Digital twin-based process reuse and evaluation approach for smart process planning

Digital twin-driven product design, manufacturing and service with big data

Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., & Sui, F. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-017-0233-1 · Cited by 2,920

Digital twin and big data towards smart manufacturing and Industry 4.0: 360 degree comparison

Qi, Q., & Tao, F. (2018) · IEEE Access · doi:10.1109/access.2018.2793265 · Cited by 1,716

Digital twin-based smart production management and control framework for the complex product assembly shop-floor

Zhuang, C., Liu, J., & Xiong, H. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-018-1617-6 · Cited by 700

Toward a Digital Twin for real-time geometry assurance in individualized production

Söderberg, R., Wärmefjord, K., Carlson, J. S., & Lindkvist, L. (2017) · CIRP Annals · doi:10.1016/j.cirp.2017.04.038 · Cited by 543

A Digital Twin-Based Approach for Designing and Multi-Objective Optimization of Hollow Glass Production Line

Zhang, H., Liu, Q., Chen, X., Zhang, D., & Leng, J. (2017) · IEEE Access · doi:10.1109/access.2017.2766453 · Cited by 471

Engineers' CAx education—it's not only CAD

Dankwort, C. W., Weidlich, R., Guenther, B., & Blaurock, J. (2004) · Computer-Aided Design · doi:10.1016/j.cad.2004.02.011 · Cited by 117

A new heuristic for integrated process planning and scheduling in reconfigurable manufacturing systems

Bensmaïne, A., Dahane, M., & Benyoucef, L. (2014) · International Journal of Production Research · doi:10.1080/00207543.2013.878056 · Cited by 99

Paradigm shift: unified and associative feature-based concurrent and collaborative engineering

Ma, Y., Chen, G., & Thimm, G. (2008) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-008-0128-y · Cited by 95

Capturing and reusing knowledge in engineering change management: A case of automobile development

Lee, H. J., Ahn, H. J., Kim, J. W., & Park, S. J. (2006) · Information Systems Frontiers · doi:10.1007/s10796-006-9009-0 · Cited by 89

Integrated manufacturing features and Design-for-manufacture guidelines for reducing product cost under CAD/CAM environment

Hoque, A., Halder, P. K., Parvez, M., & Szecsi, T. (2013) · Computers & Industrial Engineering · doi:10.1016/j.cie.2013.08.016 · Cited by 74

A hybrid hint-based and graph-based framework for recognition of interacting milling features

Rahmani, K., & Behrooz Arezoo, B. (2006) · Computers in Industry · doi:10.1016/j.compind.2006.07.001 · Cited by 73

A collaborative system for capturing and reusing in-context design knowledge with an integrated representation model

Peng, G., Wang, H., Zhang, H., Zhao, Y., & Johnson, A. L. (2017) · Advanced Engineering Informatics · doi:10.1016/j.aei.2016.12.007 · Cited by 65

An artificial intelligence planning approach to manufacturing feature recognition

Marchetta, M. G., & Forradellas, R. (2009) · Computer-Aided Design · doi:10.1016/j.cad.2009.11.007 · Cited by 53

A new process knowledge representation approach using parameter flow chart

Chen, W. L., Xie, S. Q., Zeng, F. F., & Li, B. (2010) · Computers in Industry · doi:10.1016/j.compind.2010.05.016 · Cited by 52

An effective hybrid graph and genetic algorithm approach to process planning optimization for prismatic parts

Huang, W., Hu, Y., & Cai, L. (2011) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-011-3870-9 · Cited by 50

Automatic process planning of mold components with integration of feature recognition and group technology

Jong, W., Lai, P.-J., Chen, Y., & Ting, Y.-H. (2014) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-014-6627-4 · Cited by 46

Integration of process planning and scheduling using a hybrid GA/PSO algorithm

Yu, M., Zhang, Y., Chen, K., & Zhang, D. (2014) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-014-6669-7 · Cited by 46

Process comprehension for shopfloor manufacturing knowledge reuse

Zhang, X., Nassehi, A., Safaieh, M., & Newman, S. T. (2013) · International Journal of Production Research · doi:10.1080/00207543.2012.757669 · Cited by 45

A flexible and effective NC machining process reuse approach for similar subparts

Huang, R., Zhang, S., Xu, C., Zhang, X., & Zhang, C. (2014) · Computer-Aided Design · doi:10.1016/j.cad.2014.10.004 · Cited by 43

Toward Effective Mechanical Design Reuse: CAD Model Retrieval Based on General and Partial Shapes

Li, M., Zhang, Y., Fuh, J. Y. H., & Qiu, Z. M. (2009) · Journal of Mechanical Design · doi:10.1115/1.4000253 · Cited by 41

Integrated manufacturing process planning and control based on intelligent agents and multi-dimension features

Liu, C., Li, Y., & Shen, W. (2014) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-014-6246-0 · Cited by 36

A knowledge base model for complex forging die machining

Mawussi, B. K., & Tapie, L. (2011) · Computers & Industrial Engineering · doi:10.1016/j.cie.2011.02.016 · Cited by 34

Graph based automatic process planning system for multi-tasking machine

Zhu, J. M., Kato, M., Tanaka, T., YOSHIOKA, H., & Saito, Y. (2015) · Journal of Advanced Mechanical Design Systems and Manufacturing · doi:10.1299/jamdsm.2015jamdsm0034 · Cited by 31

Knowledge reuse in manufacturability analysis

Cochrane, S., Young, R. I. M., Case, K., Harding, J. A., Gao, J. X., Dani, S. S., & Baxter, D. (2007) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2007.07.003 · Cited by 31

Content-Based Classification of CAD Models with Supervised Learning

Ip, C. Y., & Regli, W. C. (2005) · Computer-Aided Design and Applications · doi:10.1080/16864360.2005.10738325 · Cited by 27

Feature-based modelling and process parameters selection in a CAPP system for prismatic micro parts

Kumar, S. P. L., Jerald, J., & Kumanan, S. (2014) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2014.953586 · Cited by 22

An approach to mapping machining feature to manufacturing feature volume based on geometric reasoning for process planning

Liu, J., Liu, X., Cheng, Y., & Ni, Z. (2015) · Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · doi:10.1177/0954405415585377 · Cited by 22

A minimax p-robust optimization approach for planning under uncertainty

Seo, K.-K., Kim, J., & Chung, B. D. (2015) · Journal of Advanced Mechanical Design Systems and Manufacturing · doi:10.1299/jamdsm.2015jamdsm0067 · Cited by 22

Dealing with feature interactions for prismatic parts in STEP-NC

Mokhtar, A., Xu, X. W., & Lazcanotegui, I. (2008) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-008-0144-y · Cited by 21

Recognition of interacting volumetric features using 2D hints

Sormaz, D. N., & Tennety, C. (2010) · Assembly Automation · doi:10.1108/01445151011029763 · Cited by 18

Decomposition of interacting machining features based on the reasoning on the design features

Zheng, Y., Taib, J. M., & Tap, M. M. (2011) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-011-3385-4 · Cited by 16

Automatic generation of in-process models based on feature working step and feature cutter volume

Li, J., Chen, Z., & Yan, X. (2013) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-013-5507-7 · Cited by 16

A flexible process information reuse method for similar machining feature

Liu, J., Zhou, H., Xiaojun, L., & Jing, X. (2017) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-017-0131-6 · Cited by 15

An intelligent process planning system for micro turn-mill parts

Kumar, S. P. L., Jerald, J., & Kumanan, S. (2014) · International Journal of Production Research · doi:10.1080/00207543.2014.910626 · Cited by 14

Drive geometry construction method of machining features for aircraft structural part numerical control machining

Wang, W., Li, Y., & Tang, L. (2014) · Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · doi:10.1177/0954405413516953 · Cited by 13

A geometry search approach in case-based tool reuse for mould manufacturing

Li, Z., Zhou, X., Liu, W., & Kong, C. (2015) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-015-6820-0 · Cited by 13

A systematic method for the automatic update and propagation of the machining process models in the process modification

Liu, J., Liu, X., Cheng, Y., & Ni, Z. (2015) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-015-7371-0 · Cited by 13

Similarity-Based Retrieval of CAD Solid Models for Automated Reuse of Machining Process Plans

Marefat, M. M., & Pitta, C. (2007) · IEEE International Conference on Automation Science and Engineering (CASE) · doi:10.1109/coase.2007.4341835 · Cited by 7

Digital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues

Lu, Y., Liu, C., Wang, K. I., Huang, H., & Xu, X. W. (2019) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2019.101837 · Cited by 1,753

Review of digital twin applications in manufacturing

Cimino, C., Negri, E., & Fumagalli, L. (2019) · Computers in Industry · doi:10.1016/j.compind.2019.103130 · Cited by 874

A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives

Lim, K. Y. H., Zheng, P., & Chen, C.-H. (2020) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-019-01512-w · Cited by 700

The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities

Rathore, M. M., Shah, S. A., Shukla, D., Bentafat, E., & Bakiras, S. (2021) · IEEE Access · doi:10.1109/access.2021.3060863 · Cited by 616

Digital twin-driven rapid reconfiguration of the automated manufacturing system via an open architecture model

Leng, J., Liu, Q., Ye, S., Jing, J., Wang, Y., Zhang, C., Zhang, D., & Chen, X. (2019) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2019.101895 · Cited by 343

Dynamic Evaluation Method of Machining Process Planning Based on Digital Twin

Liu, J., Zhou, H., Liu, X., Tian, G., Wu, M., Cao, L., & Wang, W. (2019) · IEEE Access · doi:10.1109/access.2019.2893309 · Cited by 167

Digital twin driven process design evaluation

Liu, X., Liu, J., Zhou, H., & Ni, Z. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-818918-4.00012-9 · Cited by 1

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

Liu, J., Zhao, P., Jing, X., Cao, X., Sheng, S., Zhou, H., Liu, X., & Feng, F. (2021) · International Journal of Production Research · doi:10.1080/00207543.2021.1887531 · Cited by 50

Defining a feature-level digital twin process model by extracting machining features from MBD models for intelligent process planning

Li, J., Zhou, G., Zhang, C., Jun-sheng, H., Chang, F., & Matta, A. (2024) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-024-02406-2 · Cited by 16

The development of a digital twin for machining processes for the application in aerospace industry

Hänel, A., Schnellhardt, T., Wenkler, E., Nestler, A., Brosius, A., Corinth, C., Fay, A., & Ihlenfeldt, S. (2020) · Procedia CIRP · doi:10.1016/j.procir.2020.04.017 · Cited by 91