Resource monitoring in industrial production with knowledge-based models and rules

  • Authors:
  • Lisa Abele;Martin Kleinsteuber;Thorbjørn Hansen

  • Affiliations:
  • Siemens AG, Corporate Technology, Munich, Germany;Technische Universität München, Munich, Germany;Siemens AG, Corporate Technology, Munich, Germany

  • Venue:
  • Proceedings of the 4th workshop on Workshop for Ph.D. students in information & knowledge management
  • Year:
  • 2011

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Abstract

The manufacturing domain currently experiences a significant increase in resource expenses for industrial plants. However, the implementation of systems to monitor the resource consumption in such complex plants requires high investment concerning time and manual effort. Our goal is to describe the plant by means of knowledge-based models and rules to implement a generic, semi-automated monitoring system which can be defined with lower initial effort and which can be adapted quickly to modifications. An advantage of this model-based approach is that the energy and resource consumption of each component in a plant can be associated with a sequence of operations and the effects on the overall system get visible. Another advantage of knowledge-based systems combined with rules is that they offer application independent solutions and flexibility. The paper outlines the state of the art of relevant technologies by describing several approaches, such as existing monitoring systems, rule engines and modeling tools. Furthermore, it describes a representative example that we will use in our further work to evaluate which tools are appropriate for a resource monitoring system.