Potential of Tool Clamping Surfaces in Forming Machines for Cognitive Production

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Mohaned Alaluss - , Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik (Autor:in)
  • Robin Kurth - , Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik (Autor:in)
  • Robert Tehel - , Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik (Autor:in)
  • Martin Wagner - , Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik (Autor:in)
  • Nico Wagner - , Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik (Autor:in)
  • Steffen Ihlenfeldt - , Professur für Werkzeugmaschinenentwicklung und adaptive Steuerungen, Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik (Autor:in)

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

OriginalspracheEnglisch
Seiten (von - bis)116-131
Seitenumfang16
FachzeitschriftJournal of Machine Engineering
Jahrgang22
Ausgabenummer3
PublikationsstatusVeröffentlicht - 2022
Peer-Review-StatusJa

Schlagworte

Schlagwörter

  • forming machines, industry 4.0, machine behavior, sensor