This year’s CIMdata PLM Roadmap and PDT conference, jointly organized with Eurostep, was fully virtual due to COVID-19. Peter Bilello, president and CEO of CIMdata, kicked off the event with a keynote presentation titled “Digital Twin, It Requires a Digital Thread” and discussed why the digital thread is essential to connecting each and every digital twin across the product life cycle.
Such conferences are particularly insightful for those interested in reviewing possible PLM definitions, discipline intersections, standards, case studies, purposes and concepts: from model-based system engineering (MBSE) to other expectations from business analytics and new technologies, such as the role of the Internet of Things (IoT) as the glue that closes the loop between enterprise platforms. Furthermore, many presentations reenforced the need for having a robust data governance approach to maximize value from digital thread investments.
With the rise of smart products, smart factories, smart buildings and smart cities, industries are gradually jumping onto the “digital” bangwagon, repurposing all things related to PLM and beyond with new digitalization jargon—primarily to take stock from new technology advances, and perhaps contributing to make the discipline more appealing to non-PLM professionals. Digitalization strongly relies on data lifecycle management principles that expand across enterprise platforms and operations.
PLM Digital Purpose: Connecting the Dots Throughout Product Development
Peter Bilello reminded the audience that one of the core principles of PLM is to connect information throughout the end-to-end product data life cycle. Enterprise data typically interconnects through multi-view bills of material (BOMs) as the lifeblood of product development, from design and engineering to manufacturing and asset management: successively as-required, as-conceived, as-designed, as-validated, as-built and as-maintained/as-serviced BOMs.
It is acknowledged that digital and physical twins will come in pairs. They converge throughout the asset life cycle as both twins mature, fueled via the enterprise data backbone. Otherwise “a Digital Twin without a Digital Thread is an orphan” (to quote Peter Bilello’s presentation). Not every model or simulation is a digital twin, especially when virtual models do not represent accurately the real entity. Twins in this context are expected to be identical, or close enough to inform one another about function and performance.
The digital thread is often referenced as an enabler of “end-to-end connectivity” and “closed-loop traceability of changes,” or in other words, data integration and process feedback loops.
- A digital twin representation relies on ongoing data feeds to keep current with its physical product, machine or whatever else that it represents.
- Ongoing data connectivity to “close the gap between virtual and physical worlds” is what the digital thread is about; without such connectivity or integration, digital models are only one-time representations and “orphans” from the associated physical parents—or, should we say, “not true siblings”?
- There is clearly more than one digital twin, as there are many virtual representations of a product or service throughout their life cycle.
- By definition, digital twins must be true surrogates or avatars of their physical equivalents to be meaningful sources of value realization.
- Digital twins are not limited to the product development cycles; they reach out to other physical assets, like factories, plants, buildings, cities, and so on.
- Digital twins, powered by the IOT as the “glue,” enable organizations to understand how products are being used in the field—creating new ways to leverage data and process insights.
During product development stages, virtual models contribute to reducing the number of physical prototypes. In later stages of the asset utilization, virtual models contribute to optimizing and generating new insights from physical products and services operations. This contributes to new opportunities and threats about how learning loops can be implemented to create value—and possibly new operating models.
Looking at the Glass as Half Full: Strengths and Opportunities from the Digital Thread
Looking at the glass as half full, Peter Bilello promoted the vision of a “truly connected environment,” one that “creates value from how products are used [and the related services] rather than from products alone.” Data governance, across data structures and enterprise integration, is becoming more and more important as there is no “one-size-fits-all” digital thread.
There are indeed multiple digital threads, each and every one of which is contextual to an organization; there are also multiple digital threads within each organization. Optimizing investments in enterprise integration was also the core topic from the keynote presentation of Marc Halpern, VP and analyst with Gartner, titled “Digital Thread: Be Careful What You Wish For, It Just Might Come True.” In his presentation, Halpern referred to “digital nets” to combine and connect multiple threads that evolve over time as organizations mature and grow inorganically through mergers and acquisitions, but also as they seek to continuously improve (and simplify?) how they operate and create value.
Looking at the Glass as Half Empty: Setting Realistic Expectations and Focusing on Business Risk Mitigation
Looking at the glass as half empty, is digital thread another synonym for connectivity or data integration? The wider or longer the thread, the more complex and critical the feedback loops. There are nevertheless clear opportunities for tighter and wider data integration; hence, integration platforms might become the next value creation differentiators, whereas PLM (and other digital technology) platforms have perhaps become commodities. If mistakes can be made when implementing PLM or enterprise resource planning (ERP) solutions, the consequences of not getting the master data alignment and integration right can have critical implications to the whole ecosystem.
Marc Halpern strongly warned about the risks of the “vendor black hole” and “enterprise architecture mess”:
- The former is a recurring theme with PLM platformization and the rise of cloud transition. Such risk is critical in the context of integration of multiple digital threads. As Marc Halpern put it: Digital thread vendor lock-in might lead to “diminished negotiation power, high implementation costs, higher cost to innovate and diminished business agility.”
- The latter is also not new to PLM; it relates to the rising complexity of platforms being integrated into the wider enterprise. It is essential to avoid “boiling the ocean” from both a PLM and integration perspective to avoid “productivity declines, cost increase, knowledge lost and accelerated obsolescence.”
Will the Digital Thread Embrace MBSE Principles to Create Business Value and Enhance PLM?
Given the rising attention that “digital” is getting, one might easily be misled to think that it is somehow new, perhaps taking over the practice of PLM entirely. Think twice. MBSE is very much rooted in the V-model (or double V-model), a key principle associated with feedback loops at the core of the product data life cycle practice.
Interestingly, Mark Reisig, director product marketing with Aras, compared the digital thread with a chess board … one that might only exist contextually and be unique to each organization. Other sponsored presentations from Siemens and PTC highlighted the need for a “simplified system engineering process” (quoting Dale Tutt, vice president of aerospace and defense industry with Siemens Digital Industry Software) and “accessing information in a simplified way” (quoting Kevin O’Brien, divisional vice president & general manager with PTC).
Effective integration is about keeping data current across a given system interface, but more importantly, allowing it to enable people to make effective data-driven decisions using processes and tools on each side of the interface. The digital thread is a means to and end: aligning digital blocks to business blocks. It is important to include the decision-making process and people themselves in the equation, both from a product development point of view as well as from the customer or consumer experience perspective.
What are your thoughts?