Model-Based Systems Engineering
Issued by
University of Connecticut
Earners of the Model Based Systems Engineering Badge have developed skills in the discrete modeling and simulation of cyberphysical systems using a systems engineering approach and can construct high quality systems models using the SysML modeling language and an MBSE tool. They can analyze sensitivity of cyberphysical designs for variability and uncertainty in the context environment and perform verification and validation of requirements, design, systems, and systems models.
- Type Validation
- Level Intermediate
- Time Weeks
- Cost Paid
Skills
- Complex System Modeling
- Cyber-Physical Systems
- Manage Design Change
- Meta System Modeling
- Model-based Systems Engineering
- Model-Based Systems Engineering Management
- Model-Based Systems Engineering Modeling
- SysML
- System Design
- Systems Analysis
- Systems Architecting
- Systems Engineering
- Systems Modeling
- Systems Thinking
- Uncertainty Quantification
- Validation
- Verification
Earning Criteria
-
Badge earners complete SE 5001 Model Based Systems Engineering course at the University of Connecticut, which is a hybrid-online graduate course that can be taken from anywhere in the world. Earners can take this graduate course as a matriculated UConn graduate student or as a non-degree graduate student, which does not require admission to the UConn graduate school. Badge holders complete a course-long project and must earn a B- or better on this project to earn the badge.
-
Badge earners can perform MBSE management practices for a real-world problem, can describe modeling roles and responsibilities, can describe knowledge, skills, and abilities for MBSE practitioners, can develop a MBSE use strategy for their organization and can conduct model-based verification and validation. See Standard [4] INCOSE Model-Based Enterprise Capabilities Matrix below.
-
Badge earners can perform MBSE by system modeling using a systems modeling language, can describe different types of systems modeling languages and methods, can develop a systems engineering-driven model plan, can define model metrics, can develop a high-quality systems model based upon a defined purpose, can model stakeholder needs, and can develop a high-quality systems model using SysML or other standard language. See Standard [4] INCOSE Model-Based Enterprise Capabilities Matrix below.
-
Badge earners can analyze systems by simulation, can verify and validate models, can define and develop model libraries, can conduct model-based reviews, can integrate models, can quantify model process quality can use existing models for analysis based upon different types of needs. See Standard [4] INCOSE Model-Based Enterprise Capabilities Matrix below.
-
Badge earners can explain why models and simulations have a limit of valid use and explain the risks of fusing models and simulations outside those limits, can explain why models are developed for a specific purpose, can use modeling and simulation tools and techniques to represent a system or system element, can interpret and use outcomes of modeling and analysis, with guidance, and can contribute to the model development and interpretation activities. See Standard [3] INCOSE ISECF below.
-
Badge earners can design large-scale meta systems and predict behavior and performance with systems models during early phase design, can perform modeling and analysis to design and predict operating characteristics for a complex system, can perform modeling and analysis to design and predict when changing meta system conditions cause system failures, See Standard [2] DOE-SIAM below.
-
Badge earners can perform modeling and analysis of a stochastic system and simulate it to understand performance based upon performance measures, can decompose complex systems into canonical subsystems to design and predict system behavior and elucidating the coupling between components, can optimize a system to meet stakeholder needs and best engineering practice standards, and can perform modeling and analysis to quantify cost, schedule, and technical risk. See Standard [2] DOE-SIAM below.
-
Badge earners can manage design change through system modeling, can perform modeling and analysis to design and predict the effects of introducing a new technology into a current complex system, can modify a model of a complex system to introduce to new data types and formats, can conduct sensitivity analysis for a complex system using a model during early phase design, and can define and quantify uncertainty in systems flows and processes for a systems model. See Standard [2] DOE-SIAM below.
-
Badge earners can apply knowledge of how cyberphysical system methods integrate at the large, meta system level, can design and develop cyberphysical system architecture, can develop and update formal specifications for cyberphysical designs and systems, can develop and update verification and validation methods for cyberphysical designs and systems, can apply Systems Engineering methods and principles to the design and operation of a cyberphysical system. See Standard [1] NAE-CPS below.
-
Badge holders complete a course-long project consisting of a proposal, midterm and final reports, and systems model artifact. The project consists of creating and developing a systems model that represents the design of a real system using an MBSE tool and a systems modeling language. The model must be defined and simulated to solve a particular problem. The model is simulated to determine if requirements and key performance parameters are met.
Standards
A 21st Century Cyber-Physical Systems Education. Committee on 21st Century Cyber-Physical Systems Education; Computer Science and Telecommunications Board; Division on Engineering and Physical Sciences; National Academies of Sciences, Engineering, and Medicine. ISBN 978-0-309-45163-5 | DOI: 10.17226/23686.
SIAM APPLIED MATHEMATICS AT THE U.S. DEPARTMENT OF ENERGY: Past, Present and a View to the Future. A Report by an Independent Panel from the Applied Mathematics Research Community May 2008.
INCOSE Model-Based Enterprise Capabilities Matrix 2.0b Draft June 2019 r4. Joe Hale, NASA
INCOSE Systems Engineering Competency Framework. July 2018. INCOSE Technical Product Reference: INCOSE-TP-2018-002-01.0