Flexible reconfiguration of plants and processes by ontology-based data modeling of product, process and resourcerelationships.Copyright: WZL / SE-RWTH
Production processes as well as plants are required to adapt more frequently due to an increasing number of product variants and product lines and shorter product lifetimes. In the course of “Industrie4.0” this demand is referred to as resilient factory and describes the ability for a quick reconfiguration of production lines according to changing orders by self-adaptive software. This software optimizes the production line by identifying and linking required and available resources.
A static mapping between product, processand resource(e.g. as specified in DIN 62264) is no longer sufficient for this purpose. Instead, such a mapping needs to be flexible and conceptive for model based adaptions to allow for efficient changes.The challenge is to identify valid allocations between these components as each product imposes individual requirements to The production process and resources. In addition, transitions costs for reconfiguring the plant need to be considered by theoptimization software.
Ontologies could serve as a foundation for semantic modeling to specify capabilities of a resource on the one hand and requirements of the products and it's production process on the other. Languages from the UML family such as Feature Diagrams, Activity Diagrams and Class Diagrams will be used for modeling. The desired outcome is a formal specification of products, their variants, respective production processes andavailable resources and their respective abilities. This specification can serve as an input for optimization algorithms, which produce reconfiguration plans for the production processes as well as for the plant carrying out these processes.
In the course of this project, the data model for an existing production process(Smart Automation Lab SAL) will be adapted to allow agile reconfiguration. A software prototype will demonstrate the optimization strategies. The whole scenario will be executed and evaluated on a real manufacturing process in the SAL.