Potential of Tool Clamping Surfaces in Forming Machines for Cognitive Production

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Mohaned Alaluss - , Fraunhofer Institute for Machine Tools and Forming Technology (Author)
  • Robin Kurth - , Fraunhofer Institute for Machine Tools and Forming Technology (Author)
  • Robert Tehel - , Fraunhofer Institute for Machine Tools and Forming Technology (Author)
  • Martin Wagner - , Fraunhofer Institute for Machine Tools and Forming Technology (Author)
  • Nico Wagner - , Fraunhofer Institute for Machine Tools and Forming Technology (Author)
  • Steffen Ihlenfeldt - , Chair of Machine Tools Development and Adaptive Controls, Fraunhofer Institute for Machine Tools and Forming Technology (Author)

Abstract

High reproducibility of forming processes along with high quality expectations of the resulting formed parts demand cognitive production systems. The prerequisite is process transparency, which can be improved by increased knowledge of interdependencies between forming tool and forming machine that affects the tool clamping interface behavior. Due to the arrangement as surfaces transmitting process forces, their closeness to the forming process, and yet machine inherent, tool clamping interface provide greater potential for intelligent monitoring. This paper presents a holistic analysis of the interdependencies at the tool clamping interface. Here, the elastic deflection behavior of the press table and slide with their related clamping surfaces, the frictional slip behavior between the interacting machine components and the used clamping devices are described on qualitative level and verified by simulative analysis. Based on the results, available sensor systems are assessed regarding the capability to monitor the identified phenomena inline.

Details

Original languageEnglish
Pages (from-to)116-131
Number of pages16
JournalJournal of Machine Engineering
Volume22
Issue number3
Publication statusPublished - 2022
Peer-reviewedYes

Keywords

Keywords

  • forming machines, industry 4.0, machine behavior, sensor