Asset Administration Shell Generation and Usage for Digital Twins:

A Case Study for Non-destructive Testing

Fatih Yallıç

, Özlem Albayrak

and Perin Ünal

Research and Development, TEKNOPAR, Teknopark Ankara 224. Street, F111, Ankara, Turkey

Keywords: Asset Administration Shell (AAS), Industry 4.0, International Data Spaces (IDS), Industrial Data Space (IDS),

Digital Twin, Interoperability, None Destructive Testing (NDT)

Abstract: In a real manufacturing site, containing non-destructive testing machinery components and sensors, we have

implemented and validated Asset Administration Shell, using different tools and technologies. The tools

included emerging technologies-related tools, such as Administration Shell IO, Eclipse BaSyx, and low code

programming software for event-driven applications, namely Apache StreamPipes and Node-RED. We have

also developed International Data Spaces connectors for data exchange using previously created Asset

Administration Shells. All of the implementations in the case study have been implemented by the same

developer, the first author, while the developed outputs have been verified and validated by different various

testers. In this paper, we present the emerging digital twin technologies, and share different solution

architectures using these technologies for the purpose of secure, standard and interoperable digital twin

solutions, and data exchange between different International Data Spaces connectors. We conclude that the

presented designs are easy to implement. We found Admin Shell IO to be easier to use than the Eclipse BaSyX.

Our future studies will contain the use of Fraunhofer Advanced Asset Administration Shell Tools for digital

twin development in the same environment, and a comparison of the implementations using different

methodologies and tools.

1 INTRODUCTION

With the evolution of technology, changes in smart

manufacturing and society are accelerating at

unexpected paces (Boss, et. al. 2020). Industry 4.0

brings new challenges regarding the automatization

of IoT networks to perform information exchange in

a timely, reliable and uniform way (Alonso, et. al.

2018). Digital twins are known to be key enables for

various IoT and Industry 4.0 use cases (Boss, et. al.

2020, Albayrak and Ünal, 2020, Unal, et. al., 2022).

IoT focuses on connecting physical devices to the

internet, and collecting telemetry data, while Digital

Twins focus on organizing the collected data and

representing it in a standard way to enable the

application of Artificial Intelligence and business

rules on this data (Jacoby, et. al, 2022). Internet of

Things (IoT) devices could utilize communication

https://orcid.org/0000-0001-8060-125X

https://orcid.org/0000-0001-9517-3227

https://orcid.org/0000-0003-1357-2430

protocols compliant with Industry 4.0 (such as

MQTT, REST, and AMQP).

Without their interoperability, integrating all of

these protocols with various data structures would

require significant effort, and their potential would

not be fully exploited (Pribiš, et. al., 2021). Plattform

Industrie 4.0 made interoperability one of its strategic

fields for 2030 (Boss, et. al. 2020). Interoperability

enables cooperation and open ecosystems that permit

plurality and flexibility. In order to realize

interoperability, standards, decentralized systems,

integration, and a uniform regulatory framework, are

needed (14 in Boss, et. al. 2020).

Asset Administration Shell appears to be the key

concept of Platform Industrie 4.0 in order to enable

interoperability. The AAS can directly be adopted to

implement Digital Twins. As a result, all industries

may benefit from an open and standardized meta-

model, standardized data models with homogenized

Yallıç, F., Albayrak, Ö. and Ünal, P.

Asset Administration Shell Generation and Usage for Digital Twins: A Case Study for Non-destructive Testing.

DOI: 10.5220/0011561400003329

In Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics (IN4PL 2022), pages 299-306

ISBN: 978-989-758-612-5; ISSN: 2184-9285

299

semantics and standardized APIs and infrastructure

services.

It is also a fact that Industry and Non-Destructive

Evaluation (NDE) are growing together with the

fourth industrial revolution. It will eventually lead to

improved awareness of NDE (Vrana, et.al. 2021).

This article aims to implement the key emerging

technologies regarding Digital Twins and apply them

in a real manufacturing site’s non-destructive testing

environment. The technologies validated are AAS

and IDS.

The organization of the rest of the paper is as

follows: Section 2 presents background information

related to the emerging technologies that are

associated with Digital Twins. The technologies/tools

used and presented in this study are Asset

Administration Shell (AAS), Eclipse BaSyx and

International Data Spaces (IDS). Section 3

summarizes the case study conducted by describing

the environment of the case study and the work

performed by using the already briefed technologies

and tools. Finally, Section 4 concludes the study, and

presents future research to be conducted

2 BACKGROUNDS

Being the digitalization of manufacturing, Industry

4.0 integrates processes, devices, workers, products,

and all other relevant assets in one unified digital

system, and defines the domain of smart

manufacturing (Eclipse BaSyx). For Industry 4.0, the

term asset refers to any object that has value for an

organization. Assets in Industry 4.0 can be a

production system, a product, a software installation,

intellectual properties or human resources (AAS,

2022).

Assets have a logical representation in the

"information world", and they are managed by

information technologies systems. Hence, an asset

has to be identified as an entity, has a specific state

within its life, has communication capabilities, is

represented by means of information, and is able to

provide technical functionality. This logical

representation of an asset is called Administration

Shell (AAS, 2022). The combination of asset and

Administration Shell forms the so-called Industry 4.0

Component. In international papers, the term smart

manufacturing is also used for the term Industry 4.0.

2.1 Asset Administration Shell

The Asset Administration Shell (AAS) is the

standardized digital representation of the asset, and

also is an important element of the interoperability

between the applications managing the

manufacturing systems. AAS proposes a standardized

electronic representation of industrial assets enabling

Digital Twins and interoperability between

automated industrial systems and Cyber-Physical

Systems (CPS) (Iñigo, et. al. 2020). AAS, the concept

was introduced to provide data and information in a

standardized, and semantically described manner, in

order to enable interoperability and easy interaction

(Fuchs, et.al. 2019). Thus, AAS is considered as

being one of the key components of Industry 4.0

(Tantik and Anderl, 2017a, Bader and Maleshkova,

2019, Marcan, et. al., 2018, Ye, et. al., 2021).

AAS needs to provide a minimal and sufficient

description according to the different application

scenarios in Industry 4.0 (AAS, 2022). Different

standards, consortium and manufacturer

specifications can contribute to this definition.

Capturing the information about the AAS itself, AAS

can be taken as the digital representation or Digital

Twin of the Asset (Bader and Maleshkova, 2019).

The AAS is composed of a series of sub-models

(AAS, 2022). Each of these sub-models represents a

different aspect of the asset under consideration. The

sub-models may contain a description relating to

safety or security and also outline various process

capabilities such as assembling and process control.

AAS does not prescribe what content it contains.

Content is modelled by means of sub-models.

Implementation of the Administration Shell security

has to be together with the implementation of other

components. Each sub-model of AAS contains a

structured quantity of properties that can refer to data

and functions. A standardized format based on IEC

61360-1/ ISO 13584-42 is envisaged for the

properties. Data and functions may be available in

various complementary formats. The properties of all

the sub-models result in a constantly readable

directory of the key information of the Administration

Shell.

In order to enable binding semantics,

Administration Shells, assets, sub-models and

properties must all be identified. Global identifiers

that can be utilized are IRDI (e.g. in ISO TS 29002-

5, ECLASS and IEC Common Data Dictionaries) and

URIs (Unique Resource Identifiers, e.g. for

ontologies). It should be possible to filter elements of

the Administration Shell or sub-models according to

different given views.

There are three types of AAS specified:

Type 1 or Passive AAS is a static file serialized as

JSON, AXML or AASX. In order to exchange

information, the file needs to be passed by manually.

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Type 2 or Reactive AAS is a software component

where information exchange is realized automatically

by means of external software that communicates

with the AAS by means of API utilization. Finally,

Type 3 or Proactive AAS is a software component

that supports communication via I4.0 languages,

where information exchange is realized via direct

communication among AASs (Jacoby, et.al., 2022).

Every AAS must be secure (Boss, et. al. 2020).

Access permission rules can be defined to describe

the permissions an authenticated subject has on which

object.

Tantik and Anderl wrote the potential of AAS for

Service Oriented businesses, and concluded that

future use cases which include applications for

monitoring and remote control of the entity would not

be challenging (Tantik and Anderl, 2017a). The

authors also stated that with AAS using a

standardized external interface, seamless

interoperability would be possible. Mohr, et. al.

conducted a case study with AAS to present

interoperable digital twins in the IIoT system (Mohr,

et.al., 2019).

A semantic AAS was developed (Bader and

Maleshkova, 2019). Information provided by an AAS

can be adopted during the whole life cycle of a

production system (Cavalieri and Salafia, 2020). The

authors presented the use of AAS metamodel in order

to represent an IEC 61131-3 program and its

relationships with the real plant controlled (Cavalieri

and Salafia, 2020). AAS integrated with PLM/ALM

was demonstrated (Deuter and Imort, 2020).

While some researchers presented a methodology

of AAS implementation into an embedded system,

showing dramatically reduced system requirements

(Pribiš, et. al., 2021), and Casado and Eichelberger

(2021) presented resource monitoring with

micrometer and AAS. Park, et. al. 2021, proposed

Virtual REpresentation for a DIgital twin application

(VREDI): an asset description for the operation

procedures of a work-center-level digital twin

application.

Having briefed what AAS is, and provided an

overview of some of the ASS related studies

conducted, the next subsection list two of the AAS

tools that are utilized in the case study:

Administration Shell IO, and Eclipse BaSyx. The

selection of the tools was based on the authors’

subjective estimation of the tools’ level of recognition

in the community and the projects’ maturity levels.

2.2 AAS Tools

The top-level project “Digital Twin” of the Eclipse

Foundation is the home of many projects that are

related to the AAS (Eclipse Digital Twin, 2022). The

Eclipse Digital Twin Top-Level Project provides a

space for open-source projects to produce

implementations, and increase the adoption of

solutions, prototypes and supporting software to build

and consume information from digital twins (Eclipse

Digital Twin, 2022). The Top-Level Project supports

the ecosystem orchestrated by the Industrial Digital

Twin Association (IDTA) (Eclipse Digital Twin,

2022).

As stated by Tantik and Anderl (2017b), the

Industry 4.0 components can be enabled to manage

the production process autonomously, and additional

applications will be implemented into the AAS to

increase their functionality.

Within the scope of this study, developments have

been conducted using Admin-Shell-IO and BaSyx

open-source projects. As low-code software

development tools Apache StreamPipes and Node-

RED have been utilized (Apache StreamPipes, Node-

RED).

2.2.1 Admin Shell IO

Admin Shell IO offers software to create AAS and

display the generated AAS on the UI screen. The

Admin Shell IO software is composed of: AASX

Package Manager, and AASX Server. The Eclipse

AASX Package Explorer application of Admin Shell

IO is used to create and view AAS. While, the AASX-

Server application keeps the AAS that is generated by

the AASX-Server Package Manager on a server,

provides the visualization of the AAS, sub-model and

sub-model elements by means of the UI screen. UI

provides ease of use for Admin Shell IO.

The Eclipse AASX Package Explorer is an open-

source browser and editor for creating AASs as .aasx

packages. The Eclipse AASX Package Explorer is a

tool with a graphical user interface aimed at

experimenting and demonstrating the potential of

AASs targeting the different levels of users, ranging

from tech-savvy to less technically-inclined users.

The Eclipse AASX Package Explorer includes an

internal REST server and OPC UA server for the

loaded file.AASX format (Eclipse AASX Package

Explorer, 2022). The Eclipse AASX Package

Explorer supports the XML and JSON serialization of

the AAS. Export formats for AutomationML or

server generation for OPC UA, and BMEcat are also

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provided by the Eclipse AASX Package Export. New

features are added continuously to the software.

2.2.2 BaSyx

BaSys 4.0 defines a reference architecture for

production systems that enables the transition to

Industry 4.0. Eclipse BaSyx is the BaSys open source

project at the Eclipse Foundation (Eclipse BaSyx,

2022, BaSyx/ WhatIsBasyx, 2022).

Eclipse BaSyx™ implements an open-source

Industry 4.0 middleware that supports the digitization

of production environments (Eclipse BaSyx, 2022).

Essential components include the AAS as the

foundation for the development of digital twins, a

registry component, persistency providers, and

several container applications that simplify the

creation of common Industry 4.0 applications, such as

dashboards (Eclipse BaSyx, 2022).

Being another open-source implementation for

the AAS, BaSyx provides software development kits

for commonly used programming languages: C++,

C# and Java (AAS, 2022).

BaSys 4.0 addresses the changeability of

production processes as one major goal of Industry

4.0. Changeable production addresses unplanned

changes in production processes. Changing a

production requires (manual) intervention with the

production line. The major goal of BaSyx is to reduce

the resulting downtime to a minimum (BaSyx/

WhatIsBasyx, 2022).

BaSyx components are structured into four layers:

The field level contains automation devices, sensors,

and actuators without a specific BaSys conforming

interface. The device-level contains automation

devices that offer a BaSys 4.0 conforming interface.

Bridging devices that implement BaSys 4.0

conforming interfaces for field devices that do not

provide a conforming interface by themselves are part

of the device level as well. The middleware level

consists of re-useable Industry 4.0 components that

implement required generic, and plant-independent

capabilities for Industry 4.0 production lines.

Registry and Discovery services, protocol gateways,

and AAS providers reside on the middleware level.

Finally, the plant level contains high-level plant

components that manage, optimize, and monitor

production (BaSyx/ WhatIsBasyx, 2022,

Basissystem, 2022).

Eclipse BaSyx includes: Server component, the

Registry component and Java SDK (Implementing

the Industrie 4.0, 2020). The BaSyx Industry 4.0 SDK

encapsulates the BaSyx interface and communication

with APIs. It enables the development of Industry 4.0

components and the integration of devices and

applications into Industry 4.0 environments.

2.3 Industrial Data Spaces

With the wide application of digitalization, data

become of most importance in many domains, and

manufacturing is not an exception (Alonso, et. al,

2012, Nast, et. al, 2021). EC is constantly

encouraging governmental-business data sharing for

many topics, and EU dataspaces are commonly

requested and used for various reasons (Piest, et. al.,

2022).

The main objective of International Data Spaces

(IDS) is to support organizations of any type to enjoy

the benefits of digitalization without increasing their

risks (Uslander and Teuscher, 2022, Niskanen, 2022).

IDS was created in a research project involving

multiple Fraunhofer institutes (Alonso, et.al. 2018).

The Industrial Data Space Association (IDSA) aims

at continuous development, exploitation and

sustainability of the IDS (Alonso, et. al. 2018).

IDS offers participants the to exchange secure and

trusted data for greater benefit while maintaining their

data control (Nast, et. al., 2021, Niskanen, 2022).

Within the context of IDS, IoT devices are only data

providers. On the other hand, a data consumer

connects to a connector to retrieve IoT data (Nast, et.

al. 2021).

Industrial Data Space Reference Architecture

Model (IDS-RAM) was developed in order to achieve

a reliable exchange of data between organizations and

platforms that are developed by different vendors

(Gan, et. al. 2021). IDS-RAM emphasizes technical

and organizational security, integrity and authenticity

of data transactions for sovereign data exchange

(Wortel, et. al. 2020). The standards materialize in the

IDS-RAM and DIN SPEC 27070:2020-03 (2020)

define methods for secure data exchange between the

various IDS connectors (Gan, et. al. 2021, Barnstedt,

et. al., 2021).

Alonso et. al and Arcentales et. al. implemented

IDS structure-related components using FIWARE

(Alonso, et. al., 2018, Arcentales, et. al. 2020).

Digital Twins play critical roles in many sectors,

hence, data exchange across company borders

becomes more and more important resulting in

interoperability, transparency and openness being key

success factors. IDS has an important role in these

factors (Curry, et. al., 2021). Non-destructive systems

have high potential utilization for digital twins.

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3 THE CASE STUDY

This section presents the environment that has been

used to conduct the case study. The section also

presents the associated work performed by using

different tools and technologies that are related to

AAS and IDS generation and utilization at the real

manufacturing site’s testing facility. When

implementing an AAS for non-destructive testing, the

assets modeled are special.

3.1 Case Study Environment

The implementation of the AAS in real industrial

scenarios is not common (Iñigo, et. al. 2020).

However, the work associated with this case study has

been conducted at a real manufacturing plant. The

plant produces spirally welded steel pipes. The case

study was performed on the Non-Destructive Testing

(NDT) machinery of the plant where X-Ray

technology is being utilized for testing purposes.

The AAS has been implemented by integrating an

NDT ecosystem with X-Ray machinery and a sensor.

The implementation in this case study facilitates the

utilization of the X-Ray machinery components with

sensor data or machines in a real steel pipe

manufacturing plant, validating the AAS use in a

manufacturing environment for non-destructive

testing scenarios.

3.2 Work Performed using Admin

Shell IO

In this study, using the AASX Package Manager

software, AAS has been created for four different

components of an X-Ray machinery: X-Ray

Generator, X-Ray Tube, X-Ray Motor Execution, and

X-Ray Motor Rotation.

The created AASs have been exported in .aasx

format to be uploaded to AASX Server. Exported

files have been uploaded to AASX Server. When

AASs are uploaded to the server, data can be written

and read from outside with REST/API.

In this application, the data from MQTT has been

written to AAS with a Python script. Thus, AAS has

been created by Admin Shell IO and data including

dynamic sensor data can be written and read.

In addition, a data source has been written on

Streampipes, which reads the data from the AASX

Server and transfers it to the Apache StreamPipes

environment. MQTT incoming data is written to

AAS, and AAS data is transferred to Apache

StreamPipes thanks to the Apache StreamPipes data

source (Apache StreamPipes, 2022). Enabling low

code, even close to no-code, application

development, Apache StreamPipes is a self-service

IIoT toolbox to enable non-technical or novice users

to connect, analyze and explore IoT data streams. The

architectural diagram of the study is given in Figure

Figure 1: The architecture using Admin Shell IO.

3.3 Work Performed using Eclipse

BaSyx

Using Eclipse BaSyx and Node-RED (Node-RED,

2022), architecture has been designed and

implemented based on AAS.

Built on Node.js, Node-RED is a programming

tool for bringing APIs, hardware and online services.

The generated architecture is shown in Figure 2.

Figure 2: The architecture using Eclipse BaSyx.

An AAS has been created for the X-Ray machine

using the Eclipse BaSyx Java SDK, and a sensor has

been added as a Sub-model. The generated X-Ray

AAS has been registered in the Eclipse BaSyx AAS

Registry component.

After creating X-Ray AAS, and registering to the

Registry using Eclipse Basyx Java SDK, a proxy for

AAS was created using Basyx Java SDK. Thanks to

AAS Proxy; AAS, the sub-model, and the AAS data

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can be accessed with the REST API. For example, the

Node-RED module receives data by submitting a

GET request to this Proxy.

In this case study, the following actions have been

performed:

• An AAS with Eclipse BaSyx has been

generated,

• The generated AAS has been registered

using BaSyx Registry Component, and

• A proxy for HTPP API has been created.

A new node named “Get AAS xray” has been

developed for the Node-RED tool using the created

API. The developed node sends a request to the proxy

asking for AAS data, and the sensor data is retrieved

in response to the request. Node-RED flow and

sample output data developed using the Get AAS

xray node are shown in Figure 3.

Figure 3: Data retrieval using the generated API in Node-

RED.

3.4 Work Performed using IDS

In this study, International Dataspace Connector

(IDS) has been installed on two different hosts. One

of the connectors has been configured as a provider,

and the other has been configured as a consumer. The

provider aims to send the "temperature" sensor data

retrieved from the previously created AAS dynamic

data as the data to be installed and sent to the

computer with the IP address 192.168.a.xx. The

consumer, on the other hand, has been installed on the

test server with an IP address of 192.168.a.yy. The

consumer requests data from the provider.

As a result of the studies conducted with IDS

connectors, data transfer between different servers

has been achieved. The provider connector has been

used as a data provider for the consumer connector.

The provider connector reads data that are received

from the AAS server.

The architecture that was used to send the AAS

data to the IDS consumer connector using an IDS

provider connector is presented in Figure 4.

Figure 4: The architecture using IDS connectors.

4 CONCLUSIONS AND FUTURE

WORK

In this case study, we have designed and implemented

different technical solutions using emerging digital

twin technologies/tools to generate AAS and IDS in a

real manufacturing environment. The Admin Shell

IO, Eclipse BaSyx, and IDS connectors have been

developed and used together with Apache

StreamPipes and Node-RED. The developments have

been verified and validated by testers.

Digital twins are beneficial solutions for non-

destructive testing systems. Being one of them, X-

Ray testing systems has potential dangers, hence, it is

suggested to use digital twins for these systems. To

the best of our knowledge, this study is the first study

conducting such a case study on non-destructive

testing machinery using X-Ray technology in steel

pipe manufacturing.

We conclude that with the current maturity level

of the tools, it is easy to implement AAS and IDS for

digital twin interoperability and to enable secure data

exchanges between different organizations. In our

comparison of the tools based on the ease-of-use

attribute, we found that the Admin Shell IO is easier

to use than the Eclipse BaSyx, because it has UI for

AAS management and it generates JSON.

In the future, we will continue our studies on the

generation of AAS using Fraunhofer Advanced Asset

Administration Tools (FA

ST). Up on successful

completion of an AAS using FA

ST, we aim to

compare and contrast different technologies/tools,

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designs, and our experiences and lessons learned as

part of our AAS and IDS development studies.

ACKNOWLEDGMENTS

This research was partly funded by the H2020

COGNITWIN project and by the ITEA

MACHINAIDE project. The COGNITWIN project

has received funding from the European Union’s

Horizon 2020 Research and Innovation programme

under Grant Agreement No. 870130, and The

MACHINAIDE project has received funding under

the ITEA 3 Programme with project No. 18030.

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