information flow and decision-making in advanced · pdf fileinformation flow and...
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Information Flowand Decision-Making
in Advanced Vehicle Development
Presented by:Presented by:Joseph A. Donndelinger
General Motors Research & Development Center
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EngineerEngineerManufactureManufacture
SOP
Start of
Production
VDR
Verified Data
Release
VehicleProgramInitiation
DSI
Document of Strategic
Intent
Portfolio Plan Development
Global VehicleDevelopment Process
Managed by the Vehicle Line Executives
AdvancedVehicle
DevelopmentProcess
DSIPrep
ProgramFraming
PortfolioPlanning
VPI
EngineerEngineerManufactureManufacture
SOP
Start of
Production
VDR
Verified Data
Release
VehicleProgramInitiation
DSIDSIDSI
Document of Strategic
Intent
Portfolio Plan Development
Global VehicleDevelopment Process
Managed by the Vehicle Line Executives
AdvancedVehicle
DevelopmentProcess
DSIPrep
ProgramFraming
PortfolioPlanning
DSIPrep
ProgramFraming
PortfolioPlanning
VPI
Focus on AVDP
GM’s Vehicle Development ProcessGM’s Vehicle Development Process
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Motivating QuestionsMotivating Questions
1. To what extent can iteration be removed from the design process?
2. What are the triggers for generation, storage, and distribution of information in product development?
3. How can uncertainty be characterized and managed throughout the execution of the product development process?
4. What is the role of the engineer in decision-making?
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ApproachApproach
• Apply leading-edge methods to model GM’s Advanced Vehicle Development Process (AVDP)• Design Structure Matrix (DSM)• Decision Analysis (DA)
• Analyze models to gain insight into AVDP execution• Insights from individual models• Composite insights from both models
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ContributorsContributors
DSM ModelGM R&D Center• Alexandra Elnick• Datta Kulkarni• Joe Donndelinger
MIT CIPD• Ali Yassine• Alberto Cividanes• Steven Eppinger• Daniel Whitney• William Finch
DA ModelGM R&D Center• John Cafeo• Robert Lust• Joe Donndelinger
Oakland University• Zissimos Mourelatos
Stanford University• Ali Abbas• Apiruk Detwarasiti• Christopher Han• John Feland• Ronald Howard• Ross Shachter
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What is a Design Structure Matrix?
• A Design Structure Matrix (DSM) is a compact, matrix representation of a system/project.
• The matrix contains a list of all constituent subsystems/activities and the corresponding information exchange and dependency patterns.
BA
XAB
XXXXX
DE
C
EDC
X
F
FX
X
The Design Structure Matrix (DSM)The Design Structure Matrix (DSM)
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Three possible sequences for two tasks:
A BA
B
A
B
Independent(Parallel)
Dependent(Series)
Interdependent(Coupled)
BA
XAB
BAAB
BAX
XAB
In DSM notation:
Information Flows & Task SequencingInformation Flows & Task Sequencing
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BA
XAB
XXXXX
DE
C
EDC
X
F
FX
X
Dependent(Series)
Independent(Parallel)
Interdependent(Coupled)
• Marks along the rows indicate inputs(i.e. Task E receives inputs from tasks A, B, D and F)
• Marks along the columns indicate outputs(i.e. Task E provides an output to task F)
Reading the DSMReading the DSM
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• Product Planning• Marketing• Finance• Design Studio• Program Management
Team• Quality
• Vehicle Integration Engineering
• Manufacturing Engineering
• Packaging Engineering• Systems Engineering• Body Engineering• Chassis Engineering• Powertrain Engineering
Key Functions Interviewed:Key Functions Interviewed:
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Expert Opinion Phase
Quick Study Phase
Integrated Vehicle Concept Model and O.D. Deliverables
Phase
39 tasks
52 tasks
29 tasks
Identified 120 tasks from 19 different functions
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Track Total Vehicle Issues (TVIE)
Update Financial Assessment and Finalize Business Case (Finance)
Develop Mainstream Integrated Concept Vehicle
Model (VCE)
Assess Risks in Performance Requirements (Performance Development)
Review Quick Study Deliverables (Review Board)
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Track Total Vehicle Issues (TVIE)
Input from Systems Engineering to Different
Compartments
Input from Performance Development to Different
Compartments
Input from Manufacturing to Different Compartments
Feedback Provided by
Different Engineering
Compartments
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PlanningAssistant Planning Director
Vehicle Program ManagementDirector
Manufacturing EngineeringDirector
Option Development Review Board
Option Development Team Leadership
GPDC Planner Brand/MarketingVehicle Project Management
ManagerTotal Vehicle Integration Total Manufacturing Integration
Option Development
Team
Compartment Integration:GPDC Finance
GPDC Quality
Systems Engineering
Vehicle Concept Engineering
Performance Development
Die Manufacturing
Design Studio
Body
Chassis IP/Cockpit Front
Passenger/Rear
Team StructureTeam Structure
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Option Planning Team
Typical SectionTeam
PerformanceIntegration
Team
Compartment Integration Teams
BodyFront & Chassis
IP/Cockpit Passenger/Rear
Supplier Design Reviews
DesignCenter
Interface
VAPIR(Vehicle and Process Integration Review)
Team MeetingsTeam Meetings
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Iteration in design process• Extensive in 2nd phase of AVDP• Contributing factors:
• Investigations of alternatives to mainstream design• Coordination of work across disciplines• Tremendous complexity in subsystem interactions
Generation and distribution of information• Highly structured - Largely driven by templates• Centrally stored• Often reviewed in “town hall” meetings• Ad-hoc networks arise as needed
Insights from DSM Model (1)Insights from DSM Model (1)
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Management of uncertainty• Allocate all available resources to reducing uncertainty• More model detail à Less perceived uncertainty
Roles in decision-making• Engineers:
• Develop alternatives• Provide information
• Managers:• Make decisions
Insights from DSM Model (2)Insights from DSM Model (2)
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The Decision Analysis CycleThe Decision Analysis Cycle
Deterministic Phase
Probabilistic Phase
Informational Phase
Decision
Information Gathering
Prior Information
New Information Gather New Information
ActDeterministic Phase
Probabilistic Phase
Informational Phase
Decision
Information Gathering
Prior Information
New Information Gather New Information
Act
Matheson, J.E. and Howard, R.A., An Introduction to Decision Analysis (1968), from Readings on The Principles and Applications of Decision Analysis, Strategic Decisions Group , 1989.
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D - Decision NodeMultiple decisions non-deterministically affect the value
U - Uncertainty NodeMultiple non-deterministic relationships represent the
knowledge of how decisions affect the value
$ - Value NodeValue captures the preference under uncertainty among
various prospects
Decision DiagramsDecision Diagrams
D U $D U $
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The Elements of Decision QualityThe Elements of Decision Quality(courtesy of Strategic Decisions Group)(courtesy of Strategic Decisions Group)
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Product
Decision Diagram for Design Alternatives (1)Decision Diagram for Design Alternatives (1)
Manufacturing Process
Product Design
Parameters
Mfg Process Parameters
Independent Variables
This is how new engineers see the world…
Deterministic Quantities
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Cost to Produce
Product
Manufacturing Process
Product Design
Parameters
Mfg Process Parameters Decision(s)
Uncertainties
This is how experienced engineers see the world…
Decision Diagram for Design Alternatives (2)Decision Diagram for Design Alternatives (2)
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Profit
Customer Perceived Performance
Attributes (Styling, noise level, etc…)
Cost to Produce
Product
Attribute
Revenue
Manufacturing Process
Economy
Customer Prior Experience
Product Design
Parameters
Market Performance
Mfg Process Parameters
Competitors Products
Decision(s)
Uncertainties
Outcome
This is how decision makers see the world…
Decision Diagram for Design Alternatives (3)Decision Diagram for Design Alternatives (3)
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Target Market Segment
Degreeof Re-Use
NPV
Key Purchase Drivers | Market
Segment
Sales Volume
Material Cost
Average Price
Competitor Pricing
Competitor Offerings
Investment Cost
Actual SOP
Market Research
Architecture (new/existing)
SOP Target Date
Plant Candidate(s)
Styling Requirements
Performance Requirements
Financial Targets
Clinic Results
Vehicle Dev. Duration
“Product Definition”
Plant Selection
Production Capacity
Pricing Strategy
Design Revisions
Actual Product
Clinic Preparation
Executive Input
Union Demands
Economic Environment
Mfg. TP
Safety/ Quality Issues
Recall Likelihood
Law Suits
A Decision Diagram for the AVDPA Decision Diagram for the AVDP
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Iteration in design process• Occurs naturally in the Decision Analysis Cycle• Driven by information needs of decision-makers
Generation and distribution of information• Analytical results supplement the decision-maker’s
State of Information• Analyses are performed when the results are material
to decisions at hand
Insights from DA Model (1)Insights from DA Model (1)
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Management of uncertainty• Decision-making under uncertainty and risk is
INEVITABLE• Epistemic uncertainty can be reduced• Aleatory uncertainty CANNOT be reduced
• Uncertainty must be assessed by the decision-maker
Roles in decision-making• Engineers develop alternatives and provide information• Managers assess uncertainties and make decisions
Insights from DA Model (2)Insights from DA Model (2)
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An optimal determination of design parameters based upon pre-specified objective functions
• Current Perspective• Viewed as dimensional adjustments on the
selected design• Formulate an optimization problem where the
objective is to minimize the deviation from the specifications
• Decision Analytic Perspective• Formulate an optimization problem where the
single objective is to maximize expected utility instead of deterministic value functions
Engineering Design: Parametric DesignEngineering Design: Parametric Design
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Selection of a design from a fixed set of alternatives based upon some stated criteria
• Current Perspective• No creative process involved• Pick the design from the set that matches the
requirements
• Decision Analytic Perspective• Pick the optimal design from the set based on the
maximum expected utility criterion
Engineering Design: Design SelectionEngineering Design: Design Selection
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A creative configuration of entities to construct a system based upon some criteria
• Current Perspective• Ongoing process where final alternatives are
never completely specified until the very end• End requirements are cascaded down as
specifications in order to allow effective translation & guidance from abstract to detailed designs
• Decision Analytic Perspective• This is the focus of this research
Engineering Design: Design SynthesisEngineering Design: Design Synthesis
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Problem Characteristics• Very large alternative space• Extremely complicated
relationships• Organizational boundaries• Time constraints• Modeling complexity
Solution Characteristics• Rational decision-making
under uncertainty procedure• Manageable modeling in
terms of construction and implementation that recognizes the organizational and resource restrictions
Decision Diagram for Design SynthesisDecision Diagram for Design Synthesis
U
U
U
UU
U U
U
D D
D D
D D
D
D
D
$
U
U
U
UU
U U
U
D D
D D
D D
D
D
D
$
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w Design Decisionsn System-level decisions
l Concept, architecture, interface among subsystems, etcn Subsystem-level decisions
l Interface among components, etcn Component-level decisions
l Components and parts, etcn Fine-tuning decisions
l Parametric design decisions
Time
ConceptConcept
Number of Design Decisions
DetailedDetailed
Decisions in Design SynthesisDecisions in Design Synthesis
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Uncertainties in Design SynthesisUncertainties in Design Synthesis
w Design Uncertaintiesn How current decisions affect the value
l Evaluation of partially specified alternativesn How current decisions affect subsequent decisions
l Evaluation of restrictions imposed on later decisionsn How further refined designs will look like
l Anticipation of various more-detailed designsn How those detailed designs will affect the value
l Given detailed design, value is not known deterministically
Time
Amount of Design Uncertainties
ConceptConcept DetailedDetailed
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Final ThoughtsFinal Thoughts
On iteration in the design processPlan for “good iteration” (allow for exploration of design space and reduction of uncertainty)Reduce “bad iteration” (caused by lack of discipline, poor team or process structure, or miscommunication)
On generating and distributing informationThe primary challenge is focusing resources on the subset of information that is relevant and valuable
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Final ThoughtsFinal Thoughts
On characterizing and managing uncertaintyAs beauty is in the eye of the beholder,so is uncertainty in the eye of the decision-maker
On roles in decision-makingEngineers develop alternatives and provide informationManagers assess uncertainties and make decisionsComputers execute instructions