Information Flow and Decision-Making in Advanced Vehicle Development Presented by: Presented by: Joseph A. Donndelinger General Motors Research & Development Center
GM’s Vehicle Development Process GM’s Vehicle Development Process Focus on AVDP Advanced Advanced Global Vehicle Global Vehicle Portfolio Plan Portfolio Plan Vehicle Vehicle Development Process Development Process Development Development Development Development Vehicle Vehicle Verified Verified Start Start Process Process Program Program Data Data of of Portfolio Portfolio Portfolio Program Program Program DSI DSI DSI Initiation Initiation Release Release Production Production Planning Planning Planning Framing Framing Framing Prep Prep Prep VDR VDR SOP SOP VPI VPI DSI DSI DSI DSI Engineer Engineer Engineer Engineer Document of Document of Strategic Strategic Manufacture Manufacture Manufacture Manufacture Intent Intent Managed by the Vehicle Line Executives Managed by the Vehicle Line Executives
Motivating Questions Motivating 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?
Approach Approach • 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
Contributors Contributors DSM Model DA Model GM R&D Center GM R&D Center • Alexandra Elnick • John Cafeo • Datta Kulkarni • Robert Lust • Joe Donndelinger • Joe Donndelinger MIT CIPD Oakland University • Ali Yassine • Zissimos Mourelatos • Alberto Cividanes Stanford University • Steven Eppinger • Ali Abbas • Daniel Whitney • Apiruk Detwarasiti • William Finch • Christopher Han • John Feland • Ronald Howard • Ross Shachter
The Design Structure Matrix (DSM) The Design Structure Matrix (DSM) What is a Design Structure Matrix? A B C D E F • A Design Structure Matrix (DSM) is a A compact, matrix representation of a B X system/project. C X X D X • The matrix contains a list of all constituent subsystems/activities and E X X X X the corresponding information F X exchange and dependency patterns.
Information Flows & Task Sequencing Information Flows & Task Sequencing Three possible sequences for two tasks: A A A B B B Dependent Independent Interdependent (Series) (Parallel) (Coupled) In DSM notation: A B A B A B A A A X B X B B X
Reading the DSM Reading the DSM A B C D E F Dependent A (Series) B X Independent C X X (Parallel) D X Interdependent E X X X X (Coupled) F X • 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)
Key Functions Interviewed: Key Functions Interviewed: • Product Planning • Vehicle Integration Engineering • Marketing • Manufacturing • Finance Engineering • Design Studio • Packaging Engineering • Program Management • Systems Engineering Team • Body Engineering • Quality • Chassis Engineering • Powertrain Engineering
Expert Opinion Phase 39 tasks Identified 120 tasks from 19 different functions Quick Study Phase 52 tasks Integrated Vehicle Concept Model and O.D. Deliverables 29 tasks Phase
Track Total Vehicle Issues (TVIE) Update Financial Assessment and Finalize Business Case (Finance) Develop Mainstream Integrated Concept Vehicle Model (VCE) Review Quick Study Deliverables (Review Board) Assess Risks in Performance Requirements (Performance Development)
Feedback Track Total Vehicle Provided by Issues (TVIE) Different Engineering Compartments Input from Systems Engineering to Different Compartments Input from Performance Input from Manufacturing to Development to Different Different Compartments Compartments
Team Structure Team Structure Option Development Review Board Planning Vehicle Program Management Manufacturing Engineering Assistant Planning Director Director Director Option Development Team Leadership Vehicle Project Management GPDC Planner Total Vehicle Integration Total Manufacturing Integration Brand/Marketing Manager Design Studio Systems Engineering Option Die Manufacturing Development Team Vehicle Concept Engineering GPDC Quality GPDC Finance Performance Development Compartment Integration: Body Passenger/Rear Chassis IP/Cockpit Front
Team Meetings Team Meetings Option Planning Team Performance Integration Team Design VAPIR Center (Vehicle and Process Typical Interface Integration Review) Section Team Compartment Integration Teams Front & Body IP/Cockpit Passenger/ Chassis Rear Supplier Design Reviews
Insights from DSM Model (1) Insights from DSM Model (1) Iteration in design process Extensive in 2 nd 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 (2) Insights from DSM Model (2) Management of uncertainty • Allocate all available resources to reducing uncertainty • More model detail � Less perceived uncertainty Roles in decision-making • Engineers: • Develop alternatives • Provide information • Managers: • Make decisions
The Decision Analysis Cycle The Decision Analysis Cycle Prior Information Prior Information Act Act Deterministic Deterministic Probabilistic Probabilistic Informational Informational Decision Decision Phase Phase Phase Phase Phase Phase Information Information Gathering Gathering New Information New Information Gather New Information Gather New Information 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.
Decision Diagrams Decision Diagrams D D U U $ $ D - Decision Node Multiple decisions non-deterministically affect the value U - Uncertainty Node Multiple non-deterministic relationships represent the knowledge of how decisions affect the value $ - Value Node Value captures the preference under uncertainty among various prospects
The Elements of Decision Quality The Elements of Decision Quality (courtesy of Strategic Decisions Group) (courtesy of Strategic Decisions Group)
Decision Diagram for Design Alternatives (1) Decision Diagram for Design Alternatives (1) Mfg Process Independent Parameters Variables Product Manufacturing Deterministic Design Process Quantities Parameters Product This is how new engineers see the world…
Decision Diagram for Design Alternatives (2) Decision Diagram for Design Alternatives (2) Mfg Process Decision(s) Parameters Uncertainties Product Manufacturing Design Process Parameters Cost to Product Produce This is how experienced engineers see the world…
Decision Diagram for Design Alternatives (3) Decision Diagram for Design Alternatives (3) Mfg Process Decision(s) Parameters Uncertainties Product Manufacturing Design Process Parameters Outcome Cost to Product Produce Customer Perceived Performance Attributes (Styling, Profit noise level, etc…) Attribute Revenue Economy Market Performance This is how Competitors decision makers Products Customer Prior see the world… Experience
A Decision Diagram for the AVDP A Decision Diagram for the AVDP “Product Definition” Degree of Re-Use Architecture Material (new/existing) Recall Cost Safety/ Likelihood Quality Issues Performance Requirements Law Investment Suits Cost Styling Actual Requirements Product Target Market Segment Financial Vehicle Dev. NPV Design Targets Duration Revisions Mfg. TP Plant Plant Production Candidate(s) Selection Capacity Sales Union Volume Demands SOP Target Actual Date SOP Executive Average Pricing Input Price Strategy Competitor Pricing Clinic Clinic Preparation Results Competitor Offerings Key Purchase Market Economic Drivers | Market Research Segment Environment
Insights from DA Model (1) Insights from DA Model (1) 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
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