Achieving a fully-functional digital twin and digital thread is critical, will be game-changing and most likely inevitable. Ironically, before the aviation, aerospace and defense (AA&D) ecosystem can unleash digital capabilities, they will need to solve some unique analog problems first.
The AA&D ecosystem still needs to better define these two buzz terms more concisely. There are many exotic and confusing definitions for both the digital twin and digital thread. In addition, the concepts mean different things to different stakeholders within the ecosystem. OEMs and suppliers have one point of view while owner operators, commercial players and military have their own. Service providers have yet another definition.
Perhaps by focusing on the essential nature of each term we can simplify the discussion:
• Digital twin is the digital representation of the “current state” of a manufactured product or system at any given point in time.
• A Digital thread is the digital record of all “states” of a manufactured product or system over time from conception to disposal.
In both cases, and most importantly, the digitized information or data must be “suitably complete and accessible” to enable business, technical, operational or analytic objectives.
This requirement for “suitably complete and accessible” digital data is the essence of the first analog problem. The AA&D ecosystem includes some equipment that was designed, built, and put into service long ago using older technologies. For example, a 35-year-old C-130 tail number was not developed using today’s digital PLM systems; and, its maintenance record may not be digitally recorded.
Many of the manufactured products and systems in the AA&D ecosystem have flat sources (i.e. paper or 2D CAD, etc.) of information that are needed for fully-functional Digital Twins or Threads. Information may also be missing, incomplete or possibly incorrect. This is in addition to concerns around data security, ownership, volume and integrity. These challenges thwart the requirement for information to be complete and accessible.
Hardware and software technology can assist with many of the “flatness” issues, but barriers such as data ownership remain. One aircraft can have hundreds of suppliers that contribute to the design, build and service, but there is a lack of trust to share “data” beyond that which is required by the contractual terms and conditions. The ecosystem has to evolve its collaboration model. There is no silver bullet that stitches all of the disparate information together.
The second analog issue involves people; and, aligning workforces for the future. For example, a new aircraft with a fully-functioning digital twin or thread with predictive analytics in place may be able to detect a fault about to happen in one of the engines. Perhaps that future fault does not jeopardize the flight prior to scheduled maintenance; but, when it lands, corrective action questions arise. Some of them include:
• Who deals with the decision to take action or not ahead of planned maintenance?
• What decision criteria does that person(s) use?
• Are replacement parts available at the next ground stop?
• Are technicians available to make the unplanned repairs?
• Can the decision maker determine if parts/personnel are in place?
• Can the decision maker get them in place if they are not?
The AA&D ecosystem has an existing, fairly inflexible, complex supply chains that will need to adapt to future operating models—as will the people in them. Assuming these future capabilities like analytics are providing both broader, deeper, and eventually predictive insights from which these people will operate, network, and make decisions, then roles and responsibilities will need to be redefined and realigned on a massive scale—incrementally.
Change of this magnitude is laborious, non-linear, emotional, controversial, and even political. The AA&D industry has an impressive history of ushering in new, complex, manufactured products and systems, but, collectively, this type of cultural, organizational and behavioral change is not a strength.
It comes down to some very basic questions which the human elements of the AA&D ecosystem—people, companies, culture, and institutional norms will need to reexamine. As ecosystem members grapple with operationalizing new business capabilities based on synthesized digital twins and digital threads the questions of who owns these capabilities, when and where such capabilities apply to business scenarios or events, and how these capabilities are enabled will demand entirely new levels of collaboration and decision-making skills.
Digital twin and digital thread-based capabilities should become a massive advantage for enabling future operating models, revenue streams, and relationships. Addressing lingering analog issues is a prerequisite to success and should not be underestimated.
While an aircraft, ship or spacecraft may be able to operate autonomously; they cannot be conceived, engineered, manufactured or serviced without people collaborating globally. This next level of ecosystem-wide collaboration will inevitably be based on “suitably complete and accessible” information and data.
This is the beginning of a very exciting journey indeed—but—we are barely at the end of the beginning, and not nearly at the beginning of the end. Establishing a fully functioning digital twin or thread will demand a premeditated and persistent effort to reap the rewards.