Issues, methods and organization
for costing the CLIC accelerator project
Philippe Lebrun
Meeting on costing of CLIC detector
CERN, 26 April 2010
Ph. Lebrun - 100426
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
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
Development of circular accelerators
Lawrence’s first cyclotron
(1930)
Large Hadron Collider
(2009)
Ph. Lebrun - 100426
Cost of projects keep increasing
Cost of CERN accelerators
Construction cost [MCHF of 2008]
4000
3500
LHC
Limit of funding capability ?
3000
SPS+SPPbarS
2500
SPS
LEP+LEP2
2000
LEP
1500
1000
500
0
1950
ISR
PS
1960
1970
1980
Year of completion
Ph. Lebrun - 100426
1990
2000
2010
Cost structure of LEP and LHC
LEP
9%
•
•
•
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
30%
Accelerator infrastructure
Civil engineering
Injectors
43%
18%
LHC
11%
Accelerator components
13%
Accelerator infrastructure
Civil engineering
Injectors
8%
68%
Ph. Lebrun - 100426
Accelerator components
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
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
CLIC analytical costing based on PBS
level 1
Beam and Services
Domain
level 2
Technical responsible
level 3
Sub-domain
level 4
System
level 5
Component
Main Beam Production
1.1 Injectors
L. Rinolfi
1.1.1.
1.1.2.
1.1.3.
1.1.4.
1.1.5.
1.1.6.
1.1.7.
1.2 Damping Rings
Y. Papaphilippou
1.2.1.
1.2.2.
1.2.3.
1.2.4.
Coordinators per
domain/subdomain
1.3. Beam transport
L. Rinolfi
1.3.1.
1.3.2.
1.3.3.
1.3.4.
1.3.5.
1.3.6.
1.3.7.
1.3.8.
1.3.9.
1.3.10.
1.3.11.
L. Rinolfi
Thermoionic gun unpolarized ePrimary e- beam linac for e+
e-/e+ Target
Pre-injector Linac for e+
DC gun Polarised ePre-injector Linac for eInjector Linac
Y. Papaphilippou
Pre-damping Ring e+
Pre-damping Ring eDamping Ring e+
Damping Ring eL. Rinolfi
Bunch Compressor #1 e+
Bunch Compressor #1 eBooster Linac
Transfer to Tunnel e+
Transfer to Tunnel eLong Transfer Line e+
Long Transfer Line eTurnaround e+
Turnaround eBunch compressor #2 e+
Bunch compressor #2 e-
Component level
Drive Beam Production
Identified for analytical costing
based on level 5 description
2.1 Injectors
tbc
2.2. Frequency Multiplication
B. Jeanneret
2.3. Beam transport
B. Jeanneret
3.1. Two-beam modules
G. Riddone
2.1.1. Linac e+
2.1.2. Linac eB. Jeanneret
2.2.1. Delay Loop e+
2.2.2. Delay Loop e2.2.3. Combiner Ring #1 e+
2.2.4. Combiner Ring #1 e2.2.5. Combiner Ring #2 e+
2.2.6. Combiner Ring #2 eB. Jeanneret
2.3.1. Transfer to Tunnel e+
2.3.2. Transfer to Tunnel e2.3.3. Long Transfer Line e+
2.3.4. Long Transfer Line e2.3.5. Turnaround and Bunch Compressor e+
2.3.6. Turnaround and Bunch Compressor e-
Two-beam accelerator
3.1.1.
3.1.2
3.1.3
3.1.4
3.1.5
3.1.6
3.1.7
3.1.8
3.1.9
3.1.10
3.2. Post decelerator
Two-Beam Modules Type 0 e+
Two-Beam Modules Type 1 e+
Two-Beam Modules Type 2 e+
Two-Beam Modules Type 3 e+
Two-Beam Modules Type 4 e+
Two-Beam Modules Type 0 eTwo-Beam Modules Type 1 eTwo-Beam Modules Type 2 eTwo-Beam Modules Type 3 eTwo-Beam Modules Type 4 e-
B. Jeanneret
3.2.1. Post Decelerator e+
3.2.2. Post Decelerator e-
Interaction Region
4.1. Beam Delivery Systems
tbc
4.2. Machine-Detector Interface
tbc
4.3. Experimental Area
tbc
4.4. Post-collision line
tbc
5.1. Civil Engineering
J. Osborne
K. Schirm (R. Tomas)
4.1.1. Beam Delivery System e+
4.1.2. Beam Delivery System eK. Schirm (D. Schulte)
4.2.1. Experiment A
4.2.2 Experiment B
K. Schirm (L. Linssen)
4.3.1. Common Facilities
4.3.2. Experiment A
4.3.3. Experiment B
K. Schirm (K. Elsener)
4.4.1. Post-collision line e+
4.4.2. Post-collision line e-
Infrastructure and Services
5.7. Survey
J. Osborne
5.1.1. Underground Facilities
5.1.2. Surface Structures
5.1.3. Site Development
J. Osborne (C. Jach)
J. Osborne
5.2.1 AC network
5.2.2 DC network
H. Schmickler
J. Osborne
5.3.1. Personnel Access Control
5.3.2. Global Accelerator Control
5.3.3. Industrial Control
5.3.4. Data Network
J. Osborne (J. Inigo-Golfin)
J. Osborne
5.4.1. Water systems
5.4.2. HVAC
5.4.3. Cryogenics
5.4.4. Gas
J. Osborne (K. Kershaw)
J. Osborne
5.5.1. Surface and Vertical Shafts
5.5.2. Tunnels and Inclined Shafts
J. Osborne (F. Corsanego)
J. Osborne
5.6.1. Radiation Safety
5.6.2. Fire Safety
J. Osborne (H. Mainaud-Durand) J. Osborne
5.8. Machine Operation
tbd
5.2. Electricity
5.3. Access and Communications
5.4. Fluids
5.5. Transport / installation
5.6. Safety
Ph. Lebrun - 100426
Level 4 system
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
RF System
RF Powering System
Vacuum System
Magnet Powering System
Magnet System
Cooling System
Beam Instrumentation System
Supporting System
Alignment system
Kicker system
Cryogenic system
Laser system
Collimation system
Stabilisation System
Absorbers
Damping system
Electron Gun
RF deflectors
Installation
Commissioning
List of systems standardized
Contact experts per system
.
Costing multi-MW klystrons
Ph. Lebrun - 100426
Scaling klystron cost
E. Jensen
Ph. Lebrun - 100426
Optimizing klystron initial cost
E. Jensen
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Optimizing klystron cost including
replacement
E. Jensen
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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
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
Ph. Lebrun - 100426
CLIC Cost & Schedule WG
Communication & reporting lines
CLIC Technical Committee
PBS, developments & alternatives
Other CLIC WG
Other CLIC WG
reports to
CLIC Steering Committee
ILC GDE Cost Team
Information, methodology
CLIC Cost & Schedule WG
Configuration
Technical design
System group
Analytical costing
Other CLIC WG
System group
System group
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
Ph. Lebrun - 100426
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
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
Ph. Lebrun - 100426
Cost & efficiency optimization for CLIC
RF frequency
RF phase advance per cell
Accelerating gradient (loaded)
Cavity iris aperture
Cavity iris thickness
Wakefields
Emittance growth
Y
Bunch charge
Bunch separation
Surface field < 260 MV/m
Surface heating < 56 K
Power input < 18 MW/mm ns0.33
Luminosity per input power
Cost
Ph. Lebrun - 100426
iterate
N
Cost & efficiency optimization for CLIC
Ph. Lebrun - 100426
Feedback to technical design:
some cost drivers & potential saving options for CLIC
Cost driver
Cost
saving
impact
Accelerating structure
stacked disc
construction
Cost mitigation option
Alternative
Risk/benefit of
alternative
Specific actions
H
Quadrant construction
Technical validation
pending
Industrial cost studies,
prototyping
Accelerating structure
vacuum tank
M
Sealed construction
Leakage
Prototyping
Production yield of
accelerating structures
M to H
Replacement of 80
MV/m accelerating
structures
M
PETS on-off mechanism
M
Develop and
industrialize
Drive beam
quadrupoles:
unprecedented number
M
Powering of drive beam
quadrupoles
M
Reliability of power
converters
M
Production control and
testing
Industrial prototyping &
preseries production
Reinstall and reuse
80 MV/m structures
Maximum energy
Automated
manufacturing
Customization to
position in decelerator
Allows series powering
To be developed
Specification from beam
physics, industrial study
Novel powering scheme
("intelligent bus")
Series powering (plus
trim windings?)
Reduce cabling, limit
power consumption
Specification from beam
physics
Hot spares
Improved availability of
CLIC
Specification from beam
physics
Cost impact
L
M
H
Order of 10 MCHF
Order of 100 MCHF
Order of 1 BCHF
Ph. Lebrun - 100426
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
CLIC two-beam modules
Complexity, number, integration
G. Riddone
CLIC 3 TeV (per linac)
Modules: 10462
Accelerating str.: 71406 PETS: 35703
MB quadrupoles: 1996
DB quadrupoles: 20924
CLIC 500 GeV (per linac)
Modules: 2124
Accelerating str.: 13156 PETS: 6578
MB quadrupoles: 929
DB quadrupoles: 4248
Ph. Lebrun - 100426
CLIC vs LHC components:
different solutions for different series numbers
Maximum number of units per variant
1.E+07
Automatic chains
AS discs
Superconductors
Magnet components
Magnets
Power converters
Cryolines
Vacuum
1.E+06
1.E+05
CLIC TBM
1.E+04
AS quadrants
CLIC AS
CLIC PETS
CLIC Quads
Flexible workshops
1.E+03
Flexible cells, manual work
1.E+02
1.E+01
1.E+00
1
100
10
Number of variants
Ph. Lebrun - 100426
1000
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) nlog2a
with a = « learning percentage », i.e. remaining cost fraction when
production is doubled
• Cumulative cost of first nth units
C(n) = c(1) n1+log2a / (1+log2a)
with C(n)/n = average unit cost of first nth units produced
• n = number per production line ≠ total number in project
Ph. Lebrun - 100426
Experimental learning curve:
LHC superconducting dipole magnets
Collared coils
Cold masses
P. Fessia
Ph. Lebrun - 100426
Learning coefficients
P. Fessia
Ph. Lebrun - 100426
Effect of learning coefficient
on average unit cost up to rank N
Learning curve: average unit cost
Relative average unit cost of first N units
1
0.9
0.8
0.7
0.6
0.5
0.4
a=0.80
a=0.85
a=0.90
a=0.95
a=0.98
0.3
0.2
0.1
0
1
10
100
1000
Rank N
Ph. Lebrun - 100426
10000
100000
1000000
Saturation of learning process
has little impact on total cost
Learning curve: effect of saturation
Relative total cost increase when saturation
1
a = 0.70
a = 0.75
a = 0.80
a = 0.85
a = 0.90
a = 0.95
a = 0.98
0.1
0.01
0.001
0.0001
0
0.1
0.2
0.3
0.4
0.5
0.6
Relative rank at saturation
Ph. Lebrun - 100426
0.7
0.8
0.9
1
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
Cost variance factors
•
Decreasing control of project responsible
•
Technical definition
Technical design
–
–
–
–
Evolution of system configuration
Maturity of component design
Technology breakthroughs
Variation of applicable regulations
–
–
–
–
Qualification & experience of vendors
State of completion of R&D, of industrialization
Series production, automation & learning curve
Rejection rate of production process
Industrial execution
•
Structure of market
•
Commercial strategy of vendor
•
Inflation and escalation
•
International procurement
– Mono/oligopoly
– Mono/oligopsone
Engineering judgement
of responsible
Contract adjudication
Procurement
Reflected in scatter of offers
received from vendors (LHC
experience)
– Market penetration
– Competing productions
– Raw materials
– Industrial prices
– Exchange rates
– Taxes, custom duties
Ph. Lebrun - 100426
Tracked and compensated
Outside project control
Observed tender prices
for LHC accelerator components
All data (218 offers)
120
120
100
Frequency
Exponential fit
80
80
60
60
Adjusted to mean (1.46) and
total number (218) of sample
Ph. Lebrun
- 100426
Tender price relative
to lowest
bid [bin upper limit]
5
or
e
M
4.
75
4.
5
4.
25
4
3.
75
3.
5
3.
25
3
2.
75
0
2.
5
0
2.
25
20
2
20
1.
75
40
1.
5
40
1.
25
Frequency
100
Sampling from an exponential PDF
(m=0, s=1)
1
0.9
0.8
Exponentielle
0.7
•
f(x)
0.6
0.5
0.4
0.3
0.2
0.1
0
-5
-4
-3
-2
-1
0
1
2
3
4
5
x
1
•
0.9
0.8
Exponentielle
0.7
•
F(x)
0.6
0.5
0.4
0.3
0.2
0.1
Ph. Lebrun - 100426
0
-5
-4
-3
-2
-1
0
x
1
2
3
4
5
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
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 s = 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 s = 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 s = 1/na
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, s = 0.46
• We can therefore estimate the expected relative dispersion on paid prices
 s = 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
Ph. Lebrun - 100426
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
Exchange rates and cost escalation
Currency A
Exchange rate 1
Time 1
Time 1
?
Escalation
Index a
Currency A
Exchange rate 2
Escalation
Index b
Currency B
Time 2
Time 2
•
Currency B
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)
Ph. Lebrun - 100426
Industrial price indices (CH)
Indice des prix à la production, Suisse
Source: Office Fédéral de la Statistique
(Indices de la construction ramenés à mai 2003 = 100)
140
Métaux [mai 2003 = 100]
Machines [mai 2003 = 100]
Caoutchouc, plastiques [mai 2003 = 100]
Appareils électriques [mai 2003 = 100]
Construction bâtiment [mai 2003 = 100]
Construction génie civil [mai 2003 = 100]
Global arts & métiers industrie [mai 2003 = 100]
Global construction [mai 2003 = 100]
135
130
125
120
115
110
105
Fe
Ja
n08
b0
M 8
ar
-0
Ap 8
r-0
M 8
ay
-0
Ju 8
n08
Ju
l-0
Au 8
g0
Se 8
p0
O 8
ct
-0
N 8
ov
-0
D 8
ec
-0
Ja 8
n0
Fe 9
b0
M 9
ar
-0
Ap 9
r-0
M 9
ay
-0
Ju 9
n09
Ju
l-0
Au 9
g0
Se 9
p0
O 9
ct
-0
N 9
ov
-0
D 9
ec
-0
9
100
Month-Year
Ph. Lebrun - 100426
Swiss vs CERN indices
Comparison of Swiss industrial and CERN materials indices (base 100 = June 2002)
120.0
CH Global Arts et Métiers Industrie
CH Global Construction
Current value
115.0
CERN Materials
110.0
105.0
100.0
95.0
02
na
J
2
-0
l
Ju
03
na
J
3
-0
l
Ju
04
na
J
4
-0
l
Ju
05
na
J
5
-0
l
Ju
06
na
J
6
-0
l
Ju
07
na
J
Month-Year
Ph. Lebrun - 100426
7
-0
l
Ju
08
na
J
8
l-0
u
J
09
na
J
9
l-0
u
J
10
na
J
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 sconfig
– Price uncertainty in industrial procurement
• Estimate n number of valid offers to be received
• Apply sindustry = 50/n %
– Economical & financial context
• Deterministic
• Track currency exchange rates and industrial indices
• Estimate r.m.s. sum of sconfig and sindustry
• 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
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. 13011308
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. 11011104
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)
Ph. Lebrun - 100426