VIEWPOINT AIR POWER

Aerospace, Defense Industry Must Join Digital Revolution

5/30/2018
By Ed Kraft and Dave Chesebrough
General Electric has embraced the use of digital twins.

Art: GE

A hallmark of modern, innovative businesses is that they think digitally. They recognize that technology galvanizes different ways of thinking, and therefore doing.

The introduction of steam and water power in the 1800s, electricity in the early 19th century and electronics in the 1970s resulted in wholesale industrial revolutions with drastic changes in society and warfare.

Today’s digital engineering, sometimes called Industry 4.0, is causing a new industrial revolution. Driven by cyber-physical technologies such as industrial internet of things, cloud computing, big data analytics, digital engineering and digital manufacturing, it enables transforming document-centric processes to a digital, model-based systems engineering approach involving all the advances of the new cyber-physical world. 

It is not a question of whether the aerospace and defense industry will join the digital revolution. It is already happening. The questions are: when, to what degree, how and to what benefit?

Digital twin, or digital thread, are terms being used to describe engineering in a digital environment through modeling and simulation. At General Electric, the concept of a digital twin embodies a software representation of a physical asset such as an engine. This allows customers to better understand, predict and optimize the performance of each unique engine. This digital representation can be done for an individual asset, an integrated system of assets or a fleet of assets. In 2017, the research and advisory company Gartner identified “digital twin” as one of the top 10 critical technology trends.

Digital engineering in acquisition and sustainment of defense systems is gaining traction across the industry. Adopting digital engineering requires a digital environment, or ecosystem. It is an integrated, interconnected infrastructure and methodology — process, methods and tools — used to store, access, analyze and visualize evolving data and models. This is the definition of a digital engineering ecosystem provided by the digital engineering initiative in the office of the deputy assistant secretary of defense for systems engineering.

The ecosystem houses and manages the technical data such as digital drawings, models, test data, reports, and operational and maintenance data in a manner such that it is accessible to engineers and analysts across the lifecycle.

At any point in the lifecycle, data from the engineering ecosystem can be transformed using model-based systems engineering and model-based engineering combined with uncertainty quantification to address engineering challenges and to guide enhancements to the design, manufacturing, production, testing, operation and sustainment of systems.

From these modeling activities, authoritative digital surrogates can be generated to better emulate the performance and characteristics of the system relative to the requirements. As one moves vertically through the ecosystem, the digital surrogates can be used to efficiently support a probabilistic analysis of margins, uncertainties and risks in support of decision making under different scenarios. Robust uncertainty quantification is the connecting tissue between data, engineering analysis, risk analysis and decision making. This digital system model, frequently referred to as the digital thread, is the communication framework for the digital engineering ecosystem.

The digital twin is the parallel digital simulator to an assembled system by part number/system number from design and build to operation and maintenance. The essence of digital engineering is the connection of all phases of a system lifecycle to a shared, authoritative source of the system’s models and data.

For the aerospace and defense industry to take full advantage of the digital revolution it will not only require a digital ecosystem, but also a transition from linear, document-centric processes to dynamic, digitally-connected processes that maximize the advantages of a digital ecosystem. This is not the digitization of existing linear, document processes but a transformation to new streamlined processes enabled by a digital environment. It is thinking digitally in defense acquisition.

DoDI 5000.02 is a linear, document-centric, acquisition process guide that is a product of the post-World War II model for buying defense capabilities and drives the timelines for system acquisition. It was built in a paper world, but today we live in a digital world.

According to the Government Accountability Office report, “Acquisition Reform: DoD Should Streamline Its Decision-Making Process for Weapon Systems to Reduce Inefficiencies” (GAO-15-192), acquisition programs spend, on average, “over two years completing numerous information requirements at each milestone decision, yet acquisition officials considered only about half of the requirements as high value.”

Average time to prepare and review major acquisition documents — such as the capability development document, the systems engineering plan and the test and evaluation master plan — is measured in years. Moreover, these documents are not linked dynamically to changing requirements.

A requirement changed the day after the document is complete can take up to another year to be updated and validated in the document. At a time when the adversary has found ways of getting capability deployed faster than the U.S. military, this is a decided self-inflicted disadvantage. The main driver for modifying requirements is the changing threat. The lag time built into the current process increases the probability of delivering a system that does not meet the need when introduced.

"Digital engineering in acquisition and sustainment of defense systems is gaining traction across the industry."

Likely benefits from using digital engineering approaches include: enhanced communication among developers and stakeholders using a single, configured, quantified source of truth; reduced development risk due to continuous evaluation of requirements and design verification; improved system quality due to rigorous requirements traceability and testability; streamlined manufacturing processes with better supply chain management and less scrap and rework; increased productivity due to the ability to quickly evaluate the impact of changing requirements; and streamlined operations and sustainment through use of all available knowledge to optimize maintainability and extend service life of the system.

A digital engineering ecosystem for the defense industry should include having the information systems to gather and manage data; ensuring that data is sufficiently comprehensive, accurate and protected.

The key attributes of the ecosystem are supportive of government engineering capabilities that provide independent insight to government decision makers without compromising proprietary rights of industry; enable decision makers to leverage model-based systems engineering and model-based engineering to conduct mission and system analysis over the lifecycle; avoid the imposition of any specific digital engineering technologies or tools on contractors; evolve in a collaborative manner while maintaining healthy competition; and provide the ability to perform syntheses and analyses and share digital artifacts and information across diverse domains, disciplines, systems, organizations and lifecycle phases.

This, of course, will not be easy. There is a lot of change that needs to occur before digital becomes the standard for acquisition.

Some of the challenges include government data rights, intellectual property marking and protection, and contracting deliverables that use government digital engineering artifact.

Also, the digital engineering framework for collaboration must be available and authoritative across the lifecycle and address the security for different levels of classification and aggregation along with the appropriate levels of visibility and transparency. The current lack of standard operational architectures; common data, modeling and exchange standards; and the ability to trade between abstraction and fidelity in selected domains is a critical challenge.

To understand and address cultural changes, there needs to be a pragmatic narrative on the why, what and how in support of digital engineering — developed and delivered with impact and supported by use case and business case analyses.

Industry use of model-based systems engineering and model-based engineering will continue to grow and, without a strategy and a baseline architecture supported by common, consensus standards, the military will find itself in 2038 complaining about the same issue it did in 2008 — interoperability.

In addition to the workshops held at the National Defense Industrial Association on this subject, there are several association organizations that are engaged with digital engineering from different perspectives.

The systems engineering division has a committee devoted to model-based systems engineering, and digital twin/digital thread is a very important topic at its next annual conference, which is in Tampa in October.

The recent test and evaluation division conference held near Naval Air Station Patuxent River, Maryland, delved into the necessary changes to development testing and operational testing required in a digital engineering environment. The digital ecosystem enables a “shift left” to occur and a reduction in costly physical assets.

Test and evaluation could rely on digital models if they are accurately baselined to real-world conditions and results. This is analogous to software development using agile methods where testing is done early and often in incremental builds of capability. The test and evaluation division is also looking at digital environments with respect to testing in the hypersonic and cyber arenas.

The digital revolution is reshaping the development, fielding and sustainment of aerospace and defense systems. The Defense Department is at the front end of a significant journey toward a digital engineering transformation mandated by the need to maintain technical dominance over adversaries.

The keys to success require developing guidelines for ecosystem architectures and standards; connecting tools and technologies to support a digital engineering ecosystem; establishing policies to enable a public/private partnership while respecting data rights and intellectual property; moving from positional document-centric to fully digital, model-based, intentional processes; and educating and training program managers and systems engineers to lead the revolution. 

Ed Kraft is the associate executive director of research at the University of Tennessee’s Space Institute and former principal technical adviser to the commander of the Arnold Engineering and Development Center. He is an American Institute of Aeronautics and Astronautics fellow. Dave Chesebrough is vice president of divisions at NDIA, and former president of the Association for Enterprise Information.

Topics: Viewpoint, Air Power, Defense Contracting, Defense Innovation, Manufacturing

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