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.
Many who work the field of digital engineering give the example of producing two distinct products. 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 were “barking up the wrong tree.” If that is the case, the troubleshooting would start again, and the repair process would be repeated until the problem is 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.
Anyone wishing to learn more about Digital Engineering should start by learning more about Model Based Systems Engineering. ATI offers a three-day class that provides an introduction to Model-Based Systems Engineering. Lectures on proven, state-of-the-art techniques will be reinforced with lessons learned and case studies from the instructor’s own experiences applying MBSE of major DoD acquisition programs, along with in class, live demonstrations using a popular system modeling tool (Cameo Systems Modeler™ by No Magic, Inc.) to create an example model. The course is valuable to systems engineers, program managers, and anyone else interested in understanding what is required to create a system model, how to use it to support systems engineering activities on a program, and the benefits that can be realized.
To learn more about this the ATI course Model-Based Systems Engineering, and to register for this class, you can go here. And, as always, to learn more about the other courses available at ATI, go to www.aticourses.com .