An ontology self-learning approach for CNC machine capability information integration and representation in cloud manufacturing

Bo-Hu, 2010, Cloud manufacturing: a new service-oriented networked manufacturing model, Comput. Integr. Manuf. Syst., 16, 1 Xun, 2012, From cloud computing to cloud manufacturing, Robot. Comput. Integr. Manuf., 28, 75, 10.1016/j.rcim.2011.07.002 Yong-Liang, 2012, Key technologies of manufacturing capability modeling in cloud manufacturing mode, Comput. Integr. Manuf. Syst., 18, 1357 Yong, 2020, A survey on industrial information integration 2016-2019, J. Ind. Integr. Manag., 5, 33, 10.1142/S2424862219500167 Xu, 2015 Xu, 2020, Industrial information integration-an emerging subject in industrialization and informatization process, J. Ind. Inf. Integr., 17 Sérgio, 2020, Knowledge-based expert system to support the semantic interoperability in smart manufacturing, Comput. Ind., 115, 1 Fraga, 2020, Ontology-based solutions for interoperability among product lifecycle management systems: a systematic literature review, J. Ind. Inf. Integr., 20 Zhen-Jun, 2020, An ontology for representing knowledge of decision interactions in decision-based design, Comput. Ind., 114, 1 Zhuoyu, 2020, Smart manufacturing and DVSM based on an ontological approach, Comput. Ind., 117, 1 Sérgio, 2020, Knowledge-based expert system to support the semantic interoperability in smart manufacturing, Comput. Ind., 115, 1 Yuanyuan, 2017, An interoperable knowledge base for manufacturing resource and service capability, Int. J. Manuf. Res., 12, 20, 10.1504/IJMR.2017.083650 Hai, 2020, Selection method of machine tool resources in cloud manufacturing environment, Acta Aeronaut. Astronaut. Sin., 41, 623540 Li, 2019, A metadata based manufacturing resource ontology modeling in cloud manufacturing systems, J. Ambient Intell. Hum. Comput., 10, 1039, 10.1007/s12652-018-0964-3 Bao, 2021, The ontology-based modeling and evolution of digital twin for assembly workshop, Int. J. Adv. Manuf. Technol., 1 Feng, 2008, Networked manufacturing resources modeling and information integration based on physical manufacturing unit, Comput. Integr. Manuf. Syst., 14, 667 L. Xiaobin. Study on optimal configuration of machine tool in cloud manufacturing. PhD thesis of University of Chongqin, 2015. [in Chinese]. Wenjun, 2015, Dynamic modeling of manufacturing equipment capability using condition information in cloud manufacturing, J. Manuf. Sci. Eng., 137, 1 Järvenpää, 2018, Formal resource and capability models supporting Re-use of manufacturing resources, Procedia Manuf., 19, 87, 10.1016/j.promfg.2018.01.013 Eeva, 2019, The development of an ontology for describing the capabilities of manufacturing resources, J. Intell. Manuf., 30, 959, 10.1007/s10845-018-1427-6 ISO 10303-1: industrial automation systems and integration product data representation and exchange-overview and fundamental principles, international standard, ISO TC184/SC4, 1994. ISO. ISO 14649-1: industrial automation systems and integration-physical device control-data model for computerized numerical controllers-part 1: overview and fundamental principles, ISO, 2003. ISO. ISO10303-239: industrial automation systems and integration-product data representation and exchange-part 239: application protocol: product life cycle support. ISO, 2012. Von, 2008 Kjellberg, 2009, The machine tool model-a core part of the digital factory, CIRP Ann. Manuf. Technol., 58, 425, 10.1016/j.cirp.2009.03.035 Yang, 2008, Modeling machine tool data in support of STEP-NC based manufacturing, Int. J. Comput. Integr. Manuf., 21, 745, 10.1080/09511920701810691 Parag, 2009, unified manufacturing resource model for representing CNC machining systems, Robot. Comput. Integr. Manuf., 25, 999, 10.1016/j.rcim.2009.04.014 Jumyung, 2016, STEP-NC machine tool data model and its applications, Int. J. Comput. Integr. Manuf., 29, 1058, 10.1080/0951192X.2015.1130264 Yong, 2016, Industrial information integration-a literature review 2006–2015, J. Ind. Inf. Integr., 2, 30 Somodevilla, 2018, An overview on ontology learning tasks, Computación y Sistemas, 22, 137, 10.13053/cys-22-1-2790 Fiorentini, 2007, 7436 Krima, S. , Barbau, R. , Fiorentini, X. , Rachuri, S. and Sriram, R. (2009), OntoSTEP: OWL-DL Ontology for STEP, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD, [online],https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=901544 (Accessed October 27, 2021). Raphael, 2012, OntoSTEP: enriching product model data using ontologies, Comput. Aided Des., 44, 575, 10.1016/j.cad.2012.01.008 Yuqian, 2014, Ontology for manufacturing resources in a cloud environment, Int. J. Manuf. Res., 9, 448 Yuqian, 2019, ManuService ontology: a product data model for service-oriented business interactions in a cloud manufacturing environment, J. Intell. Manuf., 30, 317, 10.1007/s10845-016-1250-x Wang, 2014, Manufacturing task semantic modeling and description in cloud manufacturing system, Int. J. Adv. Manuf. Technol., 71, 2017, 10.1007/s00170-014-5607-z Ye, 2018, Design and development of a CNC machining process knowledge base using cloud technology, Int. J. Adv. Manuf. Technol., 94, 9, 10.1007/s00170-016-9338-1 Wang, 2019, Developing an energy-efficient process planning system for prismatic parts via STEP-NC, Int. J. Adv. Manuf. Technol. Zhang, 2020, Learning domain ontologies from engineering documents for manufacturing knowledge reuse by a biologically inspired approach, Int. J. Adv. Manuf. Technol., 106, 2535, 10.1007/s00170-019-04772-1 Rajpathak, 2020, An integrated framework for automatic ontology learning from unstructured repair text data for effective fault detection and isolation in automotive domain, Comput. Ind., 123 Park, 2020, SAX-ARM: deviant event pattern discovery from multivariate time series using symbolic aggregate approximation and association rule mining, Expert Syst. Appl., 141, 10.1016/j.eswa.2019.112950 Zhou, 2017, Thinking process rules extraction for manufacturing process design, Adv. Manuf., 5, 321, 10.1007/s40436-017-0205-6 Dogan, 2021, Machine learning and data mining in manufacturing, Expert Syst. Appl., 166