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Article

Machining Phenomenon Twin Construction for Industry 4.0: A Case of Surface Roughness

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Graduate School of Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami, Hokkaido 090-8507, Japan
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Faculty of Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami, Hokkaido 090-8507, Japan
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Mitsubishi Hitachi Tool Engineering, Ltd., Tokyo 130-0026, Japan
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Department of Chemical, Materials and Industrial Production Engineering, Piazzale Tecchio 80, 80125 Naples, Italy
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Author to whom correspondence should be addressed.
J. Manuf. Mater. Process. 2020, 4(1), 11; https://doi.org/10.3390/jmmp4010011
Received: 26 December 2019 / Revised: 30 January 2020 / Accepted: 6 February 2020 / Published: 11 February 2020
(This article belongs to the Special Issue Intelligent Machining and Grinding)
Industry 4.0 requires phenomenon twins to functionalize the relevant systems (e.g., cyber-physical systems). A phenomenon twin means a computable virtual abstraction of a real phenomenon. In order to systematize the construction process of a phenomenon twin, this study proposes a system defined as the phenomenon twin construction system. It consists of three components, namely the input, processing, and output components. Among these components, the processing component is the most critical one that digitally models, simulates, and validates a given phenomenon extracting information from the input component. What kind of modeling, simulation, and validation approaches should be used while constructing the processing component for a given phenomenon is a research question. This study answers this question using the case of surface roughness—a complex phenomenon associated with all material removal processes. Accordingly, this study shows that for modeling the surface roughness of a machined surface, the approach called semantic modeling is more effective than the conventional approach called the Markov chain. It is also found that to validate whether or not a simulated surface roughness resembles the expected roughness, the outcomes of the possibility distribution-based computing and DNA-based computing are more effective than the outcomes of a conventional computing wherein the arithmetic mean height of surface roughness is calculated. Thus, apart from the conventional computing approaches, the leading edge computational intelligence-based approaches can digitize manufacturing processes more effectively. View Full-Text
Keywords: Industry 4.0; cyber-physical systems; digital twin; surface roughness; complex phenomenon; semantic modeling; Monte Carlo simulation; DNA-based computing; Markov chain Industry 4.0; cyber-physical systems; digital twin; surface roughness; complex phenomenon; semantic modeling; Monte Carlo simulation; DNA-based computing; Markov chain
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MDPI and ACS Style

Ghosh, A.K.; Ullah, A.S.; Kubo, A.; Akamatsu, T.; D’Addona, D.M. Machining Phenomenon Twin Construction for Industry 4.0: A Case of Surface Roughness. J. Manuf. Mater. Process. 2020, 4, 11. https://doi.org/10.3390/jmmp4010011

AMA Style

Ghosh AK, Ullah AS, Kubo A, Akamatsu T, D’Addona DM. Machining Phenomenon Twin Construction for Industry 4.0: A Case of Surface Roughness. Journal of Manufacturing and Materials Processing. 2020; 4(1):11. https://doi.org/10.3390/jmmp4010011

Chicago/Turabian Style

Ghosh, Angkush K., AMM S. Ullah, Akihiko Kubo, Takeshi Akamatsu, and Doriana M. D’Addona 2020. "Machining Phenomenon Twin Construction for Industry 4.0: A Case of Surface Roughness" Journal of Manufacturing and Materials Processing 4, no. 1: 11. https://doi.org/10.3390/jmmp4010011

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