Model Based Systems Engineering and Modeling Limitations

 What is  MBSE / IVHM / HUMS / SHM / Reliability Metrics ?

MBSE - Model Based Systems Engineering

Systems Engineering is the study of systems, including stakeholders, their requirements

Industrial Engineering is systems engineering practiced to optimize the systems, subsystems, components or materials used create, design and manufacture, process and assemble functional systems.

Models start out as mathematical entities that express functions to meet system requirements.  Physical implementations are constrained by physics or capital that limit their function.

At the University of Arizona, Dr. Wymore founder of Systems Engineering department, defined system models by 5 components:  
    States, 
    Inputs, 
    Outputs, 
    Next State Transfer Functions 
    Output Functions

Systems are composed of models and coupling functions that describe how each of the five components relate to each other. 

Model Based Systems Engineering creates system models to meet functional requirements.  Functional requirements are written by stakeholders and may inherit requirements from previous models; requirements are always stated as "shall" provide this function, the feature or this dynamic. 

In practice, many systems fail at the interfaces between models due to incomplete analysis, incompatible model interfaces, simplistic mathematical modeling and simulation.  Many mathematical models assume that the sampled data representing the system status can be fit into various statistical distributions. e.g. Exponential, Gaussian, Poisson.  These distributions are associated with closed form mathematical models that eases the computational complexity.  

Limitations of current system modeling include:
1) Defective products or batches - 
    Statistical process control systems have been widely utilized yet all manufacturing systems generate  defective products.
2) Independent Identical Distributions (IID) - Defective Models 
    Functional partitioning and related models that depend on IID - Identical Independent Distributions, eliminate actual dependencies that exist between systems.  

The solution summary is to consider and correlate all system parameters.  Then look for similar patterns that indicate 


References:
1) Wymore, https://www.amazon.com/Model-Based-Systems-Engineering-Wayne-Wymore/dp/084938012X 
2) Bahill, Chapman, Wymore - https://www.amazon.com/Engineering-Modeling-Design-Systems-dp-0849380111/dp/0849380111/ref=mt_other?_encoding=UTF8&me=&qid=1603414635 
3) Bahill - Systems Engineering UofAZ URL: http://sysengr.engr.arizona.edu/whatis/index.html




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