Integrating Predictive Model Markup Language with Asset Administration Shell

Abstract

The article presents a systematic approach to integrate Predictive Model Markup Language (PMML) with Asset Administration Shell (AAS) for manufacturing interoperability. The present system aims to exchange and share PMML, i.e., data analytics models, across AASs, i.e., asset representations of heterogeneous manufacturing assets. Furthermore, the present system is designed to automatically generate data analytics models on production machines, convert models into the PMML format, create AAS instances for the machines, and embed the PMML models onto the AAS instances. The article includes the design architecture, including a concept model, system architecture, information structure. An AAS client-server prototype is implemented to demonstrate the feasibility of the present system. In the prototype, a server creates and transmits the AAS that corresponds to a production machine and contains submodels associated with PMML-based energy prediction models derived by regression analysis and artificial neural network. A client receives and parses the AAS and its PMML models to predict energy consumed in the machine.