Digital Twin

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.

Evaluating sustainability with the green digital twin

On January 5, 2023, the Corporate Sustainability Reporting Directive (CSRD) came into effect – but what exactly does that mean? The European Parliament adopted this regulation as a significant step within the European Green Deal framework of 2019. The ambitious goal: a carbon-neutral EU by 2050 – and thus the first carbon-neutral continent in the world.

CSRD and ESRS: challenges in reporting

The classification is based on environmental, social, and governance (ESG) criteria according to the EU taxonomy. Each of these three areas encompasses different guidelines and regulations. The CSRD specifically addresses environmental aspects and obliges companies across industries to act more sustainably. The European Sustainability Reporting Standards (ESRS) further specify how these obligations should be reported.

The challenge lies in recording and calculating the required environmental data, such as pollutant emissions, in accordance with ESRS KPIs. The question is: How can this data be collected efficiently and accurately?

Efficient data collection for sustainability

Environmental databases can support sustainability reporting, for example, the database for process-oriented basic data for environmental management instruments (ProBas) provided by the German Environment Agency (Umweltbundesamt, UBA).

The digital twin plays a crucial role as a useful helper. As a digital replica of products, machines, or components, it offers a comprehensive solution to the challenges of data collection in the context of the CSRD. By fully digitalizing the product passport, relevant data can be compiled throughout the entire product lifecycle. This enables both efficient data collection and transparent data sharing along the entire value chain.

From individual parts to the overall picture

The digital twin allows to consolidate information from environmental databases, ERP, MES, and material data management systems. Based on this data, the environmental impact of each component can be assessed with the Life Cycle Assessment (LCA) method. Taking a bicycle as an example, this includes the handlebar, fork, frame, saddle, pedals, and the two wheels with tires. The LCA metrics can be recorded for single components and the entire product. These individual parameters can be used to determine the carbon footprint across the entire value chain of the bike.

This data also forms the basis for the bike’s digital product passport. By fully digitalizing the product passport, the calculated environmental data can be easily shared, for example, with retailers or consumers.

Green digital twin for the aerospace industry

In the industrial sector, the aerospace industry is particularly affected by the CSRD. As part of the PredictECO research project, CONTACT Software is working with partners from science and industry on a green digital product twin that meets the new requirements. This includes the obligation to provide evidence in the form of a digital Lifecycle Data Sheet (LDS), which documents the materials and processes used down to the smallest detail. The goal is to create a comprehensive digital twin that contains all the necessary manufacturing information for sustainable production according to the requirements from the LDS and can provide them in a standardized digital form.

Outlook

The digital twin already proves to be a field-tested solution to meet the CSRD requirements of the CSRD. Collecting environmental data throughout the entire product lifecycle not only enables efficient reporting but also contributes to creating sustainable value chains. Take advantage of the opportunities the green digital twin offers to elevate sustainability in your company to a new level.

For more information on the green digital twin, read this article on the CONTACT Research Blog.

Achieving digital service excellence in three steps

The benefits of a strong service offering

Service is an anchor of stability in the machinery and plant engineering sector during times of global crises. After-sales revenues are less susceptible to external developments and economic fluctuations compared to new plant business. Additionally, their higher profit margins stabilize companies’ cash flows and mitigate risks. Moreover, an attractive service offering provides a clear competitive advantage in global markets.

According to McKinsey, customers can expect a longer product lifespan from manufacturers with corresponding maintenance contracts since no one knows the equipment better than the manufacturers themselves. Regular after-sales touchpoints deepen customer relationships and offer recurring sales opportunities, making it easier for machinery and plant manufacturers to understand their customers’ problems and resolve them with the appropriate service offerings.

The 2020 Customer Service Benchmark by the German Mechanical Engineering Industry Association (VDMA) shows that many companies in the machinery and plant engineering sector have recognized these opportunities and are expanding their services. While at the time of the last major VDMA study on this topic four years ago, only about 61% of companies offered maintenance contracts and generated around 20% of their revenue from services, an increase in these values can be expected in the next survey.

This places us in the midst of a market development that will accelerate in the coming years. Technological progress also contributes to this: the Industrial Internet of Things (IIoT) allows service business to be optimized on a customer-specific basis using data from the product’s operation.

In the future, it will become more important but also easier for machinery and plant manufacturers to increase the maturity level of their service. The following maturity model helps you assess where your company stands on the road to service excellence.

A Maturity Model for Service

Companies with low service maturity handle customer inquiries exclusively reactively. Such processes take a long time because they are still partly processed with paper forms, and searching for the required information is a tedious routine activity that does not generate value. If inquiries via email or phone are not digitally collected, this complicates the structured and prompt processing of service cases. In the worst scenario, inquiries get lost in email inboxes or remain unprocessed during an employee’s vacation because no one has insight into the current status of communication.

Digital Service Management

Digitalizing service processes is the first step to increasing internal efficiency. Companies can use a CMS (Customer Service Management) tool to manage delivered products. Services are planned and documented digitally, resulting in a service logbook for each customer and asset. Incoming customer inquiries via email or telephone are automatically converted into tickets internally and then systematically processed.

Only once service processes can be handled efficiently is it worth building up the after-sales volume. Therefore, the digitalization of internal processes is the basis for the transition from reactive to proactive service business. For example, by offering standardized service contracts with regular maintenance for sold equipment.

Connectivity & Automation

The next step for machinery and plant manufacturers is to develop their products into smart products that transmit selected operating data. In the past, there were concerns about the feasibility of this approach because providing this data depends on the customer giving his consent. However, more and more plant operators are now willing to do so. McKinsey has validated this trend in a survey and identified two significant factors:

B2C customer experiences lead to increased expectations for service experiences
Positive experiences with IoT-based remote services during COVID-19

Plant operators are generally motivated to share information with the manufacturer when the added value is tangible, for example, in the form of cheaper maintenance contracts and the promise of higher availability. Manufacturers can achieve this by using operating data to introduce usage-based maintenance strategies instead of following calendar-based maintenance cycles. This results in fewer services per plant and reduces overall costs. Furthermore, software can detect suspicious patterns in operating data early on and automatically initiate preventive measures based on rules.

Customer Integration

Companies with high service maturity integrate their customers into their business processes via a customer portal. Such a portal is the centerpiece of a modern service experience and strengthens customer loyalty. It enables customers to view their purchased products along with their operating data and the service logbook for each asset. An overview of past and planned services provides planning security and streamlines scheduling between the manufacturer and operator. A ticket system allows customers to submit new requests, track their processing status, and respond to corresponding inquiries directly in the system without the need for a service employee to answer phone calls and manually convert them into tickets. Additional services such as spare parts orders or trainings can also be requested through the customer portal, which streamlines and accelerates the sales process.

Conclusion

A strong service business has positive effects on cash flow, minimizes entrepreneurial risks, and simultaneously strengthens customer experience. How this is best achieved depends on the current situation in customer service, the company’s products, and the offering of the competitors and is unique for each company. Blueprints such as the maturity model described here provide guidance and enable a quick assessment of how excellent service can be realized step by step with the technologies available on the market.

CONTACT Elements for IoT helps your team effortlessly manage the increasing number of customer inquiries while enhancing the efficiency of your service department.