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Toward a cyber-physical manufacturing metrology model for industry 4.0

Published online by Cambridge University Press:  26 October 2020

Slavenko M. Stojadinovic Open the ORCID record for Slavenko M. Stojadinovic [Opens in a new window] ,
Vidosav D. Majstorovic  and
Numan M. Durakbasa
Slavenko M. Stojadinovic*
Affiliation:
Faculty of Mechanical Engineering, Department for Production Engineering, University of Belgrade, Kraljice Marije 16, 11120Belgrade 35 PF 34, Serbia
Vidosav D. Majstorovic
Affiliation:
Faculty of Mechanical Engineering, Department for Production Engineering, University of Belgrade, Kraljice Marije 16, 11120Belgrade 35 PF 34, Serbia
Numan M. Durakbasa
Affiliation:
Faculty of Mechanical and Industrial Engineering, Department for Interchangeable Manufacturing and Industrial Metrology, Vienna University of Technology, 1060 Wien, Getreidemarkt 9/311-01-4, BA09, Austria
*
Author for correspondence: Slavenko M. Stojadinovic, E-mail: [email protected]
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Abstract

Industry 4.0 represents high-level methodologies for the development of new generation manufacturing metrology systems, which are more intelligent (smart), autonomous, flexible, high-productive, and self-adaptable. One of the systems capable of responding to these challenges is a cyber-physical manufacturing metrology system (CP2MS) with techniques of artificial intelligence (AI). In general, CP2MS systems generate Big data, horizontally by integration [coordinate measuring machines (CMMs)] and vertically by control. This paper presents a cyber-physical manufacturing metrology model (CP3M) for Industry 4.0 developed by applying AI techniques such as engineering ontology (EO), ant-colony optimization (ACO), and genetic algorithms (GAs). Particularly, the CP3M presents an intelligent approach of probe configuration and setup planning for inspection of prismatic measurement parts (PMPs) on a CMM. A set of possible PMP setups and probe configurations is reduced to optimal number using developed GA-based methodology. The major novelty is the development of a new CP3M capable of responding to the requirements of an Industry 4.0 concept such as intelligent, autonomous, and productive measuring systems. As such, they respond to one smart metrology requirement within the framework of Industry 4.0, referring to the optimal number of PMPs setups and for each setup defines the configurations of probes. The main contribution of the model is productivity increase of the measuring process through the reduction of the total measurement time, as well as the elimination of errors due to the human factor through intelligent planning of probe configuration and part setup. The experiment was successfully performed using a PMP specially designed and manufactured for the purpose.

Keywords

Cyber-physicalGAIndustry 4.0intelligent planningmetrology
Type
Research Article
Information
AI EDAM , Volume 35 , Issue 1 , February 2021 , pp. 20 - 36
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Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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