – Cash flows before cut-off date are discounted ? Surmounts objection that equal weight is given to all flows before cut-off date ? Cash flows after cut-off date still not given any weight 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Internal rate of return (IRR) ? Investment criterion is “rate of return must be greater than the opportunity cost of capital” ? Internal rate of return is equal to the discount rate for which the NPV is equal to zero ? IRR solution is not unique – Multiple rates of return for same project ? IRR doesn’t always correlate with NPV – NPV does not always decrease as discount rate increases  NPV C 0  C 1 1IRR  C 2 1IRR 2 !  C T 1IRR T 0 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Decision Tree Analysis ? NPV analysis with different future scenarios ? Weighted by probability of event occurring 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Dynamic Programming ? A way of including uncertainty and flexibility in the program valuation ? Key features: ? Certain aspects of the system may be uncertain, e.g. the demand quantity for a given aircraft = UNCERTAINTY ? In reality, the decision-maker (aircraft manufacturer) has the ability to make decisions in real-time according to how the uncertainty evolves = FLEXIBILITY 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Dynamic Programming: Problem Formulation ? The firm: – Portfolio of designs – Sequential development phases – Decision making ? The market: – Sale price is steady – Quantity demanded is unpredictable – Units built = units demanded ? Problem objective: – Which aircraft to design? – Which aircraft to produce? – When? 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Dynamic Programming: Problem Elements 1. State variables s t 2. Control variables u t 3. Randomness 4. Profit function 5. Dynamics ? Solution: ? Solve iteratively. >@ ? ? ? ˉ ? -    )( 1 1 ),(max)( 11 tttttt u tt sFE r ussF t S 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Dynamic Programming: Operating Modes How to model decision making? 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Example: BWB ? Blended-Wing-Body (BWB): – Proposed new jet transport concept ? 250-seat, long range ? Part of a larger family sharing common centerbody bays, wings, ... Image taken from NASA's web site: http://www.nasa.gov. 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Example: BWB Simulation Run -4,000,000 -3,000,000 -2,000,000 -1,000,000 0 1,000,000 2,000,000 3,000,000 0 2 4 6 8 1012141618202224262830 time (years) cash flow ($K) 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 0 2 4 6 8 1012141618202224262830 time (years) operating mode 0 20 40 60 80 100 120 qua ntity demande d per year mode demand 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY Example: BWB Importance of Flexibility -10 -5 0 5 10 15 20 25 3 5 7 1118284469108171270 initial annual demand forecast pr ogr am val ue ( $ B) dynamic programming Net Present Value At baseline of 28 aircraft, DP value is $2.26B versus NPV value of $325M 9/19/2002 16.885 AEROSPACE COMPUTATIONAL DESIGN LABORATORY References Airbus Global Market Forecast, 2000-2019. Appendix G, Detailed passenger fleet results, p. 74. Aircraft Value News Aviation Newsletter www.aviationtoday.com/catalog.htm The Airline Monitor, ESG Aviation Services. Boeing Current Market Outlook, 2000. Appendix B, p. 42. Jane's All the World's Aircraft. London : Sampson Low, Marston & Co., 2001. Markish, J. Valuation Techniques for Commercial Aircraft Program Design, S.M. Thesis, MIT, June 2002. Markish, J. and Willcox, K. “Valuation Techniques for Commercial Aircraft Program Design,” AIAA Paper 2002-5612, presented at 9 th Multidisciplinary Analysis and Optimization Symposium, Atlanta, GA, September 2002. Markish, J. and Willcox, K., “A Value-Based Approach for Commercial Aircraft Conceptual Design,” in Proceedings of the ICAS2002 Congress, Toronto, September 2002. NASA Cost Estimating website, http://www.jsc.nasa.gov/bu2/airframe.html Roskam, J., Airplane Design Part VIII, 1990. Raymer, D., Aircraft Design: A Conceptual Approach, 3 rd edition, 1999. Schaufele, R., The Elements of Aircraft Preliminary Design, 2000.