what complexity science has to offer industry
DESCRIPTION
Prof Paul Davies Thales UK. What Complexity Science has to offer Industry. How I discovered complexity. Open Systems. Emergence. Autopoiesis. Holism vs Reductionism. Modern views of complex systems. What can complexity science offer industrial operations?. - PowerPoint PPT PresentationTRANSCRIPT
March 2013
What Complexity Science has to offer Industry
Prof Paul Davies
Thales UK
March 20132
How I discovered complexity...
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Modern views of complex systems
March 2013
What can complexity science offer industrial operations?
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Industrial projects - the basic V model
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Multiple nested V models
x8
Userrequirements
definition
Installation& validation
Operationalsystem
Proposedcharacteristics
Componentdevelopment Components
Deliveredcomponents
Integratedsystem
Systemrequirements
definition
Architecturaldesign
Integration&
verification
Allocatedrequirements
Proposedcharacteristics
Allocatedrequirements
Proposedcharacteristics
Integratedsubsystems
Suppliedsubsystems
Systemrequirements
definition
Integration&
verification
Architecturaldesign
Allocatedrequirements
Proposedcharacteristics
Integratedsubsystems
Suppliedsubsystems
Systemrequirements
definition
Integration&
verification
Architecturaldesign
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Ring Value Lifecycle model
CommunitySituation
Value of System Quantified
Effects on Problem Known
Context Adapted
Real Effect of PSS Known
OperationalResults
PSS Activated
Operational Readiness
PSS TestedComponents
Specified – Developed - Assembled
PSS ArchitectedAnd Designed
PSS Envisioned
PSS S><R Specified
Intervention Strategy
Solution EffectEnvisioned
Problem System Understood
Problem Discerned
Focus on Value
Focus on Purpose
Focus on System
After Jack Ring
PSS = Problem (proposed) System Solution
AssessAnalyse
Generateoptions
AssessAnalyse
Generateoptions
AssessAnalyse
Generateoptions
CommunitySituation
Value of System Quantified
Effects on Problem Known
Context Adapted
Real Effect of PSS Known
OperationalResults
PSS Activated
Operational Readiness
PSS TestedComponents
Specified – Developed - Assembled
PSS ArchitectedAnd Designed
PSS Envisioned
PSS S><R Specified
Intervention Strategy
Solution EffectEnvisioned
Problem System Understood
Problem Discerned
Focus on Value
Focus on Purpose
Focus on System
After Jack Ring
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Potential modelling approaches
Explicit chained activities (classical project management tools) + Monte Carlo simulation
Stochastic models introducing rework phase networks? graph-theoretic critical path analysis?
ODEs with feedback loops System dynamics
Representation using category theory
??
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System Dynamics Example
Bass, F.M., 1969. A New Product Growth For Model Consumer Durables. Management Science, Vol. 15(5), pp. 215 – 227. Sterman, J.D., 2000. Business dynamics: systems thinking and modeling for a complex world 1st ed. S. Isenberg, ed., Jeffrey J. Shelstad.
PotentialAdopters P
Adopters AAdoption Rate AR
Adoption fromWord of Mouth
++
Total Population N
AdoptionFraction I
Contact Rate c
-
Adoption fromAdvertising
AdvertisingEffectiveness a
+
+
+ +
+
+
B R
B
Market Saturation
Market Saturation Word of Mouth
Bass Diffusion (from Sterman)
Adopters A8,000
6,000
4,000
2,000
0Adoption Rate AR
600
450
300
150
00 18 36
Time (Month)
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Rework Loop
Suggested by Cooper (1993) and used with System
Dynamics (Cooper & Lee, 2009)
Cooper, K. G., & Mullen, T. W. (1993). Plowshares - The Rework Cycles of Defense and Commerical Software. American Programmer, 6(5).Cooper, K., & Lee, G. (2009). Managing the Dynamics of Projects and Changes at Fluor (pp. 1–27).
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Our Model
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Model Outputs
Cumulative Work Done GraphWork really done
400
300
200
100
0
0 4 8 12 16 20 24 28 32 36 40Time (Month)
Req
uire
men
t
Work really done : baseline
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Model Outputs
Work Rate GraphGood
80
60
40
20
0
0 4 8 12 16 20 24 28 32 36 40Time (Month)
Req
uire
men
t/Mon
th
Good : baseline
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Discussion of Results
Mawby, D., & Stupples, D. (2002). Systems Thinking for Managing Projects. Engineering Management Conference, 2002. IEMC ’02 (pp. 344–349). IEEE International.Putnam, L. H. (1978). A General Empirical Solution to the Macro Software Sizing and Estimating Problem. IEEE Transactions on Software Engineering, SE-4(4), 345–361.
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Discussion of Results
The model is producing planned parameter profiles similar to what is
expected, and which fit the PNR distribution suggested by Putnam
(1978) and incorporating the effects of rework as suggested by
Mawby & Stupples (2002)
The underlying behavioral assumptions are being explored with a
sensitivity analysis
The model needs calibration and validation against real project data
Mawby, D., & Stupples, D. (2002). Systems Thinking for Managing Projects. Engineering Management Conference, 2002. IEMC ’02 (pp. 344–349). IEEE International.Putnam, L. H. (1978). A General Empirical Solution to the Macro Software Sizing and Estimating Problem. IEEE Transactions on Software Engineering, SE-4(4), 345–361.
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Sensitivity Analysis
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So, why engage with Academia?
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Economic Indicators
1
4
3
2
-1
Q4/08
Q1/05
“By 2020, 90% of the world’s manufacturing will be based in the BRIC countries”
“If it was purely down to the cost of wages, the UK wouldhave gone out of business years ago”
White collar average wages:UK $44000; India $4000
227,000 Elec Engapplicants / year
<7,000 Elec Enggraduates / year
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So why is the UK still in business?
Because we do some things better: Innovation
Staying ahead of the competition
System integration and risk-taking
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Innovation Streams
Str
ateg
ic K
ey Q
ues
tio
ns
10 years
Consultancy
<0.5%
Res
earc
h 1
Res
earc
h n
3-5 years
Universities etc
~3%
Development
0-3 years
Internal
17 - 35%
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Technology Readiness Levels
Inn
ova
tion
fun
din
g“V
alle
y o
f De
ath
”
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General Model of University Activity Thales (UK)
Undergraduate
Postgraduate & Research
University
Graduate Recruitment/Milk Rounds Summer
Placements
Talks to final year students
Recruitment Focus
PhD & EngD Research
Collaborative
Research FP7 etc
Industrial Clustered
Research (MVCE etc)
Funded Research
ASTRAEA, OCIAM, etc
Research Focus
Techno Watch
Schools
Encouraging
participation in
STEM subjects
Industry Advisory Panels
Sponsored Chairs
Visiting Professors
Teaching
Supporting Masters Projects
Supporting Doctoral Students
(PhD & EngD)
Image Focus
CPD Focus
Public coursesTailored courses
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Summary of Technical Research Engagement
TRL TimescaleCost to
IndustrialIP Leverage Hassle
CP 1 to 5 up to 3 yrs Staff time contract 2:1 high
SA 1 to 4 typ 3 yrs Can be high contract 2:1 possible medium
IC 1 to 5 up to 3 yrs ~£50k/yr contract high low
CR 1 to 5Depends on
contractCan be high
with FECcompany low medium
SP/D 1 to 3 3.5 yrs £8k/pa contract3:1 with CASE
low
SP/M 4 to 5 3 months Staff time student - low
UP 1 to 3 up to 5 yrs Staff time university - low
CP = Collaborative ProjectsSA = Strategic Alliance IC = Industrial Clustered CR = Contract Research
SP/D = Student PhD Projects SP/M = Student MSc Projects
UP = University Projects
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What you’re selling...
“Transferrable skills”• Mathematical modelling• Proven ability to follow a single complex project through to completion, plus reporting rigour• Understanding of the fundamental interconnectedness of all things• Comfort with, and ability to represent, uncertainty
What you haven’t got, necessarily:• Collaborative project skills• Awareness / skills in the commercial world• Multidisciplinarity
March 2013
Questions?