Loading…

Forming 4.0: Smart machine components applied as a hybrid plain bearing and a tool clamping system

Higher process reliability as well as detailed information about the machine condition are necessary requirements for the manufacturing of complex geometric shapes with simultaneous increase of the machine availability and output rate. By implementing smart machine components it is possible to solve...

Full description

Saved in:
Bibliographic Details
Published in:Procedia manufacturing 2019, Vol.27, p.65-71
Main Authors: Kurth, R., Tehel, R., Päßler, T., Putz, M., Wehmeyer, K., Kraft, C., Schwarze, H.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Higher process reliability as well as detailed information about the machine condition are necessary requirements for the manufacturing of complex geometric shapes with simultaneous increase of the machine availability and output rate. By implementing smart machine components it is possible to solve central challenges focusing on the investment-intensive field of forming technology. These components gather and evaluate machine and process data on decentralized spots with certain integrated sensors. Within this paper the potential benefits of those smart machine components are demonstrated using the example of an intelligent hybrid plain bearing and a smart tool holder. Focusing on the damage prevention of plain bearings, a load controlled journal bearing combining hydrodynamic and hydrostatic characteristics has been developed and tested by simulation. In addition, a smart hydraulic tool holder for upper dies has been successfully tested by simulations and experiments in order to investigate and demonstrate the potential for using the monitored clamping characteristics to increase the process transparency and the condition of the tool holder. As a result these smart machine components can be used additionally for a significant improvement of industry 4.0 tools such as digital twins of both process and machine.
ISSN:2351-9789
2351-9789
DOI:10.1016/j.promfg.2018.12.045