How digital engineering is redefining the product development lifecycle
Although the fundamentals of system engineering have remained the same, all other aspects such as tools, speed, complexity, and risks have changed. Digital engineering should not be viewed as a separate discipline but as the adaptation of the existing discipline to new technological environments.
From documents to living models
For many years, the product development lifecycle relied on paperwork. Requirements were stored in Word documents. Design choices were kept in PDFs. If anything was modified, someone updated a document, sent it via email to a distribution list, and prayed that everyone was utilizing the most recent version. For projects containing hundreds of requirements and numerous contributing teams, that expectation was often incorrect.
Model-Based Systems Engineering (MBSE) substitutes that dormant documentation with lively, connected models. When a requirement changes on a systems level, that alteration spreads through the architecture automatically. Design teams, test engineers, and production planners all have access to the same updated information without organizing a meeting to reconcile different views. The model turns into what experts refer to as a Single Source of Truth – a single legitimate archive that every area of expertise references and contributes to.
This transformation is most important in sectors such as aerospace and defense, in which a single poorly communicated requirement can destroy a project for several months or result in a series of failures that come to light during the final phase of integration.
The skills gap is the real constraint
There are two key differences between system engineering and MBSE. The first is how engineers capture information – not as text in a word processing document, but as elements in a model. The second is a result: requirements don’t stand alone, but are connected to objects that are shared across the enterprise.
For example, in an automotive program, a “vehicle” is described exactly once in a model, and designers, safety teams, SW and HW teams all agree to use that same description for the life of the program. For each new or changed requirement, owners define the impacted elements, who reviews the change, who approves it, and what is the current status. This is why obtaining an mbse certification has moved from a resume differentiator to a practical necessity for engineers leading complex programs. This level of transparency through documents would be unwieldy, if not impossible, to maintain.
The short version – systems engineering did a great job with the tools they had, but those document-based tools are limiting across the growing complexity we’re now seeing in engineering programs. MBSE up-levels those tools to stay on pace with the kinds of systems we all want to build. It’s not the technology wave that’s coming, it’s the one that’s already here.
The digital twin advantage in early-phase design
One of the most apparent advantages of digital engineering is how it impacts physical prototyping. Before the actual component is ever manufactured, engineers have always been able to build a digital twin – a virtual representation that behaves according to real physics, thermal properties, and interface constraints.
However, this is more than conceptually advantageous simulation. It’s about moving the discovery of problems earlier in the schedule, when changes are still inexpensive. Identifying a structural interference or thermal conflict in a digital twin during preliminary design might take days to resolve. Finding the same problem during a hardware build can take months and cost orders of magnitude more.
Simulation Driven Design simply compresses multiple, former-test/fail/fix cycles into a workflow where most failures occur in software, not metal. Verification and Validation (V&V) activities that formerly required physical hardware can start while the hardware is still in design.
Why data silos keep derailing large programs
Inadequate data integration causes costly interoperability issues and requires an astonishing amount of manual data reentry. The cost that needs to be covered by the company for operating without a digital thread as a result can be significant and ultimately tied to their level of digitalisation. A digital thread is a communication framework that connects traditionally siloed elements in business processes and also in product lifecycle management. These elements include design and manufacturing systems and data sources (including IoT and the product’s digital twin), all the way to end-to-end horizontal and vertical integration that spans a supply chain from its engineering, design, and manufacturing processes to its order fulfillment, warranty management, shutdown, and recycling. When a digital thread is established, an engineer pulling requirements or bills of materials from a product lifecycle management system, for example, is working from the same connected, consistent information as an analyst running simulations or tests in an engineering modeling or simulation environment. When they’re not, the engineer and the analyst are likely maintaining separate spreadsheets and catching and correcting discrepancies only through manual effort.
The medium changed, the mission didn’t
Digital engineering does not reinvent the wheel of what system engineering is intended to do. It is all about managing complexity, managing requirements, and designing, testing, and putting into the field what we’ve engineered to do those things we need to accomplish. The difference then, in my mind, is the costs of constantly doing it the old way. The risk we enable through integration days, the schedule we compress to meet the commitment of delivering capability, and in some cases, the solution we reduce our expectation and the intent in doing it is through a volume of captured words, documents, and email threads. Organizations that view digital engineering as optional continue to take on and accumulate that technical debt for every single program run. Those that start to view it as infrastructure are starting to increase their probability of better outcomes, and in turn, are building a literacy and a workforce to sustain those fully digital engineered capabilities into the future.
