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Cyber Integrated Metrology, Learning and Evaluation System: An Approach Towards Smart Factories

[+] Author Affiliations
Martin Helgoson, Pontus Westlin, Vahid Kalhori

AB Sandvik Coromant, Sandviken, Sweden

Paper No. IMECE2017-71336, pp. V002T02A047; 10 pages
doi:10.1115/IMECE2017-71336
From:
  • ASME 2017 International Mechanical Engineering Congress and Exposition
  • Volume 2: Advanced Manufacturing
  • Tampa, Florida, USA, November 3–9, 2017
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-5835-6
  • Copyright © 2017 by ASME

abstract

Manufacturing processes has seen constant change in the last decades to remain a central element of global wealth and development. Despite large efforts to increase efficiency, still significant sources of waste during manufacturing execution exist. These are mainly based on poor manufacturability, inefficient processes and low machine utilization.

The digital transformation towards “smart factories” will however enable development of new types of methods and technologies that will support advanced automation, resource efficiency and further improvements towards Lean Manufacturing processes.

This paper presents an approach for integrated evaluation of errors introduced from process planning to machined component. Critical parameters, influencing and interrelated factors, nominal value deviations from successive process steps and real-time machining are analyzed in one common cyber-physical model. This will in turn enable analyses of root-causes and serve as basis for process feedback, quality assurance and machine learning.

The focus in this paper is to describe the architecture of the Cyber Integrated Metrology, Learning and Evaluation System (CIMLES) approach and results from proof of concept demonstrators for 3- and 5-axis machining, developed in order to evaluate and verify various subsystems of the approach.

Copyright © 2017 by ASME
Topics: Metrology

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