A knowledge-based automated driving approach for flexible production of individualized sheet metal parts

Christoph Hartmann, Daniel Opritescu, Wolfram Volk, Felix Schmiedl, Michael Ritter, Peter Gritzmann

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Driving is a highly flexible incremental sheet metal forming process. A special type of the process enables both local material stretching and, as an additional unique feature, local shrinking. Thereby, almost any component shape can be realized. Due to unavoidable tool and material variations during the process and the high number of forming steps, automation applying traditional approaches fails. This paper introduces a knowledge based automation concept, utilizing a database of manufacturing strategies for component geometries. Based on this information, new geometries can be produced by composition of appropriately transformed parts of the database. The conducted work is motivated by the trends of mass individualization and open architecture, which has a huge impact on production and manufacturing. Especially for sheet metal parts usually processed in high lot sizes, this presents a challenge. Incremental sheet metal forming processes provide suitable characteristics to target the issue of individualized shell component manufacturing. In this paper, for the first time, a highly flexible incremental sheet metal forming process, namely driving, is automated by a knowledge-based approach in a way that it meets both mass individualization and open architecture goals.

Original languageEnglish
Article number108558
JournalKnowledge-Based Systems
Volume244
DOIs
StatePublished - 23 May 2022

Keywords

  • Computer integrated manufacturing
  • Flexible manufacturing systems
  • Image registration
  • Sheet metal processing

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