Industry 4.0

Asset Administration Shell in practice

What is an Asset Administration Shell?

Industry 4.0 promises more efficient and sustainable manufacturing processes through digitalization. The foundation for this is a seamless, automatic exchange of information between systems and products. This is where the Asset Administration Shell (AAS) comes into play.

An Asset Administration Shell is a vendor-independent standard for describing digital twins. Basically, it is the digital representation of an asset; either a physical product or a virtual object (e.g., documents or software).

The AAS defines the appearance of the asset in the digital world. It describes which information of a device is relevant for communication and how this information is presented. This means the AAS can provide all important data about the asset in a standardized and automated way.

Let us take a look at a practical application to understand the benefits of an AAS:

Use case: AAS as enabler for new services

As part of the ESCOM research project, CONTACT Software collaborates with GMN Paul Müller Industrie GmbH & Co. KG to implement AAS-based component services. The family-run company manufactures motor spindles which are installed by its customers as components in metalworking machine tools and then resold.

Before the project began, GMN had already developed a new sensor technology. It enables deep insights into the behavior of a spindle and provides information on overall operation of the spindle system. The company wants to use this data to offer new, product-related services:

Certified commissioning: Before GMN ships its spindles, the components are put through a defined test cycle on the company’s in-house test bench. GMN uses the data from this reference cycle to ensure that motor spindles are installed and commissioned correctly at the customer’s facility.
Predictive services: Using the IDEA-4S sensor microelectronics, customers shall be able to continuously record and analyze operating data that provide insights into the availability and operation of the spindles. If necessary, the data can be shared with GMN, for example, for problem analysis. This saves valuable time until the machine is back up and running. In the future, GMN will be able to offer smart predictive services like predictive maintenance.

About GMN Paul Müller Industrie GmbH

GMN Paul Müller Industrie GmbH & Co. KG is a family-owned mechanical engineering company based in Nuremberg, Germany. It produces high-precision ball bearings, machine spindles, freewheel clutches, non-contact seals, and electric drives that are used in various industries. The company manufactures most of these components individually for its customers on site and sells its products via a global sales network.

How do we realize the new services?

To provide such services, companies must be able to access and analyze the sensor data of their machines. Furthermore, machines (or their components) must be enabled to communicate independently with other assets and systems on the shopfloor.

For both tasks, GMN uses CONTACT Elements for IoT. The modular software not only helps the company to record, document and evaluate the reference and usage data of their spindles. It also includes functions that enable users to create, fill and manage the AAS for an asset.

Background

During the implementation of services based on spindle operating data, GMN benefits from the cooperation with a customer. This company installs the spindles in processing machines that GMN uses to manufacture its own products. As a result, GMN can gather the operating data in-house and use it to improve the next generation of spindles.

What role does the AAS play?

For the components to exchange information in a standardized form, an AAS must be created for the spindle at item and serial number level. This is also done using CONTACT Elements for IoT. The new services are mapped in a so-called AAS metamodel. It serves as a “link” to the service offers.

AAS and submodels

The AAS of an Industry 4.0 component consists of one or more submodels that each contain a structured set of characteristics. These submodels are defined by the Industrial Digital Twin Association (IDTA), an initiative in which 113 organizations from research, industry and software (including CONTACT Software) collaborate to define AAS standards. A list of all currently published submodels is available at https://industrialdigitaltwin.org/en/content-hub/submodels.

In CONTACT Elements for IoT, GMN can populate the AAS submodels with little effort. The platform includes a widget developed as a prototype during the research project. It provides an overview of which submodels currently exist for the asset and which are available but not yet created. Through the frontend, users can jump directly to the REST node server and upload or download submodels (in AAS/JSON format).

During the implementation of data-driven service offerings, GMN focuses on the submodels

Time Series Data (e.g., semantic information about time series data)
Digital Nameplate (e. g., information about the product, the manufacturer’s name, as well as product name and family),
Contact Information (standardized metadata of an asset) and
Carbon Footprint (information about the carbon footprint of an asset)

Filling the submodels is simple. This is demonstrated by the module Time Series Data. During the reference run of a motor spindle on the in-house test bench, the time series data is recorded by CONTACT Elements for IoT. The platform automatically transfers this data to the AAS submodel of the motor spindle being tested. At the same time, the platform creates a document for the reference run. This allows GMN to track its validity at any time and make it available to external stakeholders.

New services on the horizon

Using Asset Administration Shells allows GMN to realize its service ideas. This currently concerns the commissioning service and automated quality assurance services.

By analyzing the spindle data, the company can identify outliers in the operating data and make suitable recommendations for action. For example, different vibration velocities indicate an incorrect installation of the spindle in the machine or that time-varying processes are occurring. The analysis can also be used to provide insights about anomalies in operating behavior.

Dashboards in CONTACT Elements for IoT increase transparency. They provide GMN with all relevant information about the spindles on the test bench, from 3D models to status data. This overview is extremely valuable, particularly for quality management.

An AAS in our software Elements for IoT.

Summarized

Asset Administration Shells are vendor-independent standards for describing digital twins. They are among the most important levers for implementing new Industry 4.0 business models, as they enable communication between assets, systems, and organizations. The example of GMN demonstrates the practical benefits of the AAS. The company uses it to design new, product-related services based on information from the AAS of its products. GMN can successively improve these services by continuously analyzing operating data in CONTACT Elements for IoT.

Digital Operational Excellence in Practice

Operational Excellence is the ability of a company to continuously improve its value chain in terms of efficiency and effectiveness. It is the ultimate discipline in the manufacturing industry. Companies face constant pressure to optimize their manufacturing processes and increase productivity. However, there are several hurdles to overcome, such as lack of coordination, paper-based processes, and a multitude of labor-intensive manual activities.

For sustainable production optimization, digitalization through Manufacturing Operations Management (MOM) systems is a fundamental cornerstone. It’s crucial that IT activities go hand in hand with the design of processes and methods, and their integration into the shop floor organization, which often faces challenges such as limited resources, skill gaps, and restricted operational capacity.

Based on our project experiences, we have summarized the following typical steps for you to achieve increased OEE (Overall Equipment Effectiveness) and EBIT:

Qualification and involvement

Early involvement of employees as ambassadors significantly contributes to the success of the project. Therefore, the project team and leadership are trained at the project’s outset. This fosters a shared understanding and ensures sustainable integration of activities. Additionally, to assess the coverage of process threads with the standard software and to create mock-ups for the target system as needed, key users must be involved early on.

Equipment and Asset Management

A simple system solution without smart machine integration often generates significant benefits in the initial phase of the project. This is particularly true for maintenance. Asset management documents the condition of the equipment ‘as maintained.’ This allows similar groups of systems to be managed in a standardized manner and to identify deviations (benchmarking). Further potential lies in the standardized spare parts management.

Cross-System Data Logistics

The next step typically involves the integration into company-wide data logistics. To achieve this, leading systems and consumers are identified and matching is designed at their interfaces. Companies should not underestimate this design phase, which is often the most challenging part of establishing a stable data logistics. In terms of technical implementation, certified interfaces for standard systems like SAP are preferable, as individual approaches are often maintenance-intensive and not future-proof.

Optimization of Shop Floor Control

Once order data (from upstream systems) and equipment are available in the MOM system, the optimization of processes surrounding production and shop floor control continues: Error-prone Excel tools are replaced, planning consistency is enhanced, and manual efforts are reduced.

For instance, through effective shop floor data collection (SFDC), operators can report causes and quantities of defects, improving the information basis for control. By digitally providing manufacturing documents, manual efforts and sources of errors can be reduced. All of these measures significantly increase the acceptance of digitally available information among operators.

Machine Integration and Data Preparation

The integration of machines and equipment into the MOM system (Machine Data Acquisition) creates a comprehensive picture of the current manufacturing situation. This enables companies to implement condition-based and predictive maintenance measures. Another particularly important aspect is the implementation of a cross-functional energy management on this basis, as the system provides data for calculating the CO2 footprint throughout the entire production chain.

Digital Shop Floor Management

Digital Shop Floor Management (SFM) serves as a central interface between IT and process optimization. SFM is the key lever for continuous improvement in production and is methodically supported by cascading rule meetings. This allows insights and issues to be visualized and addressed from the workshop floor to the site level, from OEEs and loss reasons at a single facility in one shift to the impact on operational performance and site EBIT.

Stabilizing and Improving OEE

The focus on improving OEE often revolves around reducing downtime and reasons for disruptions. This is based on the consolidated overview from Machine Data Acquisition (MDE) and Shop Floor Data Collection (BDE), identifying measurable causes of losses for each machine. A typical insight, applicable to many companies, is that OEE losses are not solely due to equipment failures but often stem from organizational issues. Therefore, alongside initiatives such as setup workshops, machine cleaning measures, and employee training, projects in office areas are also of significant importance (e.g., order processing, planning/scheduling, and product development/master data).

Enterprise-wide Benefits

Digitization through MOM software establishes a foundation for companies to optimize their production sustainably. In typical cases such as in medium-sized mechanical engineering, improvements of the average OEE across all machines by more than 10 percentage points and an increase in site EBIT by more than 2 percentage points are quite realistic. As long as there are sufficient orders, increased productivity is immediately reflected in higher EBIT. At the same time, improved process quality and responsiveness have a positive impact on customer relationships.

Asset Administration Shell as a catalyst of Industry 4.0

“Country of poets and thinkers” or ” Country of ideas”: Germany is proud of its writers, scientists, researchers, and engineers. And of its meticulous bureaucracy, which aims for absolute precision in statements or indications. Combined, this often results in awkward word creation when naming technical terms. A current example of this is the “Verwaltungsschale” (literally: administration shell), whose innovative potential and central relevance for Industry 4.0 are not immediately apparent.

What is an Asset Administration Shell?

“Verwaltungsschale” is not a dusty administrative authority, but the very German translation of the English term “Asset Administration Shell” (AAS). The AAS is a standardized complete digital description of an asset. An asset is basically anything that can be connected as part of an Industrie 4.0 solution (for example, plants, machines, products as well as their individual components). It contains all information and enables the exchange and interaction between different assets, systems, and organizations in a networked industry. Therefore, it is pretty much the opposite of a sluggish authority and currently the buzzword in digital transformation.

As with many new topics, definitions of AAS vary and are quite broad. From very specific like the Asset Administration Shell as an implementation of the digital twin for Industry 4.0 to the loose description of AAS as a data plug or integration plug for digital ecosystems.

I prefer the representation of the AAS as a metamodel for self-describing an asset. With this metamodel, further models can be generated to provide collected information. Through the use of software, these models are then “brought to life” and are made available to others via interfaces.

Concept and usage of the Asset Administration Shell

As a digital representation of an asset, the AAS provides information or functions related to a specific context through its submodels. Examples include digital nameplates, technical documents, the component or asset structure, simulation models, time series data, or sustainability-relevant information such as the carbon footprint. The information is generated along the various phases of the lifecycle, and it depends on the specific value network which asset information is of importance. Thus, submodels are initially created in certain lifecycle phases, specified and elaborated in subsequent phases, and enriched or updated with information in the further process. Thereby, the AAS refers to either a very generic (type) or a very concrete (instance) representation of an asset.

As assets change over time (as-defined, as-designed, as-ordered, as-built, as-maintained), so does the Asset Administration Shell. Thus, multiple AASs can exist for the same asset over the lifecycle. In order to utilize the information in the AAS within its value network, it needs to be accessible. Access is usually given via the Internet or via the cloud (repository-deployed AAS). In intelligent systems, the management shell can also be part of the asset itself (asset-deployed AAS).

Information can be exchanged in various ways. Either via files, so-called AASX files (AAS type 1), via a server-client interaction such as RestAPI (AAS type 2) or via peer-to-peer interaction (AAS type 3), in which the AASs communicate independently using the so-called I4.0 language and perform tasks cooperatively.

While type 1 and 2 take a passive role in the value network and are more likely to be used with repository-held AAS, type 3 describes an active participation in the value network and is more likely to be used with asset-held AAS running smart products.

Common standards connect!

No matter what type of Asset Administration Shell you choose: Important is that the recipient and the provider speak the same language. To achieve this, the exchange of concrete information must be standardized. Considering the amount of different industries, scenarios, assets, and functions, this is an immense number of submodels that need to be standardized. Organizations and associations such as the Industrial Digital Twin Association (IDTA), formed by research institutes, industrial companies, and software providers, are tackling this mammoth task. The rapidly growing number of members as well as the lively exchange at trade fairs and conferences among each other illustrate the potential for the industry. It is important not to leave SMEs behind, but to involve them in the standardization work in the best possible way.

Conclusion

The Asset Administration Shell is at the core of successful Industrie 4.0 scenarios. It enables manufacturer-independent interoperability and simplifies the integration of all types of assets into a collaborative value network. It increases efficiency within production processes by providing complete transparency of the real-time status of each asset. And it also offers a comprehensive security concept to protect the data. Within a very short time, the AAS has thus transformed from a theoretical construct to a real application in practice. Together with partners from research and industry, we are working within the ESCOM and Flex4Res research projects to make it usable on an industrial scale.

AAS in practice

In CONTACT Elements for IoT, you can create, manage and share asset administration shells. Our blog post ‘The asset administration shell in practice’ explains how companies benefit from this.