1. Ph. Lebrun - 100426 Issues, methods and organization for costing the CLIC accelerator project Philippe Lebrun Meeting on costing of CLIC detector CERN, 26 April 2010

2. Contents Cost of high-energy accelerators Cost estimate methods, organization & tools Feedback to technical design & optimization Large series, manufacturing techniques & learning curves Elements of cost risk analysis Coping with exchange rates & cost escalation Ph. Lebrun - 100426

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4. Development of circular accelerators Lawrence’s first cyclotron (1930) 80 years 10 5 increase in size 10 8 increase in beam energy Large Hadron Collider (2009)

5. Ph. Lebrun - 100426 Cost of projects keep increasing Limit of funding capability ?

6. Ph. Lebrun - 100426 Cost structure of LEP and LHC Accelerator components account only for ~1/3 of the cost of large accelerators projects Most of the budget goes into civil engineering, infrastructure and services, for which market prices are usually available LHC is atypical –re-use of tunnel and some infrastructure from LEP –large absolute cost of superconducting technology further reduces proportion of infrastructure

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8. Cost estimate methods Analytical –Based on project/work breakdown structure –Define production techniques –Estimate fixed costs –Establish unit costs & quantities (including production yield and rejection/reprocessing rates) –In case of large series, introduce learning curve (see later) Scaling –Establish scaling estimator(s) and scaling law(s), including conditions & range of application Empirical « First-principles » based –Define reference project(s) and fit data, mutatis mutandis In most cases, hybrid between these methods Ph. Lebrun - 100426

9. CLIC analytical costing based on PBS Component level List of systems standardized Contact experts per system Coordinators per domain/subdomain Identified for analytical costing based on level 5 description

10. Costing multi-MW klystrons Ph. Lebrun - 100426

11. Scaling klystron cost E. Jensen

12. Ph. Lebrun - 100426 Optimizing klystron initial cost E. Jensen

13. Ph. Lebrun - 100426 Optimizing klystron cost including replacement E. Jensen

14. Some issues in estimating operation costs Utilities & consumables –Variability of electricity costs: operation schedule needed –Include externalities in marginal cost Distribution losses Heat rejection Carbon footprint? –Inventory losses & replenishment (fluids) Maintenance & repair –Periodic maintenance MTBF of equipment Cost of spares and scheduled replacement –Emergency repair Comprehensive cost impact of accidents: risk analysis Model for down time and repair interventions Personnel –Staff model for operations group/team –Out- or insourcing? –Personnel stability & investment in training Ph. Lebrun - 100426

15. Organization for CLIC cost estimate CLIC Cost & Schedule WG established Communication and reporting lines defined Web node active (access protected) PBS updated and completed for 3 TeV and 500 GeV phases, including standardization of level 4 technical systems

16. Ph. Lebrun - 100426 CLIC Cost & Schedule WG Communication & reporting lines CLIC Cost & Schedule WG CLIC Steering Committee CLIC Technical Committee Other CLIC WG System group ILC GDE Cost Team Other CLIC WG System group reports to PBS, developments & alternatives Configuration Analytical costing Information, methodology Technical design

17. Ph. Lebrun - 100426 CLIC Study Costing Tool CLIC Study Costing Tool developed & maintained by CERN GS-AIS Operational, on-line from C&S WG web page (access protected) Includes features for currency conversion, price escalation and uncertainty Demonstrations to users in C&S WG meetings

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19. Cost drivers, models and optimization Limitation of PBS/WBS-based approach: does not look at interplay between technical systems ⇒ risk of local (« mountain lake ») optimization Hence importance of communication among experts to develop global view –cost WG –informal discussion with system specialists, –understanding of rationale behind scaling laws –pluridisciplinary models –feedback to project team Cost scaling models only exist for limited number of components or subsystems Targeted cost studies by industrial companies important for –providing up-to-date, relevant data –establishing limits of validity of scaling laws –exploring technical alternatives & breakthroughs

20. Cost & efficiency optimization for CLIC RF frequency RF phase advance per cell Accelerating gradient (loaded) Cavity iris aperture Cavity iris thickness Bunch charge Bunch separation Surface field < 260 MV/m Surface heating < 56 K Power input < 18 MW/mm ns 0.33 Wakefields Emittance growth Luminosity per input power Cost N Y iterate Ph. Lebrun - 100426

21. Cost & efficiency optimization for CLIC Ph. Lebrun - 100426

22. Feedback to technical design: some cost drivers & potential saving options for CLIC Cost driverCost saving impact Cost mitigation optionAlternativeRisk/benefit of alternative Specific actions Accelerating structure stacked disc construction HQuadrant constructionTechnical validation pending Industrial cost studies, prototyping Accelerating structure vacuum tank MSealed constructionLeakagePrototyping Production yield of accelerating structures M to HProduction control and testing Industrial prototyping & preseries production Replacement of 80 MV/m accelerating structures MReinstall and reuse 80 MV/m structures Maximum energy PETS on-off mechanismMDevelop and industrialize Drive beam quadrupoles: unprecedented number MAutomated manufacturing Customization to position in decelerator Allows series powering To be developed Specification from beam physics, industrial study Powering of drive beam quadrupoles MNovel powering scheme ("intelligent bus") Series powering (plus trim windings?) Reduce cabling, limit power consumption Specification from beam physics Reliability of power converters MHot sparesImproved availability of CLIC Specification from beam physics Cost impact LOrder of 10 MCHF MOrder of 100 MCHF HOrder of 1 BCHF Ph. Lebrun - 100426

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24. CLIC two-beam modules Complexity, number, integration CLIC 3 TeV (per linac) Modules: 10462 Accelerating str.: 71406PETS: 35703 MB quadrupoles: 1996DB quadrupoles: 20924 CLIC 3 TeV (per linac) Modules: 10462 Accelerating str.: 71406PETS: 35703 MB quadrupoles: 1996DB quadrupoles: 20924 CLIC 500 GeV (per linac) Modules: 2124 Accelerating str.: 13156PETS: 6578 MB quadrupoles: 929DB quadrupoles: 4248 CLIC 500 GeV (per linac) Modules: 2124 Accelerating str.: 13156PETS: 6578 MB quadrupoles: 929DB quadrupoles: 4248 G. Riddone

25. Ph. Lebrun - 100426 CLIC vs LHC components: different solutions for different series numbers Flexible cells, manual work Flexible workshops Automatic chains CLIC AS CLIC PETS CLIC Quads CLIC TBM AS quadrants AS discs

26. Ph. Lebrun - 100426 Learning curve: theory T.P. Wright, Factors affecting the cost of airplanes, Journ. Aero. Sci. (1936) Unit cost c(n) of nth unit produced c(n) = c(1) n log 2 a with a = « learning percentage », i.e. remaining cost fraction when production is doubled Cumulative cost of first nth units C(n) = c(1) n 1+log 2 a / (1+log 2 a) with C(n)/n = average unit cost of first nth units produced n = number per production line ≠ total number in project

27. Experimental learning curve: LHC superconducting dipole magnets P. Fessia Collared coils Cold masses Ph. Lebrun - 100426

28. Learning coefficients P. Fessia

29. Ph. Lebrun - 100426 Effect of learning coefficient on average unit cost up to rank N

30. Ph. Lebrun - 100426 Saturation of learning process has little impact on total cost

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32. Cost variance factors Technical design –Evolution of system configuration –Maturity of component design –Technology breakthroughs –Variation of applicable regulations Industrial execution –Qualification & experience of vendors –State of completion of R&D, of industrialization –Series production, automation & learning curve –Rejection rate of production process Structure of market –Mono/oligopoly –Mono/oligopsone Commercial strategy of vendor –Market penetration –Competing productions Inflation and escalation –Raw materials –Industrial prices International procurement –Exchange rates –Taxes, custom duties Engineering judgement of responsible Tracked and compensated Decreasing control of project responsible Outside project control Procurement Contract adjudication Technical definition Reflected in scatter of offers received from vendors (LHC experience)

33. Ph. Lebrun - 100426 Observed tender prices for LHC accelerator components Adjusted to mean (1.46) and total number (218) of sample

34. Ph. Lebrun - 100426 Sampling from an exponential PDF (m=0,  =1) In response to an invitation to tender, consider n (valid) offers distributed according to an exponential PDF: application of the CERN purchasing rule will lead to select the lowest bidder What is the PDF of the lowest bidders, i.e. of the prices effectively paid? In the following, reasoning on the integral PDF

35. Ph. Lebrun - 100426 From distribution of offers to distribution of prices Consider two valid offers X1, X2 following same exponential distribution with P(Xi<x) = F(x) = 1 – exp[-a(x-b)] ⇒ m = b + 1/a and  = 1/a Price paid (lowest valid offer) is Y = min(X1, X2): what is the probability distribution of Y? Estimate P(Y<x) = P(X1<x or X2<x) = G(x) Combined probability theorem P(X1<x or X2<x) = P(X1<x) + P(X2<x) – P(X1<x and X2<x) If X1 and X2 uncorrelated, P(X1<x and X2<x) = P(X1<x) * P(X2<x) Hence, P(X1<x or X2<x) = P(X1<x) + P(X2<x) – P(X1<x) * P(X2<x) and G(x) = 2 F(x) – F(x) 2 = 1 – exp[-2a(x-b)] ⇒ Y follows exponential distribution with m = b + 1/2a and  = 1/2a By recurrence, if n uncorrelated valid offers X1, X2,…Xn are received, the price paid Y = min (X1, X2,…Xn) will follow an exponential distribution with m = b + 1/na and  = 1/na

36. Ph. Lebrun - 100426 Dispersion of prices due to procurement uncertainties For LHC accelerator components –48 contracts –218 offers, i.e. 4.54 offers per contract on average From exponential fit of statistical data on offers, m = 1.46,  = 0.46 We can therefore estimate the expected relative dispersion on paid prices  = 0.46/4.54 ≈ 0.1 ⇒ based on LHC experience, the relative standard deviation on component prices due to procurement uncertainties can be taken as 50/n %, where n is the expected number of valid offers

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38. Exchange rates and cost escalation Exchange rate fluctuations should ideally reflect evolution of purchasing power of currencies, but –Economic parities offset by financial effects –Variety of escalation indices in each currency Choose « reference currency » (CHF) and apply relevant escalation indices in reference country (Office Fédéral de la Statistique) Currency A Time 1 Currency B Time 1 Exchange rate 1 Currency A Time 2 Currency B Time 2 Exchange rate 2 Escalation Index a Escalation Index b ? Ph. Lebrun - 100426

39. Industrial price indices (CH)

40. Ph. Lebrun - 100426 Swiss vs CERN indices

41. Ph. Lebrun - 100426 Proposed method for CLIC cost risk assessment Separate cost risk factors in three classes, assumed independent –Technical design maturity & evolution of configuration Judgement of « domain responsible » Rank in 3 levels, defining numerical values of  config –Price uncertainty in industrial procurement Estimate n number of valid offers to be received Apply  industry = 50/n % –Economical & financial context Deterministic Track currency exchange rates and industrial indices Estimate r.m.s. sum of  config and  industry Compensate economical & financial effects –Choice of CHF as reference currency –Applications of compound indices from Office Fédéral de la Statistique (CH) Arts et métiers – Industrie for technical components Construction for civil engineering

42. Ph. Lebrun - 100426 A few references I. Chvidchenko, Gestion des grands projets, Cours de Sup’Aéro, CEPADUES Editions, Toulouse (1992) C. Roche, Government, industry, accelerators, Frontiers of Accelerator Technology, World Scientific (1996) pp. 743-757 Ph. Lebrun, Estimation du coût marginal de l’énergie consommée par la cryogénie du LHC, LHC Project Note 92 (1997) S. Claudet et al., Economics of large helium cryogenic systems: experience from recent projects at CERN, Adv. Cryo. Eng. 45B Plenum Publishers (2000), pp. 1301- 1308 Management de projet: gestion du risque, norme FD X 50-117, AFNOR, Saint Denis (2003) Project Risk Management, in PMBOK ® Guide, 3rd edition, Project Management Institute, Newton Square (2004), pp. 237-268 P. Fessia et al., Industrial learning curves: series production of the LHC main superconducting dipoles, IEEE Trans. Appl. Superconductivity 17 2 (2007) pp. 1101- 1104 The CLIC Study Team, CLIC 2008 parameters, CLIC Note 764 (2008) GAO Cost Estimating & Assessment Guide, United States Government Accountability Office, GAO-09-3SP (2009) P. Garbincius et al., Assessing risk in costing high-energy accelerators: from existing projects to the future linear collider, submitted to IPAC’2010, Kyoto (2010)