Alexander Bott, Jan Baumgärtner, Nicolaus Klein, Alexander Puchta & Jürgen Fleischer 

Sustainable Manufacturing Innovations: Focus on New Energy Vehicles, Production Robots, and Software-Defined Manufacturing Proceedings of ICSM 2024, Shanghai, China, Towards a Generalised Information Modell: A Bayesian Network Approach for PPR-Representation 

Abstract:

The advancement of Industry 4.0 necessitates the abstraction of production processes to develop software-defined value streams. Existing approaches often suffer from limitations such as inflexibility and lack of scalability when individually modelling complex, heterogeneous production processes. These limitations hinder effective integration and interoperability within the Industry 4.0 framework. Given these challenges, this approach introduces an innovative “one size fits all” information model, enabling comprehensive capability matching across diverse production systems. The proposed graph-based methodology enables the probabilistic description of products and their features resulting from various production processes. This also enables the representation and investigation of their part-specific dependencies. The developed graph-based representation will be demonstrated on a complex product through elemental manufacturing processes. This standardises the description format of these production technologies. This crucial standardisation enables addressing the complexities of modern industrial processes. It also supports deploying software-defined value streams, optimising efficiency and adaptability in smart manufacturing environments.