An Approach for an Automated Adaption of KPI Ontologies by Reusing Systems Engineering Data

Abstract

Technological progress leads to an increased utilization of data analysis and Business Intelligence that support manufacturing management decisions. Many promising solutions utilize semantic technologies. However, the deployment and maintenance of semantic technologies especially in reconfigurable manufacturing environments require a lot of manual effort. Concepts to embed them in an automated environment, as required by Reconfigurable Manufacturing Systems, are limited. In this paper, we present an approach to reuse systems engineering data to guide an automated process that updates a production data knowledge base. Thereby, an ontology that integrates distributed operational data to compute Key Performance Indicators such as the Overall Equipment Effectiveness index can be updated during the manufacturing reconfiguration process. This reduces the effort to handle the required changes of semantic data integration systems and enables a cost-effective adaption of the Business Intelligence for Reconfigurable Manufacturing Systems.

An interoperable semantic service toolset with domain ontology for automated decision support in the end-of-life domain

“…Semantic architectures still have performance challenges in terms of scaling data output, multi-level heterogeneity, conflicts between applications and correction of human errors in metadata [31,32,1]. The authors in [33] proposed an ontology framework for intelligent data analysis to manage validation, representation and interpretation of data from heterogeneous sources.…”

“…The use of diverse external sources for population of the domain ontology was suggested, but not implemented. [31] proposed a data integrating gateway between the knowledge base and the shop floor. While the gathering of knowledge was not completely automated, the ontology was updated with KPI's during assembly and reconfiguration planning.…”