Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT. 29. Jeep Grand Cherokee. Chrysler 300C. Chrysler Voyager. Jeep Grand Cherokee. 3 different types ...
Agile SYSTEMS ENGINEERING vs. AGILE SYSTEMS Engineering Prof. Reinhard Haberfellner Technical University, Graz, Austria
Prof. Olivier L. de Weck Massachusetts Inst. of Technology, Boston, USA
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Outline 1. Introduction: What am I talking about? 2.
Agile SYSTEMS ENGINEERING
Different existing process models: where to find agility – and where not?
Agility is not for free
Approaches to extend agility
3. AGILE SYSTEMS engineering
Manifestations of Inflexibility: Examples
How to do better: Examples
Generalization
Theory
4. Summary Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Definitions
Agility = Property of a system that can be changed rapidly • Agile SYSTEMS ENGINEERING: agility installed in the systems engineering process
• AGILE SYSTEMS engineering: systems that can respond to changed requirements after initial fielding of the system
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Agile SYSTEMS ENGINEERING vs. AGILE SYSTEMS Engineering
Part I: Agile SYSTEMS ENGINEERING
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Descriptive Levels for the SE-Process Level
Description
Examples
1
Life Cycle Phase Concept Definition, Development, Production
2
Program Activity Mission Analysis, Prelim. Design, Detail Design
3
SE Process
4
Engineering Specialty Area
Requirements Analysis, Architecture Definition, System Design Software, Human Factors, Mechanical Design
Source: INCOSE, SE-Handbook, 2004 Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Action Model:
A.D. Hall – BWI/ETH Module 3:
PROBLEM
Module 4:
PROJECTPHASES
PROBLEM SOLVING CYCLES
Initialization Preliminary Study (D)
Variants of Solution Principles
Search for Solutions
Main Study (D)
Variants of Overall Concepts
Formulation of objectives Synthesis of solutions Analysis of solutions Evaluation
Selection
Detailed Studies (D)
Variants of Detailed Concepts Module 1:
TOP DOWN Module 2: DEVELOPMENT OF
VARIANTS
= selected variant, further worked on
Search for Objectives
Situational analysis
Decision
Establishment of s. (R)
D = Entwicklungsphase(n) R = Realisierungsphase
Introducing, handing over (R) Termination of p.
Source: Haberfellner,a.o., 2002
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Action Model acc. to A.D. Hall – BWI/ETH Module 3:
= adding flexibility PROBLEM
PROJECTPHASES
Module 4:
PROBLEM SOLVING CYCLES
Initialization Preliminary Study (D)
Variants of Solution Principles
Main Study (D)
Variants of Overall Concepts
Search for Solutions
Formulation of objectives Synthesis of solutions Analysis of solutions Evaluation
Detailed Studies (D)
Variants of Detailed Concepts Module 1:
TOP DOWN Module 2: DEVELOPMENT OF
VARIANTS
= selected variant, further worked on
Search for Objectives
Situational analysis
Establishment of s. (R)
Selection Decision
D = Development R = Realisation
Introducing, handing over (R) Termination of p.
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
Source: Haberfellner, a.o, 2002
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Waterfall Process and Iterative Prototyping
Waterfall Process
Iterative Prototyping Cycles Vers 1 Vers 2 Vers 3
Definition Analysis Design Detailed Requts Functions Definition
Programming Test Maintenance Acceptanc e
= bureaucracy: reducing flexibility
System Performance System FunctioConcept Reqs. nality Prototype Components Integration Design/ Develop
= iterations produce agility
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Manifesto for Agile Software Development
We are uncovering better ways of developing software by doing it and helping others do it. Through this work we have come to value:
• •
• •
Individuals and interactions over processes and tools Working software over comprehensive documentation Customer collaboration over contract negotiation Responding to change over following a plan = enhancing flexibility
Source: http://agilemanifesto.org/principles.html - April 25, 2005 Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Simultaneous (Concurrent) Engineering Linear Phase Concept Preliminary Study Product Development
Main Study
Preliminary Study
Detailed Studies
Main Study
Preliminary Study
Development of Production Facilities
Overlapping Phase Concept
Main Study
Detailed Studies
= increasing speed = killing flexibility
Procurement Installation
Detailed Studies
Production Preparation Prototype 0-Series
Procurement of Production Facilities
Procurement
Installation
. . .
Production Preparation Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Agility in the SE-process is not for free Time-consuming activities
Developing variants Decisions which variant is best (on different levels)
Reducing the range of variants in early phases
Simultaneous- or Concurrent-Engineering-concepts scale down the range of variants in early phases of a project. Unfortunately exactly this openness for variants would add flexibility
Simultaneous-Engineering = working on different levels of detail at the same time
The more intensely you are working on detailed concepts the lesser are the possibilities to change the overall concept An early design freeze may increase the speed But: try to modify or to change a frozen concept!
Conclusion: There is a basic conflict between an agile and a fast running SE-process. Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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The dynamics of the overall concept Stage Project Phase
1
2
3
4
5
Overall Concept
*
*
*
Detailed Concept 3
Detailed Concept 4
Solution Principle
Preliminary Study
Main Study
Detailed Concept 1
Detailed Studies
Establishment of S.
Detailed Concept 2
= External Influence
*
= Check, Modification, Adaption = Different Degree of Realization Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
Source: Haberfellner, a.o, 2002
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The dynamics of the overall concept = enhancing flexibility
= reducing flexibility
Stage Project Phase
1
2
3
4
5
Overall Concept
*
*
*
Detailed Concept 3
Detailed Concept 4
Solution Principle
Preliminary Study
Main Study
Detailed Concept 1
Detailed Studies
Establishment of S.
Detailed Concept 2
= External Influence
*
= Check, Modification, Adaption = Different Degree of Realization Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
Source: Haberfellner, a.o, 2002
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“Set based design” Decisions for Realization-Steps, not for Variants of the Overall Concept V1
1. Develop different feasible Variants
V2
V3
V4
V5
Vm = Variants of Overall Concepts Source: Shigley 1989 Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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“Set based design” Decisions for Realization-Steps, not for Variants of the Overall Concept 1
V1 1
2
V2
V3 2
1
2
V4
1
V5
2. Plan required actions for every Variant 3. Look different plans over for same actions
Vm = Variants of Overall Concepts
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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“Set based design” Decisions for Realization-Steps, not for Variants of the Overall Concept 1
V1 1
2
V2
1 RS1
RS2
1
2
V3
2 2
V4
1
V5
4. Decide for realization of those actions which are scheduled for many Variants (RS1 = Realization Step 1) etc.
Vm = Variants of Overall Concepts
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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“Set based design” Decisions for Realization-Steps, not for Variants of the Overall Concept V1
5. Eliminate Variants which are no more feasible V2
V3 RS1
RS2 RS3
V4
RSn = Realization-Step 1,2,.. V5
Vm = Variants of Overall Concepts
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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“Set based design” Decisions for Realization-Steps, not for Variants of the Overall Concept V1
Etc. etc.
V2
V3 RS1
RS2
RS4 RS3
V4
V5 RSn = Realization-Step 1,2,.. Vm = Variants of Overall Concepts
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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“Set based design” Decisions for Realization-Steps, not for Variants of the Overall Concept V1
Etc. etc.
V2
V3
RS1
RS2
RS4 RS3
V4
V5 RSn = Realization-Step 1,2,.. Vm = Variants of Overall Concepts = postponing decisions for concepts Enhancing agility Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Agile SYSTEMS ENGINEERING vs. AGILE SYSTEMS Engineering
Part II: AGILE SYSTEMS engineering
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Manifestations of Inflexibility
Macro Systems
Dominant Uncertainties
Inflexibility Manifestations
Space Systems Communications Satellites
# of subscribers, activity level, service type readiness, govt. funding
Vehicle Systems Commercial Aircraft Cars & Trucks
travel demand, demographic Aircraft cabin size, range, shifts, regulations, fuel emissions are locked in, prices, competition CAFE-standards violated shifting customers
Infrastructures Oil & Gas Exploitation Systems Commercial Buildings
fuel and gas prices, reserves contained in reservoirs, interest rates, Utilization patterns, land prices
System capacity is inadequate, cannot switch type of service
cannot take advantage of a previously unknown oil field High vacancy rates of commercial real estate
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Manifestations of Inflexibility in Systems: Examples
Low Earth Orbit Satellite Constellations:
Iridium and Globalstar financial desaster
Automotive Manufacturing Plant:
Daimler Chrysler’s PT Cruiser (good selling, Mexican site) could not be shifted additionally to Belvidere, Ill. (Neon, poor selling) because of several inches.
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Examples of Agile Systems
Optimal staging of satellite constellations for growth (de Weck 2004a)
Optimal modular facility design for divestment (Kalligeros 2004)
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Staged Cutback
Stadium for the European Soccer Championship 2007 in Klagenfurt/Austria
Need for a new stadium with capacity of 30.000 pers just for a couple of weeks After championship 15.000 pers
Solution (steel construction):
Built a stadium for 30.000
Cut-back to 15.000
Offer a 15.000 stadium for sale by using the disassembled parts Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Staged cutback
30.000 stadium
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Staged cutback
30.000 stadium
15.000 stadium (downsized)
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Staged cutback
30.000 stadium
15.000 stadium (downsized)
15.000 stadium (for sale)
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Example for “Operational flexibility”: Magna Automotive, Graz/Austria Designed for flexibility.
Different vehicles assembled in same production line in any order. Production and product data transmitted from USA and from D
In the assembly line until now have already been simultaneously assembled:
Chrysler Voyager + PT Cruiser Jeep Grand Cherokee + Mercedes M Class Chrysler Voyager + Jeep Grand Cherokee + Chrysler 300C
Bodyshell work is always done separately because of different work cycles. Body painting is possible in one paint shop for:
Chrysler Voyager, Jeep Grand Cherokee, Chrysler 300C, Mercedes G, Saab Cabrio and Mercedes E Class
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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3 different types of cars in one MAGNA-assembly line
Jeep Grand Cherokee Chrysler Voyager Jeep Grand Cherokee
Chrysler 300C
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Agile Systems – what is needed?
AGILE SYSTEMS are those that have flexibility embedded in them such that they can be changed in response to unfolding user demand after they are initially fielded. Requires three elements:
necessary flexible elements inside the system that allow it to be changed easily and quickly a set of sensors to monitor external attributes to alert decision makers when changes are warranted a decision mechanism by which the benefits and costs of system adaptation are compared and system state changes are triggered.
Practical view: Agility = Rather a mindset than a methodology ?
project team, party commissioning, steering committee, customer
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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When is agility in systems needed?
When the systems are
Expensive, involving significant upfront investment Long-lived, e.g. >10 years. User requirements may change significantly during the lifecycle. If significant switching costs exist, i.e. the expense might be too large for building an entirely new system each time the requirements change.
Designing flexibility into systems is not for free, but it may be
an insurance against downside risks, a way to take advantage of unexpected upside opportunities. Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Approaches to Agile System Design Capacity Adaptation (Staged Deployment)
Build a small initial system, grow in discrete stages, but only if needed
Example: factory design, satellite constellations
Modular and Platform-based Design
Design products/systems from a common core platform, customize variants with modules as needed Example: car platforms, modular buildings
Real Options
Create right but not obligation to modify system later
Examples: Extensible car garages
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Real Options Theory Real options analysis applies the financial principles of options (Black and Scholes 1973) to “real” or physical systems such as power plants, copper mines and so forth (de Neufville 2000). A project is treated as a “black box” and the conceptual and analytic effort focuses on trying to work the available data into forms suitable for the tools of financial analysis. A case in point is the Black-Scholes (1973) formula for pricing European call options:
V N d1 A N d 2 Xe rT
2 d1 ln r T / T X 2 d 2 d1 T
A = current value of the underlying asset X = exercise price T = Time of expiration R = Risk free interest rate = Volatility of the underlying asset N(d) = Cumulative value of normal distr. at d
V = value of call option
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Quantifying Uncertainty: GBM
Demand [Nusers]
5 x 10
Geometric Brownian Motion Model: Monte Carlo Simulation
1.6 1.4 1.2 1 0.8 0.6
0.4 0
5
Time [years]
10
15
GBM model of uncertain demand, DT = 1 month, Do = 50,000, m = 8% p.a., = 40% p.a. – 3 scenarios are shown Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Is it worthwhile? Value-at-Risk Curves
Flexibility valuation via relative comparison of E [NPV], (Hassan et al. 2005) Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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Summary
Distinguish between agile SYSTEMS ENGINEERING and the engineering of AGILE SYSTEMS
Agile SYSTEMS ENGINEERING: flexibility is embedded in the design process itself
AGILE SYSTEMS engineering: it is the system that exhibits the ability to be changed easily and quickly.
Question is whether the key uncertainties can be resolved before fielding of the system Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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The End
Field of Agile Systems Engineering is evolving Academic research and practice are in flux “Work in progress”
Reinhard Haberfellner, TU-Graz and Olivier de Weck, MIT
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