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The Current State Of Model-Driven Engineering

By John Blyler

Panelists from industry, national laboratories, and the Portland State System Engineering graduate program recently gathered for an open forum on model-driven engineering.

The goal of the forum—which was hosted in collaboration with PSU, the International Council on Systems Engineering (INCOSE) and IEEE—was to connect systems engineering and IT modeling to domain specialties in electronic/electrical, mechanical and software engineering. Panelists included speakers from Mentor Graphics, ANSYS, CH2M Hill, Pacific Northwest National labs, SAIC, Veterans Affair Resource Center and PSU.

To clarify what is meant by systems engineering (SE), Herman Migliore, director of PSU’s SE program, cited Norm Augustine’s often quoted definition: Systems engineering is the practice of creating means of performing useful functions through combination of two of more interacting components. This broad definition encompasses all domain specific SE disciplines, including hardware and software.

Migliore noted that modeling the entire system engineering process, from beginning to end, is made difficult by the challenges of exchanging modeling information between all disciplines. These disciplines include engineering, science, business and even the legal profession, as well as vertical markets such as defense, electronics and software.

“Each discipline and market has it own view of engineering and modeling the system,” said Migliore. The challenge becomes integrating all these differing points of view. That’s why the one model that might unite them all is the Vee-Diagram, which emphasizes the decomposition of the high-level system into component pieces, followed by the integration of the components into a working whole. This approach requires designers to consider test, verification and validation requirements at every phase of the development life cycle.

Next up was James Godfrey from CH2M-Hill, a construction management company that includes semiconductor equipment programming and deployment. To date, many vendors use UML diagrams to engage customers about needed processes that will then be created in software. Unfortunately, UML doesn’t address continuous systems needed for continuing improvement, according to Godfrey. SysML does deal with continuous processes, e.g., pumps, fans and moving waste.

Doing his work at PSU, Godfrey learned about a collaborative system M&S framework developed at Georgia Tech (see diagram below).

Many in the construction management world question the need for models. Godfrey noted that these users wonder why that can’t continue to use Visio to capture typical construction drawings and specification. This often leads to a redundant entering of information into static diagrams and then later in dynamic models.

“Reality feeds into models that then can become diagrams,” said Godfrey. All of which should be stored in one data repository.

ANSYS approached the system modeling challenge from a more electronics point-of-view. According to Andy Byers, ANSYS started as a structural analysis company in the nuclear industry, among others. With the acquisition of Ansoft in 2008, ANSYS added electromagnetic modeling. System-level multiphysics and electronic power modeling were added with the purchase of Apache Design a few years later.

Today, most engineers communicate via documents. But many now want models in addition to documentation for the systems they’re building or integrating. Yet models in one engineering domain don’t often translate well to other domains.

“Pictures may be best way to talk across different engineering disciplines,” observed Byers.

Another factor encouraging model-driven development is that many component companies are now moving up the supply chain (or left-hand, integration side of the Vee-Diagram) to create subsystems, including both embedded hardware and software.

As companies are moving further up the system supply chain, they are finding out that optimization modeling techniques don’t scale across multiple point and physics, noted Byers. Such inefficient optimization leads to overdesign, where designers leave too much margin on the table. This message was a key theme at the recent Ansys-Apache Electronics conference (JB: reference]

But a system-level model must be simple enough for all engineers to use. Today, most analysis are set up and performed by a few experts with PhDs. These experts are becoming a bottleneck, said Byers. “There needs to be a democratization of simulation to the engineering masses.

Finally, as useful as the Vee-Diagram is for system-level modeling, users must look beyond engineering to other systems, like cost, schedule, and even legal. Focusing on this last point, Byers related a story concerning the exchange of models in the automotive industry between and OEM and a Tier 1 (subsystem) and Tier 2 (component) vendors. In order to avoid intellectual property (IP) and gross negligence issues, the OEM lawyers wanted to embedded a legal model into the engineering one. It was unclear as to the success of this approach.

Switching perspectives, Ryan Slaugh spoke about the challenges of hardware-software integration from the standpoint of the Pacific Northwest National Labs (PNNL). With its changing mission, PNNL is facing a problem that is commonplace to electronic companies—deciding when research projects are ready for commercialization. “ We are trying to cross the chasm of death from R&D to successful product development,” said Slaugh.

To determine the maturity of an R&D project, PNNL uses a Technology Readiness Level (TRL) process. This helps grade projects to tell when they might be ready to become products. For example, a project with high confidence, which is one that re-uses known good hardware and software, has a low score. Once in the product stage, systems engineering techniques are applied to the life cycle to low the risk of failure.

How are complex modeling approaches taught to students? What is needed to help college students get used to modeling? These questions where addressed by William “Ike” Eisenhauser, an affiliate professor at PSU and director of…

Simple modeling approaches make great communication tools, especially for non-technical professionals. But in essence, all models are wrong, noted Eisenhauser. “Yet some can be useful.”

Eisenhauser presented a brief overview of different kinds of models:

  1. Simple representation: e.g., solar system ball-and-string model in high school.
  2. Math model: Describes a situation (y=function of x).
  3. State diagram: Moving from math to device representation.
  4. Engineering flowcharts (non-math models): Communicate to others to help make decisions.
  5. Behavior models: More complex, intended to describes why system behaves as it does. These models help to predict change.
  6. Discrete models: Sometimes mistaken for the actual system. They demonstration implementation, e.g., balls moving in a physical model.

The greatest challenge with modeling is teaching that models are just tools, not playthings. “Modelers must learn when to stop using models,” cautioned Eisenhauser. “This is a critical lesson for engineers. “

The problem is that students go into modeling because they want to create cool models. It is an analogous problem to physics majors who go into physics to build light sabers, not to help mankind with issues of global importance, said Eisenhauser.

That’s why it is important to teach engineers the objectives of modeling and knowing when to stop.

How does modeling fit into the role of systems engineering? Unfortunately, SE remains a text-intensive discipline. Documentation matters in detailing complex systems. There is an ongoing need to reduce text editing in SE modeling. That’s where system-modeling approaches such as SysML can help.

The educational problem that Eisenhauer and others in PSU’s SE program face is how to provide a useful SE modeling tool. All such tools—even SysML—require more than one 8-week course to learn. Any such tool will need to be taught across several classes.

Is SysML the best tool for SE modeling in university course? That’s an ongoing challenging in modeling education, namely, how to discern the popular software-of-the-day from truly useful and market-acceptable tools, said Eisenhauser.

The final speaker was Bill Chown, from Mentor Graphics. He spoke about Model Driven Development (MDD), a contemporary approach in which the model is the design and implementation is directly derived from the model.

The challenges facing system designers are well known, from increasing complexity to the convergence of multiple engineering disciplines and the associated problem of optimizing a comprehensive system design.

The design team itself is a dynamic entity, comprised of an architect or systems engineer, the hardware or software component designer and the system integrator who puts it all together, noted Chown. Further, each of these professionals may only be involved in the design for their portion of the life cycle, such as from the concept through design and to domain specific areas.

What types of models are used through the lifecycle? Chown listed three categories:

  1. Platform Independent model, which includes function, architecture, interfaces, interactions and which can demonstrate that requirements are understood and met.
  2. Platform-dependent models, such as hardware architectures with virtual prototypes or software architectures with partitions and data, which can be used to determine resources and performance goals and for hardware-software co-design before physical implementation.
  3. Platform-specific models, for implementation, verification, test and deliverables.

Models can and should drive implementation. For example, software models can generate code once configured to an RTOS. Hardware flows have emerged for C-to-RTL synthesis and UML-to-SystemC simulation and validation. Test languages also can be generated directly from models.

Model-driven design has evolved to cover the full system or product life cycle, from requirements to prototype and then production.

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