What happens after a rocket unintentionally explodes or a plane crashes or some other catastrophic event occurs?
Tracing critical information back from the actual unit that failed to its specific design, manufacturing and supplier data can take weeks or months and often times even longer.
The ability (or inability) to trace back through the lifecycle – and time required – can cause tens of millions in losses… or worse; customer safety issues, operational shutdowns, brand damage, regulatory actions, liability and other business damaging results.
What is the Digital Thread?
The US Department of Defense’s Glossary of Defense Acquisition Acronyms and Terms states:
“Digital Thread – An extensible, configurable and component enterprise-level analytical framework that seamlessly expedites the controlled interplay of authoritative technical data, software, information, and knowledge in the enterprise data-information-knowledge systems, based on the Digital System Model template, to inform decision makers throughout a system’s life cycle by providing the capability to access, integrate and transform disparate data into actionable information.”
Huh? Sounds more like buzz word soup than a clear explanation.
One of the many software providers jumping on the Digital Thread bandwagon asserts, “The Digital Thread refers to the communication framework that allows a connected data flow and integrated view of the asset’s data throughout its lifecycle across traditionally siloed functional perspectives.”
A “communications framework?” An “analytical framework?” Those sound like vendor tools I’m supposed to buy as opposed to describing a critical aspect of my enterprise information architecture.
OK, OK, let’s zero in on Benefits and come back to Definitions in a bit.
What Benefits does a Digital Thread provide?
Traceability in critical situations is clearly a key benefit. Others listed in papers which include the topic such as the USAF’s Global Horizons – Global Science and Technology Vision and the Manufacturing Leadership Council’s Vision 2030: Factory of the Future identify:
- Reduce development cycle time
- Quantify risk at critical decision points and avoid late defect discovery
- Optimize manufacturability, inspectability, and sustainability
- Allow product characteristics and performance to be better understood and improved throughout the life cycle
- Traceability across the life cycle
- Full Visibility + Automated Recourse
That last bullet point is important. It hints at the fact that the Digital Thread will be essential to enable the Smart in ‘smart factories’ and ‘smart connected products.’ The Vision 2030 report also insists:
“The single biggest transformation will be incorporating data from digital twins, enabled by digital threads, to build learning into multi-generational products.
“Cognitive analytics and computing techniques, which bring together natural language processing, problematic reasoning, machine learning, artificial intelligence, and other technologies, will enable production environments to self-configure, self-adjust, and self-optimize.
“But manufacturers will have to ensure they… support cognitive capabilities (with accurate Digital Threads / Digital Twins so) that (AI) can seamlessly understand and infer lessons from field deployments and build them into next-generation products.” <stuff in (parentheses) added by me for tie-back brevity>
What they’re saying is that for artificial intelligence / cognitive computing to be useful – and more importantly – to avoid misinterpretations that can lead to disastrous mistakes, you need “meaningful” connections between data in different systems.
Which brings us back to What is the Digital Thread? More importantly, What it Is & What it Is Not.
Critical Aspects of the Digital Thread
Really seems the Digital Thread is the Relationship connections between all of a product’s digital assets – and their revisions – over the course of the product’s lifecycle including – but not limited to – versions of BOMs, parts, software, electronics, CAD models, documents, requirements, process plans, service manuals, etc.
To truly be effective the Digital Thread needs “meaningful” relationships that include additional descriptive / semantic information which conveys:
- Context – What does it mean if a Part is connected to another Part? Are they part of a BOM? Or are they FFF Alternates? What does the connection mean?
- Dependency – Especially when both data items are changing over time (e.g. Fixed vs Float)
These points along with other scenario-specific descriptive information are critical to enable a true Digital Thread from my perspective, and that begs the question of “What it is Not”:
- Not just ‘Engineering to Manufacturing’ but all the way through the Lifecycle from Concept to actual Use and ultimately retirement.
- Not just ‘Mechanical CAD to CAM’ but across all disciplines including software, electronics, wire harness, hardware, requirements, etc, etc, etc.
- Not just ‘inside the 4 walls’ but out to Suppliers and into the Field.
- Not just a bunch of (meaningless) ‘point-to-point web links’ between data in disparate systems but meaningful relationships.
This last bullet is a significant topic that we’ll need to delve into in a future post.
In a systems-of-systems world where complexity and interdependencies are skyrocketing and Industrial Internet-enabled plants produce IoT products, the ability to interpret and act upon the data streaming back from the field and factories often require traceability to prior information from related revisions – Digital Thread.
Seems to me that the accuracy of Digital Thread traceability from the Digital Twin product configuration back through the lifecycle will be a necessary foundation for deriving value from the IoT.
What’s your take? Is the Digital Thread as important as I seem to think? Or is it just a ‘nice to have’ aspect of your enterprise information architecture?