What question did this study set out to answer?

The study aims to establish a practical use case for digitalizing a test bench using the Asset Administration Shell.

April 23, 2026Open Access

Adoption of Digital Twin Interface Standards for Supervision and Regulation of Conventional Manufacturing Infrastructures

VKV. Murali KrishnaSri Ganapathi Sachchidananda Vagdevi Center BMBandari ManasaSri Ganapathi Sachchidananda Vagdevi Center NKNUNAVATH AJAY KUMARSri Ganapathi Sachchidananda Vagdevi Center

Key Points

The study aims to establish a practical use case for digitalizing a test bench using the Asset Administration Shell.
Utilized a NVPT test bench for monitoring and control
Developed three Asset Administration Shells: two passive for data collection, one reactive for process control
Implemented engagement modeling within the AAS and used a Raspberry Pi to evaluate Edge Computing efficiency.
The methodology successfully integrated new technologies with traditional systems
Demonstrated cost-effectiveness and resource efficiency for implementing Industry 4.0
Highlighted the operational benefits of remote monitoring and control capabilities.

Abstract

Adding automation, industrialisation, and digitalisation to many areas is pointless because of Industry 4.0. In some cases, this means getting rid of old systems and putting in new ones that are made to work with these features. This requires resources that are very hard to find during the transition for small and medium-sized businesses. The paper talks about a study on how to use the Asset Administration Shell (AAS) to keep an eye on and control industrial processes. The study utilised a Level, Flow, Pressure, and Temperature (NVPT) test bench that was manufactured during the operational period of such systems. The study followed the idea of building system architecture based on the Reference Architectural Model for Industry 4.0 (RAMI 4.0). The virtualisation process led to the creation of three AAS. Two of them were passive AAS that collected and analysed data, and the third was a reactive AAS that kept the test bench's temperature and level in check. More research added an engagement modelling approach to the AAS because standard Python didn't have built-in support for it. The IoT ecosystem package, which included the ssocktio library, made it possible to build the two passive AAS by letting them work together. The third type of reactive AAS was made using a preemptive approach, which is how Python classes and inheritance rules are usually used to work with data. We used a Raspberry Pi to run the use cases and see how well Edge Computing works. We looked at how much money and resources the AAS uses compared to an enterprise and the cloud. The purpose of this study was to come up with a practical use case for digitalising the test bench so that the test bench's variables could be monitored and controlled from a distance. In short, the conclusions showed that the methodology worked and that it was a good way to mix new technologies with old systems without spending a lot of money. The conclusion was that the method could help old systems work with Industry 4.0 environments in a way that was both cost-effective and efficient.

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