dataject.log

Short description – In the machinery and plant engineering sector, which is dominated by small and medium-sized enterprises (SMEs), the on-time commissioning of custom-made products is critical to competitiveness. Project planning and management are key success factors, but they depend on having up-to-date information on all processes throughout project execution. While production data is usually already captured digitally and available in the form of a digital twin, this data is lacking for logistical processes in contract manufacturing within the machinery and plant engineering sector. Feedback on logistical processes—if provided at all—is done manually, in analog form, or aggregated retrospectively. The utilization time and location of (logistical) resources are often unclear.

This research project aims to close this gap in the digital twin. The challenge is to develop a universally applicable and extensible semantic model of a digital twin for logistics processes in mechanical and plant engineering, through which (partially) automated data collection can be implemented. The planned results include a systematization of relevant information on logistics processes, an ontology-based implementation of a semantic model for a digital shadow, a technology assessment based on intended use, and a methodology featuring technology templates and an interoperability concept for technical implementation. A demonstration platform will be used to evaluate practical application scenarios with partners from the project steering committee. The innovation lies in creating a practical approach for SMEs to digitally capture logistics process information for the mechanical and plant engineering sectors. The information requirements define an application-specific view of the Digital Shadow, in this case focused on project management. However, the semantic model and the technology templates are designed to be flexibly expandable.

The research project “dataject.log – Development of a Semantic Model for Describing a Digital Twin of Logistics Processes in Mechanical and Plant Engineering for Use in Project Management” is being carried out in collaboration between the Production Organization and Factory Planning Department at the University of Kassel and the Business Informatics Department at the Institute for Management and Information at West Saxon University of Applied Sciences in Zwickau.

IGF Project 21755 BG of the German Logistics Association (BVL)

Project Duration:
Jun 1, 2021 to Feb 28, 2023

Project Management:
Prof. Dr. Christoph Laroque

Partner:
BVL, AIF, IGF, University of Kassel

The goal of the project is to design and implement a methodology for providing a digital shadow using a range of technological approaches. Specific aspects of the research project include:

  • Ensuring the general validity of the semantic model through ontology-based modeling,
  • Utilizing existing technologies for data collection, ensuring persistent data storage, and
  • Incorporating an interoperability concept so that SME users can use the collected data directly in their project management tools for planning and control.

The innovation lies in closing an information and data gap regarding logistics processes in mechanical and plant engineering during construction site operations. In addition, the project provides SMEs with access to process information, data model descriptions, and data collection technologies. The information requirements are formulated on a case-by-case basis and define a specific “view” of the digital twin—in this project, focused on project management. The ontology, as a semantic description model, and the information model are designed to be flexible and expandable.

The logistics reference model developed in a previously completed research project (Gliem et al. 2019) is used to systematize the logistics processes and determine what data must be collected at which points to capture these processes.

The collected data is described using a semantic model, thereby representing a digital twin of the logistics processes. The semantic model is supplemented by a coordinated methodology that includes technology templates and an interoperability concept for the design, implementation, and deployment of solutions aimed at creating a digital twin of logistics processes in the mechanical and plant engineering sector for use in project management. The developed methodology is ultimately implemented in a demonstration platform and is thus available to interested companies for evaluation.