Systems Engineering SMART MODEL BASED SYSTEMS ENGINEERING Author: M.E. Alejandro Ayala, University of Detroit Mercy Coauthor: Ph.D. Jonathan Weaver, University of Detroit Mercy Coauthor: M.E. Ruben Ochoa, Hochschule Esslingen Coauthor: B.S.E. Jenifer Fuentes, Unitec University 8/14/2018
Systems Content Engineering • Background • Model Based Systems Engineering (MBSE) • Smart Model Based Systems Engineering (SMBSE) • Reusability • Automation • Dynamic Simulation • Optimization • Further Development • Conclusions • Q&A “Do complex systems meet stakeholder needs and deliver value? Do they integrate easily, evolve flexibly, and operate simply and reliable? Well architected systems do!” Bruce Cameron MIT 8/14/2018 2
Systems Background Increasing Complexity Engineering The increasing complexity of disruptive technologies and resulting ultra large 1 and complex systems engineering, requires the development of fully integrated modeling and iterative analysis platforms. Disruptive Technologies Quantum Computing Genome Editing Industry 4.0 City Brain 1 Sillitto, Hillary. Design Principles for Ultra Large Scale Systems, 2010 8/14/2018 3
Systems Model Based Systems Engineering Engineering • MBSE is the formalized application of systems engineering modeling to manage requirements traceability, identify constraints and interfaces, define verification and validation activities, and predict emergence results. 2 • A wide range of current Systems Engineering models were analyzed to identify opportunities for adding functional capabilities to current Model Based Systems Engineering methodologies. 2 Cameron, Bruce “Systems Architecture”, MIT 8/14/2018 4
Systems Model Based Systems Engineering Engineering • MBSE has been a dominant methodology for defining and modeling complex systems; however, it has not yet been paired with cutting-edge digital engineering transformation. Complexity Systems Growing gap between Engineering complex systems Complexity engineering and MBSE functionality MBSE Time 8/14/2018 5
Systems Model Based Systems Engineering Engineering • MBSE is constrained to represent a whole system, but lacks other capabilities, such as dynamic simulation and optimization, as well as integration of the model with software and hardware. 8/14/2018 6
Systems Smart MBSE Engineering • This research provides the key elements for developing a Smart MBSE (SMBSE) modeling approach that integrates Systems Engineering (SE) with the full suite of other development tools utilized to create today’s complex products and services. 8/14/2018 7
Systems Smart MBSE Engineering • SMBSE will provide the required functionality in accordance with cyber-physical systems engineering requirements in terms of speed, robustness and anticipated results. Source: https://www3.nd.edu/~dwang5/courses/spring17/ 8/14/2018 8
Systems Smart MBSE Engineering • This research was oriented towards exploring the opportunity to develop a SMBSE methodology by integrating reusability, automation, simulation and optimization to the conventional MBSE. • SMBSE is a compelling requirement for the increasing systems engineering complexity, while taking full advantage of cyber tools. 8/14/2018 9
Systems Smart MBSE Engineering • The main benefit of SMBSE is to close the gap between the growing business needs of complex systems engineering and conventional MBSE. Complexity Systems Opportunity to close the Engineering gap through SMBSE Complexity methodology MBSE Time 8/14/2018 10
Systems Smart MBSE Engineering • An additional benefit is the design integration between software and hardware components with multiple features, often with conflicting targets. SMBSE functionalities to validate hardware, software and targets before prototype build 8/14/2018 11
Systems Smart MBSE Engineering • The above sequence is the recommended path for developing SMBSE methodology, leveraging the reusability of proven prior models in order to focus on the unique elements of the new product or services. 8/14/2018 12
Systems Reusability Engineering • The models developed using a SMBSE approach are able to reuse the requirements, signals and interfaces from the carryover subsystems, and apply them to the new systems. 8/14/2018 13
Systems Reusability Engineering • Reusability of prior proven models provides opportunity to reduce cost and timing for developing new complex models. Time “The cheapest defect to fix is the one you prevented”* Quality Time Cost Reusability • Quality history, quality tools and lessons learned translated into design requirements and design rules are critical elements for preventing systemic issues on the new models. *Lenny Delligati , “ SysML Distilled” 8/14/2018 14
Systems Automation Engineering • In most of ground vehicle applications, about 40% of the components are carryover from the prior product generation, even for products with revolutionary innovation. 40% of carryover subsystems parts Gasoline Car Electric Car Pedestrian Protection Regulation compliance is extended through the products variants https://www.bmwblog.com/2014/05/06/pondering-bmws-cfrp-past-present- based on the same architecture future/http://www.electricmotorengineering.com/italian-automotive-components-industry/ https://www.continental-automotive.com/en-gl/Passenger-Cars/Chassis-Safety/Software-Functions/Passive- Safety/Pedestrian-Protection 8/14/2018 15
Systems Automation Engineering • The development of new products based on a common architecture, provides the opportunity to automate the systems engineering model creation, from common parameters for new product variants. 3D Parametric Automated Models • SMBSE automation generates models from parametric modeling algorithms that replicate existing models for new products with carryover architectures or subsystems. http://www10.mcadcafe.com/nbc/articles/1/965427/Concepts-NREC-Advancing-Clean-Efficient-Turbine-Technology-ASME- 8/14/2018 16
Systems Dynamic Simulation Engineering • Current common practice is to conduct the modeling, simulation and analysis on separate software platforms with minimum integration between these three central elements of systems engineering. Current MBSE practice 8/14/2018 17
Systems Dynamic Simulation Engineering • A common constraint in the conventional MBSE is the limited simulation functionality with linear models which are not representative of real complex systems. • An effective design of cyber physical systems requires the proper modeling representation, but fully integrated with simulation and analysis functionalities. SMBSE integrated elements 8/14/2018 18
Systems Optimization Engineering • The central benefit of SMBSE is to develop the simplest solution for complex and large system engineering, as well as to facilitate the decision-making process on the early architecture definition. Elegant Solution = Sufficient + Simple • Once the system solution is developed the optimization stage is activated by the application of smart algorithms to maximize performance and minimize costs. 8/14/2018 19
Systems Optimization Engineering • The SMBSE optimization functionality is oriented to identify different systems architecture options before proceeding to develop a new subsystem. The wider the scope of architecture optimization, the simpler the solution at different levels of decomposition. Elegance metric** Ei = Cp / Csi A) Integral Architecture * Where: B) Linear Modular Architecture Ei= elegance of the i sufficient solution C) Bus-modular Architecture Cp = complexity of the problem Csi = complexity of the I complexity solution B C A *Gwangki, M., Eun Suk, S., & Katja, H. O. (2015 de Dec de 21). System Architecture, Level of Decomposition, and Structural Complexity: Analysis and Observations.** Cfatmaneshnik & Ryan,2015 8/14/2018 20
Systems Optimization Engineering • Complexity elasticity metric is a recommended option to quantify the solution elegance 3 before and after an optimization process is applied. Don’t optimize parts at the expense of the whole 4 * 3 Salado, Alejandro, “ Painting Systems: From Art to Systems Architecting ” 2016, * Gwangki, M., Eun Suk, S., & Katja, H. O 4 Hillary Sillito . 8/14/2018 21
Systems Further Development Engineering • A growing need to lower costs and shorten the product development cycle has forced high-tech industries to virtual simulate engineering systems and gradually replace the full physical prototyping testing validation and verification. Physical prototypes units to be gradually replaced by virtual verification units 8/14/2018 22
Systems Further Development Engineering • Following this trend, the virtual product development (VPD) systems are leading the modeling simulation and visualization tools integration. • MBSE software tools are limited with static variables, making a challenging integration with VPD systems. https://hvm.catapult.org.uk/impact/case-studies/mtc-inspires-siemens-digital-factory-to-use-virtual-reality-for-product- and-factory-design/ 8/14/2018 23
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