Great Read “Enhancing MBSE with LML”

Review on “Enhancing Model-Based Systems Engineering with the Lifecycle Modeling Language” by Dr. Warren Vaneman

Dr. Vaneman’s paper on “Enhancing Model-Based Systems Engineering with the Lifecycle Modeling Language” provides a compelling justification for the need of a simpler, yet more complete, language, which integrates systems engineering with program management to support the entire systems lifecycle. It shows that the current LML standard 1.1 includes all the key features of the Systems Modeling Language (SysML), and thus can be used by people who practice systems engineering to generate the complete SysML diagram set.

This paper expresses the key goals of LML: “1) to be easy to understand; to be easy to extend; to support both the functional and object-oriented (O-O) approaches within the same design; 4) to be a language that can be understood by most system stakeholders, not just systems engineers; 5) To support the entire system’s lifecycle – cradle to grave; and 6) to support both evolutionary and revolutionary system changes to system plans and designs over the lifespan of the system.”

Dr. Vaneman covers three themes in the rest of the paper: 1) overview of legacy modeling and in introduction to LML; 2) comparison of SysML and LML using eight MBSE effectiveness measures; and 3) the potential to use LML as an ontology for SysML. Of particular interest was the comparison of SysML to LML. The major problem with SysML is the lack of an ontology, which makes it less expressive and precise. SysML seems to have problems in usability as well, due to the complexity of the diagraming notations.

Although a preliminary mapping of LML to SysML was done as part of the first release of the standard, the 1.1 version only had to be slightly modified to more fully visualize all the SysML diagrams. Only two new entity classes were defined (Equation and Port). Equation was developed to support the Parametric Diagram, which diagrams equations, and the Port, which is a subclass of Asset, was essential for a couple of the physical modeling diagrams.

I heartily agree with Dr. Vaneman’s conclusion that “LML provides a means to improve how we model system functionality to ensure functions are embedded in the design at the proper points and captured as part of the functional and physical requirements needed for design and test.”

You can read Warren Vaneman’s paper here:

IEEE MBSE Paper- Vaneman

More resources:

-LML website

Quick Guide to Innoslate’s Ontology


10 Qualities That Make a Good Systems Engineer

All systems engineers should have an understanding of basic concepts and a strong technical background, but these qualities go beyond just the necessities. From 40+ years of experience, I have found that a good systems engineer must have the following 10 qualities.

#1 Patience and Perseverance

To create a complicated system, an engineer must have a lot of patience and perseverance. The more complex the system the longer and more tedious a project it becomes. An engineer cannot figure out everything at once. It takes time to see the big picture, to look for all the small details. You will test and test and still find errors. You have to have patience to know that it takes time and determination to keep going after hundreds of failed attempts.

#2 Ability to Know When You Are Done

A good systems engineer wants their project to be flawless, but often it’s too easy to fall into a perfectionist trap. You tell yourself, “One more change and it will be perfect.” However, doing this may mean you never complete your project and all that hard work will become obsolete. The best engineers know when their system is good enough and when the system needs a little more re-engineering.

#3 An Analytical Brain

Most engineers are naturally analytical, which is probably why they were attracted to the field in the first place. From the moment they could talk, they were the ones that continually asked questions and analyzed the world around them. A good systems engineer can go one step further than just analyzing and look for solutions to the problems and questions they analyze.

#4 Knowledge of Systems Engineering Software Tool(s)

In this day and age all systems engineers should have some experience with tools. Most colleges, especially grad school level, use systems engineering software tools. These tools allow you to create complex systems. They help you organize your information and develop documentation and reports at a much quicker pace and with higher accuracy. They can also help you analyze your information better. Even though you should already be a pro at analyzing, using a tool can help your organize the information in a way that makes analyzing faster and easier. Tools can make you into a better systems engineer. Tools, such as Innoslate®, are capable of improving you as a systems engineer.

#5 Strong Organizational Skills

You need organizational skills in order to handle the amount of information that a systems engineer deals with on a regular basis. It is important to organize well, so you are able to track status and history accurately and create documents and reports that are understandable. Although a tool can greatly improve the way you organize, you still need to understand organizational concepts.

#6 Ability to See the Small Picture

One of the greatest qualities a systems engineer can have is to be detailed oriented. You should be able to look at the small picture and see that all the details are thoroughly reviewed and that no errors occur. You need to be detail oriented type of person. Much of what we do is planning. Just like if you are an event planner, you have to make sure all the details are just right to make the ultimate goal (the event) a success.

#7 Ability to See the Big Picture

The overall system needs to be looked at just as much as the small details that make up the system. You need to make sure that the goal of the entire system is kept in mind throughout the planning. A good systems engineer needs to be able to determine future needs as well. They must have vision (I talk about this in my upcoming book on LML) and be detail oriented, but still be able to see the big picture.

#8 Well Rounded Background

A bad systems engineer knows systems engineering concepts and definitions like the back of his hand, but knows nothing else. A good systems engineering tries to be knowledgeable in other subjects relating to their field. A great systems engineer understands the importance of being well-rounded. A well rounded background will help a systems engineer analyze and find potential issues better than anyone else.

#9 Communication Skills

Unfortunately, English is not a high priority for many engineering colleges. Systems engineers need to communicate well. They need to be able to communicate to non-engineers. Communication skills take time and practice to perfect. If you are a systems engineer and you know that communication is not a strong skill of yours, make the effort to improve.

#10 Ability to Lead, Follow and Work Well in a Team

At some point in your career you will have led, followed, and worked in a team. The best systems engineers know how to do all three well. A good leader knows how to follow and work together with others. A leader understands what his or her team needs to know and understand. The inability to do all three can be detrimental to a project. Systems engineers, more often than not, do extremely important work and need a good leader and a good team to follow.


It takes a lot of time to develop all these qualities. I know I did not have all of them when I began my career. Don’t let this discourage you, but make it a goal to obtain each one of these qualities.

If you think you have these qualities, join our team.

Reposted from SPEC Innovations with permission.


Document Trees in Innoslate

Different levels of documents result from decomposition of user needs to component-level specifications, as shown in the figure below.

Innoslate enables the user to create such trees as a Hierarchy chart, which uses the “decomposed by” relationship” to show the hierarchy. An example is shown below.

Each of these Artifacts contain requirements at the different levels. Those requirements may be related to one another using the “relates from/relates to” relationship if they are peer-to-peer (i.e. at the same level of decomposition) or using the decomposed by relationship to indicate that they were derived from the higher-level requirement.

This approach allows you to reuse, rather than recreate requirements from a higher-level document. An example is shown in Requirements View below.


In this example, the top-level Enterprise Requirements were repurposed for the Mission Needs document (MN.1.1 and MN.1.2) and the System Requirements Document (SRD.5). If you prefer to keep the original numbers, you only have to Auto Number the ERD document using that button on the menu bar and the objects would show up with the ERD prefix in the lower documents. Note that in either case, the uploaded original document would retain the original numbers, in case you wanted to reference them that way. Also, each entity has a Universal Unique Identifier (UUID) that the requirement retains, if you prefer to use that as a reference.

This approach discussed above is only one way to accomplish the development of a document tree. Innoslate enables other approaches, such as using a new relationship (i.e. derived from/derives). Try it the way above and see if it meets your needs. If not, adjust as you like.

Do Frameworks Really Work?

Over the past 20 years, we have been using various “Frameworks” to capture information about architectures and systems. Beginning perhaps with the Zachman Framework, which is still one of the most successful. The Zachman Framework is timeless for this reason: it forced us to think about the standard interrogatives (Who, What, When, Why, Where, and How) and different perspectives (Executive, Business Management, Architect, Engineer, and Technician) as applied to the enterprise. The idea was to build models in each area, starting with simple lists and working into detailed models of the systems at a component level.

Other frameworks followed, included the DoD Architecture Framework (DoDAF – which came from the C4ISR Architecture Framework), the Ministry of Defence Architecture Framework (MODAF), the NATO Architecture Framework, and many others. All these Frameworks were built on the idea that the information could be easily “binned” into these boxes, but as we know many of the models in these Frameworks included maps between different data elements, such as the CV-6 from DoDAF that maps Capabilities to Operational Activities. Recently, the Object Management Group (OMG) and others have been trying to push out a Unified Architecture Framework (UAF) that combines the models from many of these other frameworks into a single, very large framework. OMG is also responsible for developing the Unified Modeling Language (UML), Systems Modeling Language (SysML), and the Unified Profile for DoDAF and MODAF (UPDM).

All of these framework and languages are ways to capture information about a system or enterprise and show them as a set of data, often as a picture or model with two or more pieces of information in the model. An example is the DoDAF OV-5a, which is a functional hierarchy of Operational Activities, which only contains a single entity class and the decomposition relationship between those entities. Another example is the OV-5b, which shows the Operational Activities and the “Resource Flows” (which many of us recognize as inputs and outputs to/from the Operational Activities) between them. Thus, we have now two entity classes and the associated relationships between them. Obviously, the information in the CV-6, OV-5a, and OV-5b overlap in that the same Operational Activities need to show up in each of these models. But how many of these different models would we need to complete describe a system or enterprise?

An alternative way to capture information is to use an ontology (and the DoDAF 2.02 is based on a rather large ontology – the DoDAF MetaModel 2.0 or DM2) that captures the information in a finite number of classes (or bins) and a set of relationships between these classes. The classes and relationships can have attributes associated with them, which are also pieces of information. At the ontology level, all we see is a mass of data, so most of us want to see the pictures, and most architects and system engineers seem to prefer this approach.

An alternative to the DM2 is the Lifecycle Modeling Language (LML), which contains both an ontology and a set of diagrams to capture the necessary technical and program information associated with a project. This language uses an ontology that appears simpler than the DM2, but actually hides the complexity through the large number of relationships between entities and the fact that the relationships can have attributes associated with them. LML purports to be the 80% solution to the ontology, meaning that you may decide to extend it to meet your specific needs. But let’s just stick with it. LML has 20 classes of entities, and each entity class has a number of relationships associated with it (over 40 in total). So, if we ignore the attributes, we have over 20(20-1)/2=190 combinations of information possible. Does that mean I need 190 or more diagrams to visualize all this information, perhaps – it could be less, but it could be more. Can we really have that many different diagrams to represent this information, which is what a Framework would require? And of course, if we add in all the attributes to both the classes and relationships, then we are trying to display a lot more information than this.

So, Frameworks are a useful starting point, which is how John Zachman uses his framework, and it may be enough for enterprise architecture, but it’s not a panacea for all of systems engineering problems. Sooner or later as we want to decompose the system to a level we can determine what to buy or build, as well as manage these kinds of projects, you likely will need to use a more robust approach. LML and this kind of ontology makes it much easier to capture, manage, and visualize the information. See for yourself. Go to and try out the tool that uses LML for free. Explore the Schema Editor to see the entire ontology. Play with the “Getting Started” panel examples. I think once you do you will find this approach works much better than the Frameworks. In addition, Innoslate has a “DoDAF Dashboard” that enables you to create DoDAF models directly from the dashboard, so if that’s what you are more familiar with, you will find it the easiest to get started. Notice that may of the other projects are automatically populated with the information from the other models. That’s because Innoslate reuses that information to automatically create the other views!