Dynamic design method of digital twin process model driven by knowledge-evolution machining features

Machining plan is the core of guiding manufacturing production and is regarded as one of the keys to ensure the quality of product processing. Existing process design methods are inefficient to qui...

[1]  Jie Zhang,et al.  The modelling and operations for the digital twin in the context of manufacturing , 2018, Enterp. Inf. Syst..

[2]  Christophe Kolski,et al.  Enhanced visual data mining process for dynamic decision-making , 2016, Knowl. Based Syst..

[3]  Weiming Shen,et al.  Agent-based collaborative product design engineering: An industrial case study , 2006, Comput. Ind..

[4]  Guanghui Zhou,et al.  Deep learning-enabled intelligent process planning for digital twin manufacturing cell , 2020, Knowl. Based Syst..

[5]  Yajun Zhang,et al.  A survey of knowledge representation methods and applications in machining process planning , 2018, The International Journal of Advanced Manufacturing Technology.

[6]  I. Musevic Nematic Liquid-Crystal Colloids , 2017, Materials.

[7]  Chao Zhang,et al.  Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing , 2019, Int. J. Prod. Res..

[8]  Fei Tao,et al.  Make more digital twins , 2019, Nature.

[9]  Aydin Nassehi,et al.  Process comprehension for shopfloor manufacturing knowledge reuse , 2013 .

[10]  Tianliang Hu,et al.  Design and development of a CNC machining process knowledge base using cloud technology , 2016, The International Journal of Advanced Manufacturing Technology.

[11]  Zhonghua Ni,et al.  A new method of reusing the manufacturing information for the slightly changed 3D CAD model , 2018, J. Intell. Manuf..

[12]  Xiaojun Liu,et al.  Dynamic Evaluation Method of Machining Process Planning Based on Digital Twin , 2019, IEEE Access.

[13]  Lei Qi,et al.  Hybrid knowledge model of process planning and its green extension , 2016 .

[14]  Zhuoning Chen,et al.  Automatic generation of in-process models based on feature working step and feature cutter volume , 2014 .

[15]  Xiaojun Liu,et al.  The Modeling and Using Strategy for the Digital Twin in Process Planning , 2020, IEEE Access.

[16]  Chaoyang Zhang,et al.  Digital twin-driven rapid reconfiguration of the automated manufacturing system via an open architecture model , 2020, Robotics Comput. Integr. Manuf..

[17]  Lihui Wang,et al.  Sequencing of interacting prismatic machining features for process planning , 2007, Comput. Ind..

[18]  Neng Wan,et al.  Research on the knowledge recognition and modeling of machining feature geometric evolution , 2015 .

[19]  Parag Vichare,et al.  Systematic modeling and reusing of process knowledge for rapid process configuration , 2008 .

[20]  Qiang Liu,et al.  Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system , 2019, Int. J. Prod. Res..

[21]  Laurent Tapie,et al.  A knowledge base model for complex forging die machining , 2011, Comput. Ind. Eng..

[22]  Hao Li,et al.  Data-Mining for Processes in Chemistry, Materials, and Engineering , 2019, Processes.

[23]  B. Guyuron,et al.  Factors Contributing to the Facial Aging of Identical Twins , 2009, Plastic and reconstructive surgery.

[24]  Rong Mo,et al.  Change and Maintenance Method for 3D Machining Procedure Model Based on Design Structure Matrix , 2018, Int. J. Pattern Recognit. Artif. Intell..

[25]  Andrew Y. C. Nee,et al.  Digital twin-driven product design framework , 2019, Int. J. Prod. Res..

[26]  Jae Kwan Kim,et al.  Ontology-based modeling of process selection knowledge for machining feature , 2013 .

[27]  He Zhang,et al.  Digital Twin in Industry: State-of-the-Art , 2019, IEEE Transactions on Industrial Informatics.

[28]  Yan Yang,et al.  A knowledge generation mechanism of machining process planning using cloud technology , 2019, J. Ambient Intell. Humaniz. Comput..

[29]  Xiaojun Liu,et al.  An approach to mapping machining feature to manufacturing feature volume based on geometric reasoning for process planning , 2017 .

[30]  Xionghui Zhou,et al.  A feasible approach to the integration of CAD and CAPP , 2007, Comput. Aided Des..

[31]  Rui Huang,et al.  Structured modeling of heterogeneous CAM model based on process knowledge graph , 2018 .

[32]  Xiaojun Liu,et al.  Digital twin-based process reuse and evaluation approach for smart process planning , 2018, The International Journal of Advanced Manufacturing Technology.

[33]  Liu Xiaojun,et al.  A flexible process information reuse method for similar machining feature , 2017 .

[34]  Sang Do Noh,et al.  Digital twin-based cyber physical production system architectural framework for personalized production , 2019, The International Journal of Advanced Manufacturing Technology.

[35]  Abid Ali Khan,et al.  Object Oriented Case Representation for CBR Application in Structural Analysis , 2015, Appl. Artif. Intell..

[36]  W. L. Chen,et al.  A new process knowledge representation approach using parameter flow chart , 2011, Comput. Ind..