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Faster Onboarding: Automating Device Inte­gra­tion with AAS

Why it is
impor­tant

To save time on manual onboarding and hidden data

In many facto­ries, connecting new devices still means manual config­u­ra­tion, scat­tered docu­ments, and unclear data flows. Each inte­gra­tion requires custom effort, which slows down commis­sioning, increases the chance of errors, and makes scaling diffi­cult.

At the same time, valu­able infor­ma­tion like time series data often remains isolated, preventing oper­a­tors and engi­neers from gaining a complete view of perfor­mance or tracing issues across the life­cycle. The lack of struc­tured, system-read­able data leads to inef­fi­cien­cies, higher costs, and unnec­es­sary down­time.

Making device infor­ma­tion stan­dard­ized and acces­sible changes this: assets can be inte­grated faster, data can be shared seam­lessly, and compa­nies gain a reli­able basis for moni­toring, analytics, and digital twins.

Should
-You- care?

Yes, if device inte­gra­tion and reli­able data matter to your oper­a­tions

This is rele­vant for anyone who installs, config­ures, or manages indus­trial equip­ment. In both discrete manu­fac­turing and process indus­tries, the effort to onboard new assets or recon­nect replace­ments can delay produc­tion and intro­duce errors if handled manu­ally. At the same time, missing or frag­mented time series data makes it harder for engi­neers and oper­a­tors to verify perfor­mance, trace anom­alies, or prove compli­ance.

Different roles gain different value:

  • Oper­a­tors and main­te­nance teams save time during commis­sioning and reduce the risk of miscon­fig­u­ra­tion.

  • Engi­neering teams benefit from struc­tured, reusable data for faster inte­gra­tion.

  • Produc­tion managers get more trans­parency across equip­ment life­cy­cles.

  • Quality and compli­ance staff can access consis­tent records for audits and trace­ability.

You do not need to redesign your automa­tion system. Stan­dard­ized Asset Admin­is­tra­tion Shell submodels can plug into existing envi­ron­ments and grad­u­ally extend their use. What matters is the strategic shift: treating devices and their data as part of a connected, machine-read­able ecosystem rather than isolated objects.

In short: if you want faster onboarding, fewer errors, and trust­worthy data across the life­cycle, this is some­thing you should care about.

What we
made happen

We connected Asset Admin­is­tra­tion Shells directly with zenon and proved two things in prac­tice:

Auto­matic Asset Onboarding

    • zenon can now read the Asset Inter­faces Descrip­tion and Inter­faces Mapping Config­u­ra­tion submodels from an AAS repos­i­tory.

    • Using this, Modbus‑, HTTP- and MQTT-based devices can be onboarded auto­mat­i­cally without manual config­u­ra­tion.

    • The system imports all rele­vant inter­face details directly from the AAS, cutting inte­gra­tion time and reducing errors.

Time Series Data in zenon

  • The Time Series Data submodel was used to provide measure­ment data (e.g. 10 internal points of a sensor) directly to zenon.

  • This allows trend curves, compli­ance checks, and life­cycle moni­toring to be displayed in the automa­tion plat­form.

  • Data gener­ated during produc­tion, trans­port, or oper­a­tion becomes instantly acces­sible and struc­tured.

The outcome: a working setup where device infor­ma­tion and measure­ment data flow digi­tally into zenon through stan­dard­ized AAS submodels. Instead of static docu­ments and manual setup, we now have struc­tured, reusable, and machine-read­able inte­gra­tion.

What Submodels have been used

the team
that deliv­ered

#better
together

This setup goes beyond single use cases. By combining auto­matic asset onboarding and time series data visu­al­iza­tion, we created a shared foun­da­tion for digital device inte­gra­tion that works across different envi­ron­ments. Built on open stan­dards and real AAS submodels, it demon­strates how existing automa­tion plat­forms like zenon can connect seam­lessly with the AAS ecosystem.

The value lies in its reusability: manu­fac­turers, oper­a­tors, and system providers can take the same submodels, adapt them to their own equip­ment, and extend them with addi­tional func­tions. What started as onboarding and data visu­al­iza­tion can easily grow into cali­bra­tion records, main­te­nance history, or full digital twin manage­ment.

This is not a one-off demon­strator, but an invi­ta­tion to collab­o­ra­tion. Together we can turn frag­mented, manual processes into connected, scal­able solu­tions that benefit the entire value chain.

Inter­ested in joining or learning more?

Let’s talk

insights
and Q&A

How does auto­matic onboarding in zenon actu­ally work with the AAS?

Zenon reads the stan­dard­ized Asset Inter­faces Descrip­tion and Mapping Config­u­ra­tion submodels directly from the AAS repos­i­tory. Instead of engi­neers entering every protocol detail by hand, the system imports Modbus‑, HTTP‑, or MQTT para­me­ters auto­mat­i­cally. This removes a big source of delay and miscon­fig­u­ra­tion, making device connec­tion almost plug-and-play.

What role does time series data play in this setup?

The Time Series Data submodel feeds measure­ment values such as internal sensor points straight into zenon. Once avail­able in struc­tured form, these data streams can be visu­al­ized as trend curves, compared for compli­ance checks, or stored for life­cycle moni­toring. The effect is that produc­tion and oper­a­tional data are no longer locked away in devices but are directly usable in the automa­tion plat­form.

What if a device does not yet have an Asset Admin­is­tra­tion Shell?

For such cases, zenon can create a new AAS entry in the repos­i­tory. That means compa­nies can grad­u­ally extend the ecosystem: new devices can be regis­tered, old ones can be brought into scope, and over time the entire shopfloor moves toward a consis­tent, digital twin-ready envi­ron­ment without requiring a complete redesign of existing systems.

Beyond onboarding and moni­toring, what’s the long-term benefit?

This demon­strator proves more than just a single feature. It lays the ground­work for reusability: the same submodels that make onboarding and data visu­al­iza­tion possible can later handle cali­bra­tion records, main­te­nance logs, or even full digital twin manage­ment. In other words, today’s effi­ciency gains are only the start . The same infra­struc­ture can scale to cover broader life­cycle and compli­ance needs across indus­tries.