Increasing Resource Efficiency of Manufacturing Systems Using a Knowledge-Based System

Stefan Blume*, Christoph Herrmann, Sebastian Thiede

*Corresponding author for this work

Research output: Contribution to journalConference articleAcademicpeer-review

3 Citations (Scopus)
6 Downloads (Pure)

Abstract

Nowadays, companies often implement sustainability strategies in order to react to changing market demands and reduce their environmental impacts and resource related costs. In this context, the identification and exploitation of resource saving potentials is a challenging issue. Depending on the knowledge and experience of the persons in charge, promising improvement measures might be found or remain undetected. At this point, knowledge-based systems can come into play, providing expert knowledge to support planners and decision-makers with the identification of specific improvement measures. This work presents such a knowledge-based system, which is able to identify improvement measures on machine and process chain level through rule-based reasoning. In order to exploit these potentials, suitable improvement measures are assigned automatically from a knowledge database. The application is demonstrated with a case from the metal mechanic industry.

Original languageEnglish
Pages (from-to)236-241
Number of pages6
JournalProcedia CIRP
Volume69
DOIs
Publication statusPublished - 1 Jan 2018
Externally publishedYes
Event25th CIRP Conference on Life Cycle Engineering, LCE 2018 - Copenhagen, Denmark
Duration: 30 Apr 20182 May 2018
Conference number: 25

Keywords

  • Decision Support
  • Improvement Measures
  • Knowledge-Based System
  • Resource Efficiency
  • Rule-based Reasoning

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