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Maximilian Both

M.Eng.
Faculty of Process Engineering, Energy and Mechanical Systems

Institute of Building Services Engineering

Maximilian Both

Campus Deutz
Betzdorfer Straße 2
50679 Köln
Room HW2-69 Mailing address


  • Phone: +49 221-8275-2388

Conference Paper

  • Interoperability of semantically heterogeneous digital twins through Natural Language Processing methods
    Cartus, A.; Both, M.; Maisch, N.; Müller, J.; Diedrich, C., Publisher: 14th REHVA HVAC World Congress, Rotterdam
    Self-organizing systems represent the next stage in the development of automation technology. For being able to interact with each other in an interoperable manner, it requires a uniform digital representation of the system's components, in the form of digital twins. In addition, the digital twins must be semantically interoperable in order to realize interoperability without the need for costly engineering in advance. For this purpose, the current research approach focuses on a semantically homogeneous language space. Due to the multitude of actors within an automation network, the agreement on a single semantic standard seems unlikely. Different standards and vendor-specific descriptions of asset information will continue to exist. This paper presents a method extending the homogeneous semantics approach to heterogeneous semantics. For this purpose, a translation mechanism is designed. The mapping of unknown vocabularies to a target vocabulary enables the interactions of semantically heterogeneous digital twins. The mapping is based on methods from the artifcial intelligence domain, specifically machine learning and natural language processing. Semantic attributes (name, definition) as well as further classifying attributes (unit, data type, qualifier, category, submodel element subtype) of the digital twins' attributes are used therefore. For the mapping of the semantic attributes pre-trained language models on domain specific texts and sentence embeddings are combined. A decision tree classifies the other attributes. Different semantics for submodels of pumps and HVAC systems are used as the evaluation dataset. The combination of the classification of the attributes (decision tree) and the subsequent semantic matching (language model), leads to a significant increase in accuracy compared to previous studies.
    DOI: 10.34641/clima.2022.143
  • Automated performance monitoring of HVAC components by artificial intelligence
    Both, M.; Cartus, A.; Maisch, N.; Kämper, B.; Müller, J.; Diedrich, C., Publisher: 14th REHVA HVAC World Congress, Rotterdam
    Energy management systems are an important tool for increasing the energy efficiency of buildings. However, the widespread availability of such systems is offset by the high complexity and high costs of implementation, as well as a lack of data. By using standardized digital twins of technical components, these obstacles can be addressed. In combination with homogeneous semantics of the digital twins and standardized interfaces as uniform access points to the information, the implementation of an energy management system can be simplified. If all technical components of a building have the same information technology structure in the form of digital twins and make their standardized information uniformly available for query, simple query rules can be implemented. These enable the automated integration of the information into an energy management system. However, given the large number of different manufacturers of the technical components, agreement on a common semantic standard in particular seems unlikely. Studies show that methods from the field of Natural Language Processing can be used to process heterogeneous semantics. Agreement on a common vocabulary is no longer necessary. Instead, different semantics can be used and matched to a target vocabulary. In order to use semantic matching in Industrie 4.0 environments, it must be provided as an Industrie 4.0 service. The service provides a translation mechanism from a foreign vocabulary to one's own. For this purpose, a standardized Industrie 4.0 interface consisting of two operations is specified. This interface is implemented prototypically as an API to show how it can be used. The specified interface can be used within the digital twins to process heterogeneous semantics and map them to its own. Extending the Industrie 4.0 approach from homogeneous to heterogeneous semantics can help simplifying the implementation of energy management systems. Simpler implementation lowers the barriers to the use of such systems, which in turn can lead to their higher availability.
    DOI: 10.34641/clima.2022.144
  • Reducing configuration efforts in energy management systems based on natural language processing methods and asset administration shells
    Both, M.; Müller, J.; Diedrich, C., Publisher: 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)
    Energy management systems are an important tool for increasing the energy efficiency of buildings. However, the widespread availability of such systems is offset by the complexity and high costs of implementation, as well as a lack of data. These obstacles can be addressed by using standardized digital twins of technical components. In combination with homogeneous semantics and standardized interfaces as uniform access points to information, the implementation of an energy management system can be simplified. However, given the large number of different manufacturers of the technical components, an agreement on a common semantic standard of the information elements seems unlikely. Studies show that methods from the field of natural language processing can be used to process heterogeneous semantics. An agreement on a common vocabulary is no longer necessary. Instead, different semantics can be used and matched to a target vocabulary. The implementation of such a matching service reduces the configuration effort for the implementation of an energy management system. Providing an Industrie 4.0 interface that contains the semantic matching service within the components allows the interaction between them and an energy management system. A prerequisite for automated interaction is the availability of information in a uniform structure in the form of an information model. This paper presents the design of an Industrie 4.0 asset administration shell and initial submodels for an energy management system. Additionally, an Industrie 4.0 interface for the semantic matching service is implemented in a prototypical application of an energy management system. This implementation demonstrates how the configuration effort of such a system can be reduced by semantic matching.
    DOI: 10.1109/ETFA52439.2022.9921479

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