Implementation of a Test Plan Ontology for Incremental Sheet Metal Forming Made with Models for Manufacturing (MfM) Methodology

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Models for Manufacturing (MfM) is a methodology currently under development with a novel approach to applying Ontology-Based Engineering concepts to manufacturing. MfM is based in a 3-Layer Model (3LM) framework: a Data layer that collects all the information, e.g. in databases, an Ontology layer for ontological definition containing the domain knowledge, and a Service layer comprising all necessary software services. The Ontology layer is the core of the 3LM framework and is made up of 4 models: Scope, Data, Behaviour, and Semantic models. The 3LM framework is supported by user-friendly modelling tools and guarantees independence between the 3 layers. This work aims to evaluate the MfM methodology through the development of a real use case based on previous work by the authors: an experimental test plan to study sheet metal formability in hole-flanging operations by Single-Point Incremental Forming (SPIF). The test plan includes the definition of the main geometrical parameters of the specimens, the generation of the forming tool paths and G-code for a CNC machine, the evaluation of the manufactured parts and the analysis of the material formability. The paper presents the definition of the Ontology layer for the developed use case using various graphical modelling tools and a simple implementation of Data and Service layers as well as the interfaces between the 3 layers. The conclusions of the work highlight the strengths and weaknesses of the application developed and point out the main lines of future development of the MfM methodology.

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167-175

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October 2023

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© 2023 Trans Tech Publications Ltd. All Rights Reserved

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[1] A. Akundi, V. Lopez. A Review on Application of Model Based Systems Engineering to Manufacturing and Production Engineering Systems. Procedia Computer Science 185 (2021) 101-108.

DOI: 10.1016/j.procs.2021.05.011

Google Scholar

[2] L. Yang, K. Cormican, M. Yu. Ontology-Based Systems Engineering: A State-of-the-Art Review. Computers in Industry 111 (2019) 148-71.

DOI: 10.1016/j.compind.2019.05.003

Google Scholar

[3] S. El Kadiri, W. Terkaj, E.N. Urwin, C. Palmer, D. Kiritsis, R. Young. Ontology in Engineering Applications. In: Formal Ontologies Meet Industry, FOMI 2015. Lecture Notes in Business Information Processing, 225. Springer, Cham, 2015.

DOI: 10.1007/978-3-319-21545-7_11

Google Scholar

[4] R. Arista, F. Mas, D. Morales-Palma, M. Oliva, C. Vallellano. A Preliminary Ontology-Based Engineering Application to Industrial System Reconfiguration in Conceptual Phase. In: 11th International Workshop on Formal Ontologies meet Industry Proceedings, FOMI 2021, CEUR Workshop Proceedings (CEUR-WS.org), 2021.

Google Scholar

[5] F. Mas, J. Racero, M. Oliva, D. Morales-Palma. A Preliminary Methodological Approach to Models for Manufacturing (MfM). In: Product Lifecycle Management to Support Industry 4.0. PLM 2018. IFIP Advances in Information and Communication Technology, 540. Springer, Cham, 2018.

DOI: 10.1007/978-3-030-01614-2_25

Google Scholar

[6] Sprinkle, Jonathan, Bernhard Rumpe, Hans Vangheluwe, Gabor Karsai. Metamodelling: State of the Art and Research Challenges. In: Model-Based Engineering of Embedded Real-Time Systems. Lecture Notes in Computer Science, 6100. Springer, Berlin, Heidelberg, 2010.

DOI: 10.1007/978-3-642-16277-0_3

Google Scholar

[7] D. Morales-Palma, M. Oliva, R. Arista, C. Vallellano, F. Mas. AEnhanced Metamodels Approach Supporting Models for Manufacturing (MfM) Methodology. In: 12th International Workshop on Formal Ontologies meet Industry Proceedings, FOMI 2022, CEUR Workshop Proceedings (CEUR-WS.org), 2022.

Google Scholar

[8] A. Fisher, M. Nolan, S. Friedenthal, M. Loeffler, M. Sampson, M. Bajaj, L. VanZandt, K. Hovey, J. Palmer, L. Hart. Model Lifecycle Management for MBSE. INCOSE International Symposium, 24 (2014) 207-229.

DOI: 10.1002/j.2334-5837.2014.tb03145.x

Google Scholar

[9] R. Arista, F. Mas, M. Oliva, J. Racero, D. Morales-Palma. Framework to support Models for Manufacturing (MfM) methodology. In: 9th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2019. IFAC-PapersOnLine 52(13), 2019, pp.1584-1589.

DOI: 10.1016/j.ifacol.2019.11.426

Google Scholar

[10] F. Mas, J. Racero, M. Oliva, D. Morales-Palma. Preliminary ontology definition for aerospace assembly lines in Airbus using Models for Manufacturing methodology. In: 7th International conference on Changeable, Agile, Reconfigurable and Virtual Production, CARV 2018. Procedia Manufacturing 28 (2019) 207-213.

DOI: 10.1016/j.promfg.2018.12.034

Google Scholar

[11] D. Morales-Palma, F. Mas, J. Racero, C. Vallellano. A Preliminary Study of Models for Manufacturing (MfM) Applied to Incremental Sheet Forming. In: Product Lifecycle Management to Support Industry 4.0, PLM 2018. IFIP Advances in Information and Communication Technology, 540. Springer, Cham, 2018.

DOI: 10.1007/978-3-030-01614-2_26

Google Scholar

[12] Behera AK, de Sousa RA, Ingarao G, Oleksik V. Single point incremental forming: An assessment of the progress and technology trends from 2005 to 2015. Journal of Manufacturing Processes 27 (2017) 37-62.

DOI: 10.1016/j.jmapro.2017.03.014

Google Scholar

[13] M. Borrego, D. Morales-Palma, A. J. Martínez-Donaire, G. Centeno, C. Vallellano. Analysis of formability in conventional hole flanging of AA7075-O sheets: punch edge radius effect and limitations of the FLC. International Journal of Material Forming 13 (2020) 303-316.

DOI: 10.1007/s12289-019-01487-2

Google Scholar

[14] NIST: Integration Definition for Function Modeling (IDEF0). Computer Systems Laboratory of the National Institute of Standards and Technology, December 1993, URL: http://www.idef.com/wp-content/uploads/2016/02/idef0.pdf.

DOI: 10.6028/nist.fips.183

Google Scholar

[15] A. Cañas, G. Hill, R. Carff, N. Suri, J. Lott, T. Eskridge, G. Gomez, M. Arroyo, R. Carvajal. CmapTools: A Knowledge Modeling and Sharing Environment. In Concept maps: Theory, methodology, technology. Proceedings of the first international conference on concept mapping, 2004.

DOI: 10.1007/11510154_11

Google Scholar

[16] D. Morales-Palma, M. Oliva, J. Racero, I. Eguia, R. Arista, F. Mas. Metamodels Approach Supporting Models for Manufacturing (MfM) Methodology. In: Product Lifecycle Management. Green and Blue Technologies to Support Smart and Sustainable Organizations. PLM 2021. IFIP Advances in Information and Communication Technology, 640. Springer, Cham, 2022.

DOI: 10.1007/978-3-030-94399-8_29

Google Scholar

[17] B. M. Randles, I. V. Pasquetto, M. S. Golshan, C. L. Borgman. Using the Jupyter Notebook as a Tool for Open Science: An Empirical Study. In: 2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL), Toronto, Canada, 2017.

DOI: 10.1109/jcdl.2017.7991618

Google Scholar

[18] R. Arista, F. Mas, D. Morales-Palma, D. Ernadote, M. Oliva, C. Vallellano. Evaluation of a Commercial Model Lifecycle Management (MLM) Tool to Support Models for Manufacturing (MfM) Methodology. In: Product Lifecycle Management, PLM in Transition Times: The Place of Humans and Transformative Technologies, PLM 2022. IFIP Advances in Information and Communication Technology, 667. Springer, Cham, 2022.

DOI: 10.1007/978-3-031-25182-5_65

Google Scholar