Digital Twin: virtual model with potential

Bayer and LESER have been collaborating on digital twins. The two experts interviewed are Marc Westphal, Subject Matter Expert for Technical Asset Management and Materials Management at Bayer AG, Division Crop Science, Dormagen site, and Hendrik Wormuth, Manager Product Sales Solutions, LESER GmbH & Co. KG.

Text and images by Bayer-LESER

For many years now, there has been a close cooperation partnership between Bayer and LESER. The scope of this cooperation extends across a number of projects, including a long-standing initiative dedicated to digitalisation and the use of digital twins in the German process industry.

Considering that these topics are still in the development stage, without any industry standards available as yet, the cooperation partnership is doing pioneering work. In the Digital Data Chain Consortium (DDCC), the two companies are developing standards and technologies jointly with other partners from the process industry.

What results have they achieved so far? What are the next goals? What are the challenges that must be overcome? This interview provides some answers to these questions from both, the equipment operator’s and the manufacturer’s perspectives.

What is your definition of a digital twin?

Marc Westphal, Bayer:

A digital twin is a comprehensive digital representation of an identifiable asset. It is an entity that not only represents the current state of the asset but can also store historical data, for example data covering the entire lifecycle of the asset. It may also reflect links to digital twins of other assets.

Even though the term ‘digital twin’ was first defined some 20 years ago and became a hot business topic five years ago, we are only now able to begin reaping the potential of this technology. Open platforms and industry standards such as the Asset Administration Shell, or AAS, support these efforts. They are actually prerequisites for implementing digital twins.

Unfortunately, the definition of an asset administration shell is technically complex, scaring off some companies and getting in the way of industrial digitalisation.

There are two approaches that can help simplify this. The theoretical approach defines the digital twin on the basis of specific maturity levels during the product lifecycle. It differentiates between how an asset was designed (“as engineered”), how it was manufactured (“as built”), and finally, how it is being maintained (“as maintained”). At each maturity level, new or additional information becomes available that is digitally linked to the asset. If we apply all this to safety valves made by LESER, it would mean that for every safety valve delivered to us as the customer, a digital twin would be available at the lowest maturity level, the “as built” level, which comprises manufacturing bill of materials information (MBOM) as well as information about spare and wear parts. When LESER provides us with maintenance information, the maturity level will advance to “as maintained”.

What is actually of greater interest to the industry as a more pragmatic approach would be a version of the digital twin based on its possible implementation, i.e. as an asset twin, product twin or line twin.

This approach places greater emphasis on the application aspect and the interlinking (or collaboration) of the digital twin with various ‘partners.’ An asset twin, also referred to as a master data or information twin, reflects the initial and most basic composition of the asset. It is a purely digital representation of the entity as manufactured and supplied. This implementation, along with other information collected from master data, documents, CAD documents and bills of material, enables new application scenarios. Examples include the digital nameplate or ID link.

The next development step, called product twin, opens up opportunities for predictive maintenance when combined with additional IoT data (from sensors and controllers). The highest level, or line twin, is interlinked with all digital twins of a process line, enabling the simulation of entire processes. The implementation of a digital twin we are currently addressing is the asset twin. Together with LESER, we have collected and reconciled all information needed for a digital representation of safety valve master data. In this process we apply industry standards such as ECLASS and VDI2770. This work has prepared the basis for using an information platform to generate and use future Digital Product Passports (DPP).

Hendrik Wormuth, LESER

There isn’t much I can add to these explanations from a technical viewpoint. I would like to emphasise that the cooperation between the partners has been key to the success of these efforts. The complete digital twin consists of many layers. As manufacturers of safety valves, we are owners of some of the required data, such as operator instructions and certificates. The operator has data related to the behavior of the safety valve in the given application. Maintenance activities can contribute data on wear parts and off-duty times. Merging all of these aspects in a single solution that can be used consistently across the industry is a big coordination challenge. But resolving it will pay off.

The new digital twin technology is a hot discussion topic and predicted to play a major role in the future. What is your assessment?

Marc Westphal, Bayer:

As I mentioned earlier, digital twins are a key aspect of every digitalisation project. Merging all relevant information (characteristics, status information) covering the entire asset lifecycle is impossible without a digital twin. This is why there is great potential for digital twins. To realise this potential, digital twins need to be used collaboratively between the manufacturer, the operator, and the service provider. This requires introducing unified data standards such as the AAS mentioned earlier. But other aspects of data sovereignty must be standardised too.

Once there is a clearly structured process for the interaction between all the stakeholders, it will open up many possibilities for additional services along the asset lifecycle. Even options for creating semantic networks based on available information are no longer utopian. With the digital twin as a basis, the use of AI can be advanced efficiently.

Hendrik Wormuth, LESER: 

We are also convinced that having structured access to operational data will allow us to develop products that are better adapted to our customers’ needs, and to provide better advice to our customers. It will be possible to use proof-of-performance data from operational safety valves in the field to develop application-related recommendations for our products. In the future, our customers will be able to access any information about their safety valves at any time and from any location. And last but not least, the unique information on the nameplate is a machine-readable identifier that interlinks with all documentation for that particular safety valve.

Marc Westphal
Hendrik Wormuth

What challenges are you facing, and how do you intend to overcome them?

Marc Westphal, Bayer:

Regrettably, many things we are talking about today are still mere theory. What is the precise definition of a digital twin when we are talking to our partners? What is the basis of this definition? Is the digital twin interoperable? How can the required data sovereignty be made possible? Plus, there are system- and data-related challenges inherent in IT systems, in particular information-sharing platforms needed for collaboration. To tackle these challenges, we have identified the following key aspects we need to address:

  • Interacting with all stakeholders (manufacturer, operator, service provider, platform operator) as partners and cultivating an open dialog. We cannot hope to arrive at an effective and sustainable solution unless everybody has the same understanding of the boundary conditions and requirements.
  • Sharing information in committees (such as the ones mentioned earlier) will support the development of solutions that can be applied on a broad basis.
  • Including users in the development process, especially with regard to potential new services and E2E processes, is crucial. User cases and user stories must be developed by involving everyone.
Hendrik Wormuth, LESER:

Nobody can resolve these challenges alone in an efficient manner. Even a solution developed jointly by Bayer AG and LESER would not be fit for the broader industry. Manufacturers of other products and other operators would find it difficult to follow the same strategy. In short, it would only be an insular solution with limited benefits.

What will the next steps be in your digitalization strategies?

Marc Westphal, Bayer:

As far as our collaboration with LESER is concerned, we will soon take the asset twin from the pilot phase to the Steady State stage and continue optimising it.

Based on experiences gained during the pilot phase, we will enter products from other manufacturers and service providers into the information sharing platform and start communicating on the basis of asset twins.

As part of our committee work, we will promote the continued development and utilisation of a AAS, jointly with LESER. This will drive standardisation efforts with regard to digital twins based on the criteria of the Digital Data Chain (DDC).

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