Cloud based platform for optimal machining parameter selection based on function blocks and real time monitoring

Nikolaos Tapoglou, Jörn Mehnen, Aikaterini Vlachou, Michael Doukas, Nikolaos Milas, Dimitris Mourtzis

Research output: Contribution to journalArticle

57 Citations (Scopus)

Abstract

The way machining operations have been running has changed over the years. Nowadays, machine utilization and availability monitoring are becoming increasingly important for the smooth operation of modern workshops. Moreover, the nature of jobs undertaken by manufacturing small and medium enterprises (SMEs) has shifted from a mass production to small batch. To address the challenges caused by modern fast changing environments, a new cloud-based approach for monitoring the use of manufacturing equipment, dispatching jobs to the selected computer numerical control (CNC) machines, and creating the optimum machining code is presented. In this approach the manufacturing equipment is monitored using a sensor network and though an information fusion technique it derives and broadcasts the data of available tools and machines through the internet to a cloud-based platform. On the manufacturing equipment event driven function blocks with embedded optimization algorithms are responsible for selecting the optimal cutting parameters and generating the moves required for machining the parts while considering the latest information regarding the available machines and cutting tools. A case study based on scenario from a shop floor that undertakes machining jobs is used to demonstrate the developed methods and tools.
Original languageEnglish
Article numberMANU-14-1548
Number of pages11
JournalJournal of Manufacturing Science and Engineering
Volume137
Issue number4
Early online date8 Jul 2015
DOIs
Publication statusPublished - 1 Aug 2015

Keywords

  • function blocks
  • optimisation
  • cloud manufacturing

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