Model-Based Systems Engineering (MBSE) Application Strategies

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来自 University at Buffalo 的课程

MBSE: Model-Based Systems Engineering

49 个评分

University at Buffalo

MBSE: Model-Based Systems Engineering

49 个评分

课程 8（共 9 门，Specialization Digital Manufacturing & Design Technology ）

This Model-Based Systems Engineering (MBSE) course and the Digital Thread courses featured earlier in this specialization bring together the concepts from across digital manufacturing and design, forming a vision in which the geometry of a product is just one way of describing it. MBSE is where the model resulting from the evolution of system requirements, design, analysis, verification and validation activities is the focus of design and manufacturing. Students will gain an understanding of systems engineering, the model-based approach to design and manufacturing, the Digital Twin, and a roadmap toward a model-based enterprise. Students will be able to explain the value and expectations of systems engineering and model-based systems engineering, and the underlying motivations and opportunities represented by a model-based enterprise. They will develop the knowledge necessary to perform a baseline assessment of an organization’s potential to leverage MBSE. Main concepts of this course will be delivered through lectures, readings, discussions and various videos. This is the eighth course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA

从本节课中

Model-Based Systems Engineering

The purpose of this module is to explain Model-Based Systems Engineering (MBSE) and its applications. Upon completion, learners will be able to assess a process for MBSE opportunities and develop an argument for implementation. The learners will also be able to develop a strategy on how to implement applications of MBSE.

Model-Based Systems Engineering (MBSE) Application Strategies5:08

与讲师见面

Ken English
Deputy Director
Sustainable Manufacturing and Advanced Robotic Technologies Community of Excellence

Recall a graph showing the timing of costs committed versus cost incurred.

If we overlay two additional curves,

product knowledge versus time and the ability to change a design versus time,

these curves guide us to the following conclusions.

That increased simulation capability and capacity provides more knowledge

earlier in the design process enabling changes to be made before costs are committed.

It's important to maximize impact on cost drivers

and maximize the ability to iterate early in the design process.

And developing and using models allows the product knowledge curve to be shifted left,

front loading product knowledge,

reducing the need for physical prototypes.

To truly use a model-based system to its full potential,

a framework is required.

This framework provides the guiding structure to

implement analysis throughout the lifecycle of the product.

MBSE frameworks can focus on

single components or a series of components that are linked together.

Each part of the model can be checked for errors as well to

determine if a design meets the product development requirements.

An analysis framework connects a variety of

simulation tools -- for example, Ansys, Nastran, Matlab,

and tools built in-house -- in such a way that outputs of

one analysis provide the input for subsequent analyses without human intervention.

A framework will also have some form of execution engine or control

mechanism to iterate the analyses

until a stable solution is reached for a particular design point.

Models and the framework can be

version control and updated without impacting the architecture of the analysis.

In an ideal situation,

MBSE focuses a significant amount of effort on getting the requirements right.

With some analysis frameworks,

these requirements can be automatically checked against

simulation outputs to see if expectations are met.

One example of an MBSE framework is Siemens offering HEEDs.

HEEDs provides a means of computationally exploring

possible design alternatives in search of specific performance goals.

And, in HEEDs, design space exploration is made possible

by automating the construction of the virtual prototype via process automation,

accelerating testing of the virtual prototype via distributed execution,

looking for better design alternatives via an efficient search process,

and ensuring reliable product performance via

insight and discovery tools related to visualization.

When we think about these automated processes,

keep in mind the traditional process of simulation

requires multiple steps and human intervention.

The MBSE process allows for automated design space exploration.

And, with that in mind,

another example of an MBSE framework is the LMS Imagine.Lab.

LMS Imagine.Lab facilitates the simulation of mechatronic systems using an MBSE approach.

Imagine can integrate with LMS Amesim models,

Matlab and Simulink models, or other tools.

LMS Imagine.Lab has three key components.

System synthesis which focuses on system architecture and configuration.

Amesim which is for building and running simulations.

And Sysdm which focuses on system data and configuration management.

These all come together in order to explore our design spaces for our products.

Other example frameworks include Phoenix Integrations ModelCenter.

This creates and automates simulation workflows,

allows the integration of models from standalone application,

and runs multi-disciplinary simulation processes.

The MBSE pack of model center enables integration with Doors or No

Magic to connect requirements to

model-based simulation results closing the loop in system design.

Esteco's ModeFrontier is another simulation workflow automation tool

that focuses on trade space exploration.

And Dassault's iSight is a simulation workflow automation package that enables

optimization and the exploration of design of

experiments in a multi-disciplinary analysis environment using different tools.

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