INCOSE (MBSE) Model Based System Engineering Cost/Logistics Modeling

1. INCOSE (MBSE)Model Based System Engineering Cost/Logistics Modeling Chris Adams, PhD Raytheon c-adams5@raytheon.com Jan 21-22, 2012 INCOSE IW12 MBSE Workshop MBSE Wiki page: http://www.omgwiki.org/mbse MBSE SoS/Enterprise Modeling Wiki page: http://www.omgwiki.org/MBSE/doku.php?id=mbse:enterprise

2. Outline • Introduction • Modeling Approach • Examples of the Modeling Approach • Supporting the Integrated Modeling Vision • Cost and Logistics Modeling Integration Challenges • How can MBSE Help to Address the Challenges? • Questions…

3. Introduction • There is a current emphasis of comprehensive assessment of cost for development, procurement and sustainment. • This requires the balancing of four separate aspects of total system “value”. • Performance (Coverage) • Operational Availability (Ao)/Logistics • Reliability (MTBF) • Life Cycle Cost (LCC) • Objectives set in the value equation include • Maximize Performance (Coverage) • Maximize Operational Availability • Optimize the logistics support strategy • Minimize Life Cycle Cost • Maximize Reliability (MTBF)

4. Modeling Approach / Analysis Flow

5. Cost Modeling Uses CAIV Cost As an Independent Variable (CAIV) balances, cost, schedule, performance, and risk Treats cost as a requirement Early application critical Answers the question: How much performance can I get for my money? Trades performance or effectiveness for reductions in life cycle cost

6. Reliability vs. Cost Modeling Process Input Output Reliability Investment Model MTBF improvement versus cost relationships given the implementation of different reliability best practices • # of Redundant Systems • Investment Options • Failure Modes Effects Analysis • Reliability Growth Testing • Highly Accelerated Life Testing • Statistical Reliability M&S • Thermal and Fatigue Analysis • Mean Time Between Failures (MTBF) • Life Cycle Cost trade off analysis is driven by reliability • The tasks performed during development to ensure a reliable design strongly influence life cycle cost 1/2/2020

7. Life Cycle Cost Model Reliability Investment $s MTBF & # of Redundant Assemblies System, Product & Component Unit Costs 00

8. Cost Modeling Approach • Parametric Cost Analysis? • “ Parametric Cost Analysis employs equations that describe relationships between cost, schedule, and measurable attributes of systems, hardware, and software. The equations describe how a products design, technology, and programmatic characteristics affect its cost and schedule. “ • * from the International Society of Parametric Analysts (ISPA) Website • How can we expand parametric cost modeling by developing cost estimating relationships between functions and performance parameters?

9. Cost Modeling & Analysis • Commercial Parametric Cost Models • Price True Planning & Price Estimating Suite • PRICE H, the Hardware Estimating Model • PRICE HL, the Hardware Life Cycle Estimating Model • PRICE M, the Electronic Module & Microcircuit Estimating Model • PRICE S/SL, the Software Development & Support Cost Estimating Model • SEER • SEER H, Parametric Hardware Life Cycle Cost Model • SEER SEM, Parametric Software Cost Model • SEER IT, Information Technology Cost Model • SEER DFM, Manufacturing Parametric Cost Model

10. PRICE H Cost Model Input Parameters Mechanical Design • Relationships exist between Mechanical & Electrical System Design Parameters used in CAD systems • Manufacturing process simulations can be used to update parametric cost models Electrical Design

11. Cost Modeling as Part of Systems Engineering Vision

12. Logistics Modeling & Analysis • Logistic support analysis • Reliability-centered maintenance (RCM) • Failure modes effects (criticality) analysis (FMECA) • Reliability and maintainability (R&M) studies • Safety analysis • Life cycle cost (LCC) analysis • Maintenance task analysis (MTA) • Level of repair analysis (LORA) • Logistics Support Analysis Record (LSAR • Existing LOGSA Tools are the current focus of DoD Logistics Activities

13. Logistics Modeling Parameters

14. Cost Model Integration Challenges • Identifying cost estimation relationships between performance parameters • Generally product cost is based on type of material and manufacturing processes • Increased system performance tied to increases in system size, processing capacity or logic built into devices • How do we generalize these relationships into utility curves that relate system performance and function to cost? • Identifying tip over points for integration of functions into new designs • What functions are easily integratable at low cost • How many functions can you integrate before development results into a complete system redesign

15. Logistics Model Integration Challenges • Modeling Hierarchical System, Product, Component and Piece Part Structures • Spares Stocklists use hierarchical models that must be common between cost, reliability, weight, power and size models • Spares Optimization models using hierarchical structures are typically complex • Integration at this level of complexity can be dificult • Generally models that include spares optimization algorithms have proprietary interfaces • Integration of Concept of Operations Modeling with logistics support structure • Modeling of where spares can be kept on a vehicle (tires, filters, batteries…) or stored during operations is essential to how stocklists are identified

16. How Can MBSE Help Address the Challenges? • Assign performance parameters to systems and subsystems • Create cost/performance curves based on existing designs that satisfy scenarios, capabilities, & functions • Create Matrices • Map subsystem costs to capabilities and functionality • Map Performance Levels to specific subsystem groups used to perform one or more system functions • Include ability to select specific capabilities at a given cost or performance level • Develop parametric cost modules for each function & performance level • Potentially create classification algorithm that identifies best system to use for a given set of capabilities, cost and performance levels CONOPS/Scenario Matrix Capability Matrix Performance Matrix Systems Function/ Capability Performance Levels Capabilities Subsystem Subsystem Example Exploring the Tradespace

17. Conclusions • An integration framework should be developed that maps system performance and functionality to cost parameters • Cost is is modeled using design implementations that satisify a given function • Many design implementations may satisfy one function • These design implementations will have different performance levels • Performance versus cost relationships will provide better search of the trade space • A parametric Modeling approach to map cost to performance parameters should be considered • Logistics Modeling involves complex system, product and component interactions • Architecure Modeling, System CONOPS and usage scenarios must be closely coupled with system logistics support concepts • Ensure proper infrastructure is in place for system support • Ensure effective partitioning of system components to reduce logistic footprint and life cycle costs