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Current Issues in Flexible Manufacturing Using Multicriteria Decision Analysis and Ontology Based Interoperability in an Advanced Manufacturing Environment

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Production Research (ICPR-Americas 2020)

Abstract

The manufacturing industry is undergoing a major transformation based on the emerging industry 4.0 technologies, such as cloud computing, big data, internet of things and cyber-physical systems. These novelty technologies aim at providing central management for the user’s flexible manufacturing requirements and information. Also, the advent of these technologies has transformed the process planning and became crucial for the building of knowledge-based process planning environments. However, current praxis cannot deal with all semantic issues within this new paradigm, as requirements must be clear, consistent, measurable, stand-alone, testable, unambiguous, unique and verifiable. In this context, multicriteria decision analysis models have gained focus of the scientific and industrial communities as a support tool for the decision-making process in the product development and advanced manufacturing as these processes excel in environments with numerous and conflicting alternatives, providing the optimal alternative. Therefore, the main objective of this research is to highlight the current issues and research tendencies regarding ontology-based interoperability systems, multicriteria decision analysis and their integration. To achieve this goal, it will be applied a literature review on the targeted technologies, discussing the current tendencies of the field and the main issues regarding their implementation and integration. Finally, the paper points themes for further research and indicates viable concepts that can compose a solution for the gaps in a systematic manner.

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References

  1. Ye, Y., Tianliang, H., Zhang, C., Luo, W.: Design and development of a CNC machining process knowledge base using cloud technology. Int. J. Adv. Manuf. Technol. 94(9–12), 3413–3425 (2018)

    Article  Google Scholar 

  2. Leite, A.F.C.S.M., Canciglieri, M.B., Szejka, A.L., Junior, O.C.: The reference view for semantic interoperability in integrated product development process: The conceptual structure for injecting thin walled plastic products. J. Indus. Inf. Integr. 7, 13–23 (2017)

    Google Scholar 

  3. Canciglieri, M.B., de Moura Leite, A.F.C.S., Szejka, A.L., Junior, O.C.: An approach for dental prosthesis design and manufacturing through rapid manufacturing technologies. Int. J. Comput. Integr. Manuf. 32(9), 832–847 (2019)

    Article  Google Scholar 

  4. Berners-Lee, T., Fischetti, M.: Weaving the Web, Chapter 12. HarperSanFrancisco (1999). ISBN: 978-0-06-251587-2

    Google Scholar 

  5. Ceravolo, P., et al.: Big data semantics. J. Data Semant. 7(2), 65–85 (2018). https://doi.org/10.1007/s13740-018-0086-2

    Article  Google Scholar 

  6. Khan, Z.M.A., Saeidlou, S., Saadat, M.: Ontology-based decision tree model for prediction in a manufacturing network. Prod. Manuf. Res. 7(1), 335–349 (2019). https://doi.org/10.1080/21693277.2019.1621228

    Article  Google Scholar 

  7. Li, X., Zhang, S., Huang, R., Huang, B., Changhong, X., Zhang, Y.: A survey of knowledge representation methods and applications in machining process planning. Int. J. Adv. Manuf. Technol. 98(9–12), 3041–3059 (2018)

    Article  Google Scholar 

  8. Chungoora, N., Young, R.I.M.: Semantic reconciliation across design and manufacturing knowledge models: A logic-based approach. Appl. Ontol. 6(4), 295–315 (2011)

    Article  Google Scholar 

  9. Jelokhani-Niaraki, M.: Knowledge sharing in web-based collaborative multicriteria spatial decision analysis: An ontology-based multi-agent approach. Comput. Environ. Urban Syst. 72(May), 104–123 (2018). https://doi.org/10.1016/j.compenvurbsys.2018.05.012

    Article  Google Scholar 

  10. Du, Juan et al.: An ontology and multi-agent based decision support framework for prefabricated component supply chain. Inf. Syst. Front. 22, 1467–1485 (2019)

    Google Scholar 

  11. Jelokhani-Niaraki, M., Sadeghi-Niaraki, A., Choi, S.M.: Semantic interoperability of GIS and MCDA tools for environmental assessment and decision making. Environ. Model Softw. 100, 104–122 (2018). https://doi.org/10.1016/j.envsoft.2017.11.011

    Article  Google Scholar 

  12. Li, X., Zhang, S., Huang, R. et al.: Structured modeling of heterogeneous CAM model based on process knowledge graph. Int. J. Adv. Manuf. Technol. 96, 4173–4193 (2018). https://doi.org/10.1007/s00170-018-1862-8

  13. Bagherifard, K., Rahmani, M., Nilashi, M., Rafe, V.: Performance improvement for recommender systems using ontology. Telematics Inf. 34(8), 1772–1792 (2017). https://doi.org/10.1016/j.tele.2017.08.008

    Article  Google Scholar 

  14. Lahdhiri, H., et al.: Supervised process monitoring and fault diagnosis based on machine learning methods. Int. J. Adv. Manuf. Technol. 102(5–8), 2321–2337 (2019)

    Article  Google Scholar 

  15. Peko, I., Gjeldum, N., Bilić, B.: Application of AHP, Fuzzy AHP and PROMETHEE method in solving additive manufacturing process selection problem. Tehnicki Vjesnik 25(2), 453–461 (2018)

    Google Scholar 

  16. Almeida, D., Teixeira, A., Alencar, M.H., Garcez, T.V., Ferreira, R.J.P.: A systematic literature review of multicriteria and multi-objective models applied in risk management. IMA J. Manage. Math. 28(2), 153–184 (2017)

    Article  MathSciNet  Google Scholar 

  17. Park, J.W., Kang, B.S.: Comparison between regression and artificial neural network for prediction model of flexibly reconfigurable roll forming process. Int. J. Adv. Manuf. Technol. 101(9–12), 3081–3091 (2019)

    Article  Google Scholar 

  18. Chourabi, Z., Khedher, F., Babay, A., Cheikhrouhou, M.: Multi-criteria decision making in workforce choice using AHP, WSM and WPM. J. Textile Inst. 110(7), 1092–1101 (2019). https://doi.org/10.1080/00405000.2018.1541434

    Article  Google Scholar 

  19. Rezaei, J.: Best-worst multi-criteria decision-making method. Omega (United Kingdom) 53, 49–57 (2015). https://doi.org/10.1016/j.omega.2014.11.009

    Article  Google Scholar 

  20. Alsina, E.F., Chica, M., Trawiński, K., Regattieri, A.: On the use of machine learning methods to predict component reliability from data-driven industrial case studies. Int. J. Adv. Manuf. Technol. 94(5–8), 2419–2433 (2018)

    Article  Google Scholar 

  21. Segreto, T., Teti, R.: Machine learning for in-process end-point detection in robot-assisted polishing using multiple sensor monitoring. Int. J. Adv. Manuf. Technol. 103(9–12), 4173–4187 (2019)

    Article  Google Scholar 

  22. Trächtler, A., Denkena, B., Thoben, K.-D.: Editorial: system-integrated intelligence – new challenges for product and production engineering. Procedia 26, 1–3 (2016). http://dx.doi.org/10.1016/j.protcy.2016.08.001

  23. Tang, D., Zheng, K., Zhang, H., Sang, Z., Zhang, Z., Xu, C., Espinosa-Oviedob, J.A., Vargas-Solar, G., Zechinelli-Martini, J.L.: Using autonomous intelligence to build a smart shop floor. Int. J. Adv. Manuf. Technol. 94(5–8), 1597–1606 (2018)

    Article  Google Scholar 

  24. Razia Sulthana, A., Ramasamy, S.: Ontology and context based recommendation system using neuro-fuzzy classification. Comput. Electr. Eng. 74, 498–510 (2019). https://doi.org/10.1016/j.compeleceng.2018.01.034

    Article  Google Scholar 

  25. Zhou, J., Yao, X.: Hybrid teaching–learning-based optimization of correlation-aware service composition in cloud manufacturing. Int. J. Adv. Manuf. Technol. 91(9–12), 3515–3533 (2017)

    Article  Google Scholar 

  26. Navarro, I.J,, Yepes, V., Martí, J.V.: A review of multicriteria assessment techniques applied to sustainable Infrastructure design. Adv. Civil Eng. 2019, 16 p. (2019). Article ID 6134803. https://doi.org/10.1155/2019/6134803

  27. Saeidlou, S., Saadat, M., Sharifi, E.A., Jules, G.D.: Agent-based distributed manufacturing scheduling: an ontological approach. Cogent Eng. 6(1), 1–23 (2019). https://doi.org/10.1080/23311916.2019.1565630

    Article  Google Scholar 

  28. Saeidlou, S., Saadat, M., Jules, G.D.: Knowledge and agent-based system for decentralised scheduling in manufacturing. Cogent Eng. 6(1), 1–19 (2019). https://doi.org/10.1080/23311916.2019.1582309

    Article  Google Scholar 

  29. Asghar, E., Zaman, U.K., Baqai, A.A., Homri, L.: Optimum machine capabilities for reconfigurable manufacturing systems. Int. J. Adv. Manuf. Technol. 95(9–12), 4397–4417 (2018)

    Article  Google Scholar 

  30. Sevinç, A., Şeyda, G., Tamer, E.: Analysis of the difficulties of SMEs in industry 4.0 applications by analytical hierarchy process and analytical network process. Processes 6(12), 264 (2018)

    Google Scholar 

  31. Qu, Y.J., et al.: Smart manufacturing systems: state of the art and future trends. Int. J. Adv. Manuf. Technol. 103(9–12), 3751–3768 (2019)

    Article  Google Scholar 

  32. Wang, L., et al.: Distributed manufacturing resource selection strategy in cloud manufacturing. Int. J. Adv. Manuf. Technol. 94(9–12), 3375–3388 (2018)

    Article  Google Scholar 

  33. Wang, S., Wan, J., Li, D., Liu, C.: Knowledge reasoning with semantic data for real-time data processing in smart factory. Sensors (Switzerland) 18(2), 1–10 (2018)

    Google Scholar 

  34. Widiyati, M.: “No Titleענף הקיווי: תמונת מצב.” עלון הנוטע 66: 37–39 (2012)

    Google Scholar 

  35. Wu, Z., et al.: Towards a semantic web of things: a hybrid semantic annotation, extraction, and reasoning framework for cyber-physical system. Sensors (Switzerland) 17(2), 403 (2017)

    Google Scholar 

  36. Hamdi, F., Ghorbel, A., Masmoudi, F., Dupont, L.: Optimization of a supply portfolio in the context of supply chain risk management: literature review. J. Intell. Manuf. 29(4), 763–788 (2018)

    Article  Google Scholar 

  37. Zhang, Y., Luo, X., Zhang, B., Zhang, S.: Semantic approach to the automatic recognition of machining features. Int. J. Adv. Manuf. Technol. 89(1–4), 417–437 (2017)

    Article  Google Scholar 

  38. Zhao, Y., et al.: Dynamic and unified modelling of sustainable manufacturing capability for industrial robots in cloud manufacturing. Int. J. Adv. Manuf. Technol. 93(5–8), 2753–2771 (2017)

    Article  Google Scholar 

  39. Kumar, S., Dhingra, A.K., Singh, B.: Kaizen selection for continuous improvement through VSM-Fuzzy-TOPSIS in small-scale enterprises (2018)

    Google Scholar 

  40. Zhou, Q., Yan, P., Liu, H. et al.: Research on a configurable method for fault diagnosis knowledge of machine tools and its application. Int. J. Adv. Manuf. Technol. 95, 937–960 (2018). https://doi.org/10.1007/s00170-017-1268-z

    Article  Google Scholar 

  41. Liu, K., El-Gohary, N.: Ontology-based semi-supervised conditional random fields for automated information extraction from bridge inspection reports. Autom. Constr. 81, 313–327 (2017). https://doi.org/10.1016/j.autcon.2017.02.003

    Article  Google Scholar 

  42. Roy, B.: Paradigms and challenges. In: Figueira, J., Greco, S., Ehrgott, M. (eds.) Multiple Criteria Decision Analysis: State of the Art Surveys, vol. 78, pp. 3–24. Springer, New York (2005)

    Chapter  Google Scholar 

  43. Kodikara, P.N.: Multi-objective optimal operation of urban water supply systems, Ph.D thesis. Victoria University (2008)

    Google Scholar 

  44. Roy, B.: Multicriteria Methodology for Decision Aiding. Springer, Boston (1996)

    Book  Google Scholar 

  45. Jacquet-Lagreze, E., Siskos, Y.: Preference disaggregation: 20 years of MCDA experience. Eur. J. Oper. Res. 130, 233–245 (2001)

    Article  Google Scholar 

  46. Martel, J.-M., Matarazzo, B.: Other Outranking Approaches. Multiple Criteria Decision Analysis: State of the Art Surveys, vol. 78, pp. 197–259. Springer, New York (2005)

    Google Scholar 

  47. Saaty, T.L.: The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill International Book Co, New York, London (1980)

    MATH  Google Scholar 

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Correspondence to M. B. Canciglieri .

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Canciglieri, M.B., Leite, A.F.C.S.M., Rocha Loures, E.F., Canciglieri, O., Monfared, R.P., Goh, Y.M. (2021). Current Issues in Flexible Manufacturing Using Multicriteria Decision Analysis and Ontology Based Interoperability in an Advanced Manufacturing Environment. In: Rossit, D.A., Tohmé, F., Mejía Delgadillo, G. (eds) Production Research. ICPR-Americas 2020. Communications in Computer and Information Science, vol 1407. Springer, Cham. https://doi.org/10.1007/978-3-030-76307-7_28

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  • DOI: https://doi.org/10.1007/978-3-030-76307-7_28

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