Digital Engineering

Lifecycle activities for a project include concept development, and continue with design, construction, operation, maintenance, and conclude with project disposal tasks.  In the past, an individual working on a project might be concerned with only one part of the lifecycle, and then hand off the product or ideas to another person working on the next […]

Lifecycle activities for a project include concept development, and continue with design, construction, operation, maintenance, and conclude with project disposal tasks.  In the past, an individual working on a project might be concerned with only one part of the lifecycle, and then hand off the product or ideas to another person working on the next aspect of the lifecycle.  As projects have become more complex, and as hardware and software are being asked to work together more than ever, it is no longer possible to work on some isolated aspect of a complex project; the project must be handled holistically across all phases of the lifecycle, and this requires a new way of doing business. 

Traditional engineering projects would have addressed requirements, design, verification and validation, and then delivered the project to the customer for construction, and eventually ongoing operation and maintenance.  The new paradigm, Digital Engineering, addresses all of the things that Traditional engineering addressed, but continues to be active and relevant throughout the entire remaining Lifecycle of the project.  Digital Engineering is defined (Steven’s Institute of Technology) as ‘‘an integrated digital approach that uses authoritative sources of systems’ data and models as a continuum across disciplines to support lifecycle activities from concept through disposal.”

The first phase of the lifecycle is concept development and design. Model Based Systems Engineering (MBSE) supports these preliminary systems engineering activities; requirements, architecture, design, verification, and validation. Physics based models used by other engineering disciplines would then need to be connected to the model in order to assess and monitor operations during the following phases of the lifecycle.  All of these models used holistically would be a Digital Engineering approach to the project.

In the past, a building project would result in one product, the building itself.  Using the digital engineering approach, we would end up with two distinct products.  The first product would still be the building, but the second product would be a “digital twin” of the building.

A modern building can be thought of as a System of Systems.  The building is a System, but it is comprised of many subsystems; climate control system, fire control system, electrical system, just to name a few.  Under traditional engineering methods, if there was a problem with one of the subsystems in the building, maintenance people would need to troubleshoot the problem using tools like voltmeters and sledge hammers, identify the best solution, perhaps tear down drywall to access and fix the culprit system, and perhaps ultimately discover that they did not fix the problem, or discover that that when they fixed one subsystem, they caused unwanted effects on other subsystems.    If that is the case, the troubleshooting would start again, and the repair process would be repeated, maybe now on additional subsystems, until the problems are ultimately identified and fixed.  This is a cumbersome and expensive process, but it is how we have done business for many years.

With a “digital twin” which resulted from using the Digital Engineering process, one could troubleshoot the problem from a computer, and test potential solutions to see if the outcome would be favorable.  Additionally, Digital Engineering could utilize Artificial Intelligence (AI) with data collected from each subsystem, to alleviate or prevent many problems before they even occur. 

When problem do occur, however, although a solution may solve the immediate problem, it can sometimes cause new problems which need to be addressed.  With the “Digital Twin”, the solution to the problem can be investigated and verified before any repairman grabs his toolbox and starts tearing down walls.  If there are unexpected consequences associate with the repair, it will quickly become evident from the Digital Twin.

The holistic approach of Digital Engineering can have profound impacts on production costs, production schedule, and risk reduction throughout the entire lifecycle of the project.  For these reason, Digital Engineering is rapidly gaining popularity in today’s marketplace.

If you want to learn more about Digital Engineering, consider taking the ATI course Digital Engineering. This two-day short course provides an overview of the Digital Engineering of systems, and how models, simulations, and data enable its implementation.  To learn more about this course, and to register to attend, please visit here.

ATI will be offering a free Webinar preview of Digital Engineering on September 13.  At this event, you will be able to meet the instructor and hear what he has planned for the full course in October.  Feel free to attend the free preview even if you don’t plan to attend the full course; you may learn something, and, we may change your mind.  You can learn more about the free preview, and register to attend it here.

If you have any questions about this course, or any course at ATI, please reach out to us. Contact information can be found at www.aticourses.com .

Modeling and Simulation

Modeling and Simulation can be very complex, or it can be a simple part of everyday life. One can compute the probability of a certain event occurring.  As a simple example, the probability of throwing a die and getting a 1 is computed to be 1/6.   The Law Of Large Numbers says that if you […]

Modeling and Simulation can be very complex, or it can be a simple part of everyday life.

One can compute the probability of a certain event occurring.  As a simple example, the probability of throwing a die and getting a 1 is computed to be 1/6.   The Law Of Large Numbers says that if you conduct a trial a large number of times, perhaps an infinite number of times, you will observe the computed probability of that event; it’s an undisputable fact.  So, if you are a casino dealing with very large numbers of games, you can compute the simple probability of a casino win for each game, and the casino can be 100% assured, given that they host a very large number of games, that they will win that percentage of times, overall.  So, as one might expect, although a player may be gambling, the casino has a sure bet.  If a casino offers a bet, they know they will win it, over time.  Its all in the numbers.

In the example of throwing the die, we know that once every six rolls, on average, we will roll a 1.  Any game of chance, like the roll of die, is essentially a simulation of behavior with a known probability distribution.  The goal of data analysts is to create a simple model to determine the behavior of complex systems.

As data analytics becomes increasingly popular, the use of Modeling and Simulation in Systems Engineering is becoming more important too.  If you want to learn more about how M&S fits into the Systems Engineering process, ATI has a course that will help you.  Consider taking our new offering of Modeling and Simulation in the Systems Engineering Process

This two-day short course provides an overview of the use of Modeling and Simulation in the Systems Engineering process. After an introduction of key M&S terms and processes, the course presents an overview of the types of models and simulations used across the phases of the Systems Engineering life cycle, from system needs analysis through system sustainment.  Examples are given for several types of systems, including systems developed under the U.S. Department of Defense (DoD) acquisition process.  The course then provides information on advanced M&S and Digital Engineering topics, including the U.S. DoD Digital Engineering Strategy; the Unified Modeling Language (UML) and the Systems Modeling Language (SysML); interoperable and live-virtual-constructive (LVC) simulation; collaborative environments and asset repositories for Digital Engineering; and modeling the natural and man-made environments.

Consider registering for this class.  You can find additional information on the class, and you can register to attend here.  And, as always, you can find a full listing of ATI’s other classes here.