SysML v2 Planning & Requirements Working Group Meeting September 24, 2015 http://www.omgwiki.org/OMGSysML/doku.php?id=sysml-roadmap:sysml_assessment_and_roadmap_working_group Sandy Friedenthal Eldad Palachi

SysML Background SysML v1 adopted in 2006 Facilitated awareness and adoption of MBSE Much learned from applications of MBSE using SysML General agreement the time is right to begin work on the next generation of SysML (v2)

SysML v2 Work Group Status Sponsored by OMG SE DSIG Objective: Develop RFP for next generation SysML v2 Current focus on requirements and concepts INCOSE MBSE Themed article published August ‘15 on the capabilities, effectiveness measures, and driving requirements for a systems modeling environment (SME)

Meeting Objectives Concept Leads/Presentors Present draft concepts for the System Modeling Environment (SME) Participants Identify issues and missing concepts to provide to Follow-up Continue to refine and vet the concepts Establish the baseline SME Concept by the Reston meeting in March, 2016 Document in white paper Use to help derive requirements for SysML v2 RFP

Agenda 09:00 - 09:15 Introduction - Sandy Friedenthal 09:15 - 09:30 SE Use Cases - John Watson 09:30 - 10:00 Systems Engineering Concept Model (SECM) - Domain [R1] - John Watson 10:00 - 10:30 Systems Engineering Concept Model (SECM) - Kernel [R1] - Charles (Chas) Galey 10:30 - 10:45 Break 10:45 - 11:15 Modeling Formalism [R2] - Yves Bernard 11:15 - 11:45 Analysis Concept [R2] - Manas Bajaj 11:45 - 12:00 Reserve 12:00 - 13:00 Lunch 13:00 - 13:30 Model Visualization [R3] - Chris Schreiber 13:30 - 14:00 Model Construction [R4] - Ron Williamson 14:00 - 14:30 Model Interoperability [R5] and Standard API [R6] - Axel Reichwein 14:30 - 15:00 Break 15:00 - 15:30 Model Management [R7] - Laura Hart 15:30 - 16:00 Integration with PLM [R7] - Uwe Kaufmann/Michael Pfenning 16:00 - 16:45 ESA System Modeling Environments - Harald Eisenmann/Hans-Peter deKonning 16:45 - 17:15 Model Execution Approach and Issues [R2] - Robert Karban 17:15 - 17:30 Planning and Next Steps (e.g. Work Group Coor, Comm, Wiki's, etc.)

System modeling Environment (SME)

Configuration Management MBE To-Be State Source: NDIA MBE Final Report dated February 2011 Hardware Models Q SET CLR S R System Models Component Models ò G ( s ) U Analysis Models Operational Models Component Models System Models ò G ( s ) U Analysis Models Operational Models Configuration Management Program Management Test Manufacturing Hardware Systems Customer Logistics Software System Models Operational Models The MBE to-be state leverages MBE across the acquisition life cycle to enhance affordability, shorten delivery time, and reduce risk. In the to-be state, the models become an integral part of the technical baseline, and evolve throughout the programs life cycle. The current state is characterized by gaps between domain silos and lifecycle development phase hand-offs that are often the source of errors until later in the development process when they are more expensive to fix.  The future state of MBE seeks to reduce these errors though seamless integration of model data across domains and across the lifecycle by aligning shared model properties and assumptions. Different engineering disciplines concurrently operate on different facets of the system and/or product design, such that the impact of a change in one model can be readily assessed in another model. Engineering and programmatic knowledge is shared through a common technical baseline. The models developed by each discipline evolve in maturity throughout the life cycle, and are not thrown away and redeveloped as the program transitions from one phase of development to another. This includes the up-front mission analysis models, the system requirements and architecture models, the detailed hardware and software design models, and the detailed simulation models used to assess and verify all aspects of the system as it evolves. Early validation of requirements including those for manufacturing and support, and efficient development of a fully integrated technical baseline result in significant improvement to the development process. The collaborative foundation provides a means to share the information from the model registry across the extended enterprise of customers, teammates and suppliers. The foundation includes the modeling standards that enable information exchange, the model registry that enables ready access to the different models, and a trusted environment which enforces protection of intellectual property and secure access to sensitive and classified data. The collaborative environment also enables reuse from one program to another to enable sharing across a family of products and system of systems. The MBE to-be state includes a workforce that is skilled in the use of the matured modeling methods and tools, an infrastructure that supports this capability, and policies that enable it. MBE Enhances Affordability, Shortens Delivery and Reduces Risk Across the Acquisition Life Cycle Needs Current Capabilities Budget/Schedule

System Architectural Model MBSE Use Cases Customer Program Management Product Support ò G ( s ) U Analytical Models System Architectural Model Verification Models Analysis Spec Test Plan System Engineering Development Environment Performance, RMA, SWaP, Cost, etc. Manufacturing Mechanical & Electrical Models Q SET CLR S R Software Models To measure SysML effectiveness we need to understand the context of how it is used Source: John Watson © 2014 Lockheed Martin Corporation. All Rights Reserved.

System Modeling Environment (SME) Used by system modelers to perform MBSE in the broader context of Model-Based Engineering (MBE) Provide basic capabilities that include: model construction model visualization model analysis model management model exchange and integration support for MBSE collaboration and workflow Scope SysML modeling language and tools Reuse libraries (e.g., models, practices, ..) Integrations with other engineering models and tools

System Modeling Environment Basic Functionality in Support of MBSE

Effectiveness Measures Improve systems engineering productivity, quality, and management of complexity and risk Expressive: Ability to express the system concepts Precise: Representation is unambiguous and concise Presentation/communication: Ability to effectively communicate with diverse stakeholders Model construction: Ability to efficiently and intuitively construct models Interoperable: Ability to exchange and transform data with other models and structured data Manageable: Ability to efficiently manage change to models Usable: Ability for stakeholders to efficiently and intuitively create, maintain, and use the model Adaptable/Customizable: Ability to extend models to support domain specific concepts and terminology

Driving Requirements Driving requirements for the next-generation system modeling language and tools have been identified as highlighted below. Express the core systems engineering concepts. Include precise semantics that avoid ambiguity and enable a concise representation of the concepts. impact assessment of a requirement or design change integrate with equation solvers, execution environments, & capture quantitative data. Provide flexible and rich visualization and reporting capabilities to support a broad range of model users. Enable much more intuitive and efficient model construction. Integrate across discipline-specific engineering tools, including hardware and software design, analysis and simulation, and verification.

Driving Requirements (cont.) Provide a standard application program interface (API) to provide dynamic access to the model. Capable of being managed in a heterogeneous and distributed modeling environment. Enable efficient and intuitive use by a broad range of users with diverse skills. Must be highly adaptable and customizable to multiple application domains. Support the migration of existing models with minimum information loss. Enable evolution of the above capabilities that take advantage of on-going advances in technologies, concepts, methods, and theories.

Systems Modeling Environment Conceptual Architecture 10/06/14

System Modeling Environment

Next Steps Develop concepts for each driving requirement – Dec 2016 Document SME concept in white paper – March 2016 Vet among the community Derive requirements and issue SysML v2 RFP – March 2017

Backup

Systems Modeling Environment Concept Development Approach For each capability area Assess current state and limitations Develop concept Determine near term, mid term, and long term improvements Leverage current activities, research, and initiatives Develop a follow-up plan to prototype and validate concept Integrate each capability concept into an overall system modeling environment concept and roadmap that supports MBSE in the context of Virtual Engineering

Systems Modeling Environment Source: A Practical Guide to SysML, 3rd Edition Figure 18.5. High level information exchange between the system modeling tool and other tools. Copyright © 2014 by Elsevier Inc All Rights Reserved.