[1] Y B Wang, K J Hong, J Zou, et al. A CNN-based visual sorting system with cloud-edge computing for flexible manufacturing systems. IEEE Transactions on Industrial Informatics, 2020: 16(7): 4726-4735.
[2] Y Huang, B H Lu, W H Zhao. Application of cloud computing in intelligent machine tool control system. Chinese Journal of Mechanical Engineering, 2018, 54(8): 210-216. (in Chinese)
[3] D M Zhang, J Z Zhang, H W Huang, et al. Machine learning-based prediction of soil compression modulus with application of 1D settlement. Journal of Zhejiang University-Science A, 2020, 21(6): 430-444.
[4] X Y Li, J Jie. Ballistic behavior of high strength steel targets during high speed impact of projectile. Journal of Iron and Steel Research, 2020, 32(5): 429-436. (in Chinese)
[5] L B Zhang, H P Lv, D P Tan, et al. An adaptive quantum genetic algorithm for task sequence planning of complex assembly systems. Electronics Letters, 2018, 54(14): 870-871.
[6] Y Z He, L B Zhang, D P Tan, et al. Research on intelligent microgrid monitoring system based on DPWS. Acta Energiae Solaris Sinica, 2015, 36(12): 2979-2985. (in Chinese)
[7] L B Zhang, P H Lv, F Xu, et al. Modeling and optimization of CPN collaborative assembling tasks for low-voltage apparatus. Computer Integrated of Manufacturing Systems, 2020, 26(07): 1737-1748. (in chinese)
[8] J K Chen, Y Y Jin, Z P Zhou. Review of wound roll stress in roll-to-roll manufacturing of flexible electronics. Chinese Science Bulletin, 2019, 64(Z1): 555-565. (in Chinese)
[9] H F Wang, F Zhang, Y F Tong. Digital design and manufacturing technology. Harbin : Harbin Engineering University Press, 2015. (in Chinese)
[10] Z L Cheng, W H Zhou, Z Ding, et al. Estimation of spatiotemporal response of rooted soil using a machine learning approach. Journal of Zhejiang University-Science A, 2020, 21(6): 462-477.
[11] B Zhang, L Gao, Q Xue, et al. Strengths, weaknesses, and applications of computational axial lithography in tissue engineering. Bio-Design and Manufacturing, 2020, 3: 5-6.
[12] L Zhang, Z M Yuan, D P Tan, et al. An improved abrasive flow processing method for complex geometric surfaces of titanium alloy artificial joints. Applied Sciences, 2018, 28(7): 1037.
[13] Y J Rao. Simulation and experimental research on stainless steel sawing process of metal band sawing machine. Hangzhou: Zhejiang University of Technology, 2020. (in Chinese)
[14] Behringer——The pioneer sawing sawing technology in world. Die & Mould Manufacture, 2006(2): 62-63. (in Chinese)
[15] Bellinger will launch a new sawing machine in EMO2015. Auto Manufacturing Engineer, 2015(9): 22. (in Chinese)
[16] Horizontal Band Saws - Behringer. https://www.behringersaws.com/. 2020.6.11.
[17] X R Guo. New development trend of feed motion control method of metal band sawing machine. Machine Tool & Hydraulics, 2016, 44(23): 153-155. (in Chinese)
[18] Amada Machine Tools America Corporation. https://amadamt.com/, 2020.6.11.
[19] Z Z Fang. The design and optimization of the CH360 horizontal CNC band sawing. Hangzhou: Zhejiang University of Technology, 2015. (in Chinese)
[20] Home - KASTO - Saws. Storage. And More. https://www.kasto.com/us/, 2020.6.11.
[21] Machining Products and Technologies | DANOBATGROUP. https://www.danobatgroup.com/en/products, 2020.6.11.
[22] DoALL Sawing Products. https://www.doallsaws.com/, 2020.6.11.
[23] D P Tan, L Li, Y L Zhu, et al. Critical penetration condition and Ekman suction-extraction mechanism of sink vortex. Journal of Zhejiang University-Science A, 2019, 20(1): 61-72.
[24] X X Hu, F Xu, R H Wang. Synchronous sampling-based direct current estimation method for self-sensing active magnetic bearings. Sensors, 2020, 20(12): 3497.
[25] S M Ji, J Q Ge, D P Tan, et al. Wall contact effects of particle-wall collision process in two-phase particle fluid. Journal of Zhejiang University-Science A, 2017, 18(12): 958-973.
[26] R Ferreira, A Sabbaghi, Q Huang. Automated geometric shape deviation modeling for additive manufacturing systems via Bayesian neural networks. IEEE Transactions on Automation Science and Engineering, 2020, 17(2): 584-598.
[27] Y S Hao, Y S Fan, J Zhang. Service recommendation based on description reconstruction in cloud manufacturing. International Journal of Computer Integrated Manufacturing, 2019, 32(3): 294-306.
[28] J F Lu, T Wang, L Li, et al. Dynamic characteristics and wall effects of bubble bursting in gas-liquid-solid three-phase particle flow. Processes, 2020, 8: 760.
[29] D P Tan, P Y Li, X H Pan. Application of improved HMM algorithm in slag detection system. Journal of Iron and Steel Research, International, 2009, 16(1): 1-6.
[30] Z M Liu, J Wang. Human-cyber-physical systems: concepts, challenges, and research opportunities. Frontiers of Information Technology & Electronic Engineering, 2020, 21(11): 1535-1553.
[31] C Li, Q D Xu, J Q Ge, et al. Research on the incidence of soft abrasive flow to a wall and the machining characteristics. Proceeding of Institution of Mechanical Engineers Part B: Journal of Engineering Manufacture, https://doi.org/10.1177/0954405420937559.
[32] Y Guo, N Wang, Z Y Xu, et al. The internet of things-based decision support system for information processing in intelligent manufacturing using data mining technology. Mechanical Systems and Signal Processing, 2020, 142: 106630.
[33] D P Tan, L B Zhang, Q L Ai. An embedded self-adapting network service framework for networked manufacturing system. Journal of Intelligent Manufacturing, 2019, 30(2): 539-556.
[34] C Li, S M Ji, D P Tan. Softness abrasive flow method oriented to tiny scale mold structural surface. International Journal of Advanced Manufacturing Technology, 2012, 61(9-12): 975-987.
[35] S M Ji, X X Weng, D P Tan. Analytical method of softness abrasive two-phase flow field based on 2D model of LSM. Acta Physica Sinica, 2012, 61(1): 010205.
[36] D P Tan, Y S Ni, L B Zhang. Two-phase sink vortex suction mechanism and penetration dynamic characteristics in ladle teeming process. Journal of Iron and Steel Research, International, 2017, 24(7): 669-677.
[37] D P Tan, L Li, Z C Yin, et al. Ekman boundary layer mass transfer mechanism of free sink vortex. International Journal of Heat and Mass Transfer, 2020, 150: 119250.
[38] Q S Jiang, D P Tan, Y B Li, et al. Object detection and classification of metal polishing shaft surface defects based on convolutional neural network deep learning. Applied Sciences, 2020, 10(1): 87.
[39] J Li, S M Ji, D P Tan. Improved soft abrasive flow finishing method based on turbulent kinetic energy enhancing. Chinese Journal of Mechanical Engineering, 2017, 30(2): 301-309.
[40] L Jia, H Y Dai, Y Song. Test technology research and fatigue damage prediction of a car body based on dynamic simulation load spectrum. Journal of Zhejiang University Science A, 2020, 21(11): 923-937.
[41] Q Gao, W Wu, J G Zhi, et al. Effect of a self-rotating oxygen lance system on mass transfer between slag and molten steel. Journal of Iron and Steel Research, International, 2020, https://doi.org/10.1007/s42243-020-00515-9.
[42] L Li, D P Tan, T Wang, et al. Multiphase coupling mechanism of free surface vortex and the vibration-based sensing method. Energy, 2020, 216: 119136
[43] L Li, H Qi, Z C Yin, et al. Investigation on the multiphase sink vortex Ekman pumping effects by CFD-DEM coupling method. Powder Technology, 2020, 360: 462-480.
[44] J C Zhang, T Zhang, Y T Yang. Microstructure and properties evolution of Nb-bearing medium Cr wear-resistant cast steel during heat treatment. Journal of Iron and Steel Research, International, 2020, https://doi.org/10.1007/s42243-020-00510-0.
[45] C Li, Q D Xu, J Q Ge, et al. Study of soft abrasive flow field measurement based on particle image velocimetry. The International Journal of Advanced Manufacturing Technology, 2020, 109(7-8): 2039-2047.
[46] L Qiu, X Zeng, S M Ji, et al. Research on abrasive belt based machining technology for milling shaped aero-engine blades. Tehnicki Vjesnik - Technical Gazette, 2019, 26(5): 1353-1362.
[47] J X Wang, B Cao, X Zeng, et al. Detecting difference between process models using edge network. IEEE Access, 2019, 7: 142916-142925.
[48] D P Tan, S M Ji, M S Jin. Intelligent computer-aided instruction modeling and a method to optimize study strategies for parallel robot instruction. IEEE Transactions on Education, 2013, 56(3): 268-273.
[49] Z Y Jia, Y Q Wang, F J Wang. Research on measure-redesign-machining integration manufacturing method for complicated surface parts with high performance. Journal of Mechanical Engineering, 2013, 49(19): 126-138. (in Chinese)
[50] X P Guan, C L Chen, C L Chen, et al. Towards the integration of sensing, transmission and control for industrial network systems: Challenges and recent developments. Acta Automatica Sinica, 2019, 45(1): 27-38. (in Chinese)
[51] B Tao, X W Zhao, R P Li. Research on robotic measurement-operation-machining technology and its application. China Mechanical Engineering, 2020, 31(1): 49-56. (in Chinese)
[52] A Nascimento, R Flesch, C Flesch. Data-driven soft sensor for the estimation of sound power levels of refrigeration compressors through vibration measurements. IEEE Transactions on Industrial Electronics, 2020, 67(8): 7065-7072.
[53] N A Fountas, N M Vaxevanidis. Intelligent 3D tool path planning for optimized 3-axis sculptured surface CNC machining through digitized data evaluation and swarm-based evolutionary algorithms. Measurement, 2020, 158: 107678.
[54] B Strbac, B Acko, S Havrlisan, et al. Investigation of the effect of temperature and other significant factors on systematic error and measurement uncertainty in CMM measurements by applying design of experiments. Measurement, 2020, 158: 107692.
[55] K Scicluna, C S Staines, R Raute. Sensorless low/zero speed estimation for permanent magnet synchronous machine using a search-based real-time commissioning method. IEEE Transactions on Industrial Electronics, 2020, 67(8): 6010-6018.
[56] J X Wang, D P Tan, B Cao. An independent path-based process recommendation algorithm for improving biomedical process modeling. Electronics Letters, 2020, 56(11): 531-533.
[57] L Li, J F Lu, H Fang, et al. Lattice Boltzmann method for fluid-thermal systems: status, hotspots, trends and outlook. IEEE Access, 2020, 8: 27649-27675.
[58] X X Hu, F Xu, D P Tan, et al. A synchronous sampling-based direct current estimation method for self-sensing active magnetic bearings. Journal of Zhejiang University-Science A, 2020, 21(5): 401-405.
[59] L Zhang, J S Wang, D P Tan, et al. Gas compensation based abrasive flow processing method for complex titanium alloy surfaces. International Journal of Advanced Manufacturing Technology, 2017, 92(9-12): 3385-3397.
[60] J Q Ge, S M Ji, D P Tan, et al. A gas-liquid-solid three-phase abrasive flow processing method based on bubble collapsing. International Journal of Advanced Manufacturing Technology, 2018, 95(1-4): 1069-1085.
[61] M G Wu, C D Lu, D P Tan, et al. Effects of metal buffer layer for amorphous carbon film of 304 stainless steel bipolar plate. Thin Solid Films, 2016, 616: 507-514.
[62] D P Tan, S M Ji, Y Z Fu. An improved soft abrasive flow finishing method based on fluid collision theory. International Journal of Advanced Manufacturing Technology, 2016, 85(5): 1261-1274.
[63] Y Z Gu, D W Zuo, W M Xu. A modal analysis and optimization of physiotherapy appliance bed structure. Machine Building & Automation, 2009, 1: 36-39. (in Chinese)
[64] L Jiang, D Xiang, P Mou, et al. Study of gearbox's robust optimization design. Machinery Design & Manufacture, 2018, S1: 14-16. (in Chinese)
[65] Y H Li, Q Zang, J Zhang. Robust and optimal design of gear box for high speed train. Journal of Dalian Jiaotong University, 2015(6): 29-33. (in Chinese)
[66] J T Wang, J G Lu, B X Wang, et. al. Application of the food chain conduction response algorithm in the gearbox optimization. Computer Integrated Manufacturing Systems, 2017: 1-18. (in Chinese)
[67] C Liu, Z D Fang, X J Zhang, et al. An efficient modeling method for coupled vibration analysis of double-helical gear reduction. Noise Control Engineering Journal, 2017, 65(2): 121-137.
[68] G Belingardi, V Cuffaro, F Cura. Multibody approach for the dynamic analysis of gears transmission for an electric vehicle. Proceedings of The Institution of Mechanical Engineers Part C - Journal of Mechanical Engineering Science, 2018, 232(1): 57-65.
[69] C Osorio, G Koch, H Pinheiro, et al. Robust current control of grid-tied inverters affected by LCL filter soft-saturation. IEEE Transactions on Industrial Electronics, 2020, 67(8): 6550-6561.
[70] C Li, S M Ji, D P Tan. Multiple-loop digital control method for 400Hz inverter system based on phase feedback. IEEE Transactions on Power Electronics, 2013, 28(1): 408-417.
[71] D P Tan, T Yang, J Zhao, et al. Free sink vortex Ekman suction-extraction evolution mechanism. Acta Physica Sinica, 2016, 65(5): 054701.
[72] J W Fan, X F Wang, D J Chen, et al. Error sentivity analysis of machine tools based on mufti-body kinematic theory. Chinese High Technology Letters, 2013, 23(03): 318-324. (in Chinese)
[73] M Ge, S M Ji, D P Tan. Erosion analysis and experimental research of gas-liquid-solid soft abrasive flow polishing based on cavitation effects. International Journal of Advanced Manufacturing Technology, 2020, 9: 40. https://doi.org/10.1016/j.jamt.
[74] Y W Hu, H Chen, D D Chen, et al. A flexible hybrid PWM strategy based novel cascaded grid simulator with improved internal model repetitive controller. Frontiers of Information Technology & Electronic Engineering, 2020, https://doi.org/10.1631/FITEE.1700728.
[75] Y Y Wang, P C Ni, D H Wen, et al. Dynamic performance optimization of circular sawing machine gearbox. Applied Sciences, 2019, 9(20): 4458.
[76] X Zeng, S M Ji, M S Jin, et al. Research on dynamic characteristic of softness consolidation abrasives in machining process. International Journal of Advanced Manufacturing Technology, 2016, 82(5-8): 1115-1125.
[77] J L Chen, F Xu, D P Tan. A control method for agricultural greenhouse heating based on computational fluid dynamics and energy prediction model. Applied Energy, 2015, 141: 106-118.
[78] S H Zheng, Y K Yu, M Z Qiu, et al. A modal analysis of vibration response of a cracked fluid-filled cylindrical shell. Applied Mathematical Modelling, 2021, 91: 934-958
[79] X Zeng, S M Ji, M S Jin, et al. Investigation on machining characteristic of pneumatic wheel based on softness consolidation abrasives. International Journal of Precision Engineering and Manufacturing, 2014, 15(10): 2031-039.
[80] S C Gong, W D Huang, N L Tai, et al. Complex network based comprehensive evaluation method of topology for electro-thermal microgrid. Automation of Electric Power Systems, 2019, 43(23): 173-189. (in Chinese)
[81] Z H Wang, Z H Liu. Partial synchronization over complex networks: chimera states, remote synchronization and group synchronization. Acta Physica Sinica, 2020, 69(8): 59-72. (in Chinese)
[82] D P Tan, L B Zhang. A WP-based nonlinear vibration sensing method for invisible liquid steel slag detection. Sensors and Actuators B, 2014, 202: 1257-1269.
[83] D P Tan, L Li, Y L Zhu, et al. An embedded cloud database service method for distributed industry monitoring. IEEE Transactions on Industrial Informatics, 2018, 14(7): 2881-2893.
[84] E Y Chen, Y C Shi, G Y Xu. Evaluation and improvement of UPnP service discovery algorithm. Journal of Tsinghua University(Science and Technology), 2006. 4: 600-608. (in Chinese)
[85] R C Tang, X Feng, X Q Ding, Contest-based content adaptation algorithm and its application in UPnP AV. Journal of Jilin University (Engineering and Technology Edition), 2014, 44(5): 1441-1446. (in Chinese)
[86] C Wu, X N Wang, H L Xiao, et al. Design and implement of middleware for high performance computing environment based on message bus. Chinese High Technology Letters, 2020, 30(3): 248-258. (in Chinese)
[87] B F Wu. Design of IoT middleware based on microservices architecture. Computer Science, 2019, 46(S1): 580-604. (in Chinese)
[88] P C Xiong, Y S Fan. Middleware for consistent data interaction in distributed workflow system. Journal of Tsinghua University (Science and Technology), 2008, 7: 1213-1216. (in Chinese)
[89] D P Tan, P Y Li, X H Pan. Computer integrated manufacturing systems. Computer Integrated Manufacturing Systems, 2009, 15(1): 131-134. (in Chinese)
[90] Y Pan, S M Ji, D P Tan, et al. Cavitation based soft abrasive flow processing method. International Journal of Advanced Manufacturing Technology, 2020, 109(9): 2587-2602.
[91] L B Zhang, Y Z He, F Xu, et al. Monitoring method of micro-grid based on DPWS network middleware and Petri nets. Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(20): 163-171. (in Chinese)
[92] F Xu, Y K Yang, D P Tan, et al. Monitoring architecture of microgrid and adaptive service method based on DPWS. Automation of Electric Power Systems, 2015, 39(19): 34-53. (in Chinese)
[93] J F Lu, T Wang, L Li, et al. Dynamic characteristics and wall effects of the bubble bursting in gas-liquid-solid three-phase particle flow. Processes, 2020, 8: 760.
[94] D P Tan, P Y Li, X H Pan. Intelligent industry monitoring network architecture UPnP based. Chinese Journal of Electronics, 2008, 17(4): 607-610. (in Chinese)
[95] X Wang, S K Ong, A Y C Nee. A comprehensive survey of ubiquitous manufacturing research. International Journal of Production Research, 2019, 30(2): 539-556.
[96] China Mobile. China Mobile officially released 5G module middleware and solutions. http://m.elecfans.com/article/1167135.html, 2020. (in Chinese)
[97] L Zheng, P Y Jiang, L H Qiao, et al. Challenges and frontiers of manufacturing systems. Journal of Mechanical Engineering, 2010, 46(21): 124-136. (in Chinese)
[98] H Q Wu. New features of network society and industry challenges in the 5G era. Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition), 2020, 32(2): 171-176. (in Chinese)
[99] D P Tan, P Y Li, Y X Ji, et al. SA-ANN-based slag carry-over detection method and the embedded WME platform. IEEE Transactions on Industrial Electronics, 2013, 60(10): 4702-4713.
[100] S M Ji, F Q Xiao, D P Tan. Analytical method for softness abrasive flow field based on discrete phase model. Science China - Technological Sciences, 2010, 53(10): 2867-2877.
[101] D P Tan, S M Ji, P Y Li, et al. Development of vibration style ladle slag detection method and the key technologies. Science China-Technological Sciences, 2010, 53(9): 2378-2387.
[102] S T Chen, D P Tan. A SA-ANN-based modeling method for human cognition mechanism and the PSACO cognition algorithm. Complexity, 2018, 2018: 6264124.
[103] B H Li, X D Cai, B C Hou, et al. Computer integrated manufacturing systems. Computer Integrated Manufacturing Systems, 2019, 25(12): 2997-3012. (in Chinese)
[104] Z D Shan, Y Zhou, Y Z Li. Process optimization and decision-making model of service-oriented manufacturing network based on cloud computer. Computer Integrated Manufacturing Systems, 2019, 25(12): 3139-3148. (in Chinese)
[105] J F Man, L Q Zhao, C Peng, et al. Computer Integrated Manufacturing Systems. Computer Integrated Manufacturing Systems, 2020, DOI: 11.5946.tp.20200502.0852.002. (in Chinese)
[106] P Helo, D Phuong, Y Q G Hao. Cloud manufacturing - scheduling as a service for sheet metal manufacturing. Computers & Operations Research, 2019, 110: 208-219.
[107] A Simeone, B Deng, A Caggiano. Resource efficiency enhancement in sheet metal cutting industrial networks through cloud manufacturing. International Journal of Advanced Manufacturing Technology, 2020, 61: 101832.20: 107(3-4): 1345-1365.
[108] M H Mourad, A Nassehi, D Schaefer, et al. Assessment of interoperability in cloud manufacturing. Robotics and Computer - Integrated Manufacturing, 2020, 61: 101832.
[109] E Aghamohammadzadeh, O F Valilai. A novel cloud manufacturing service composition platform enabled by Blockchain technology. International Journal of Production Research, 2020, https://doi.org/10.1080/00207543.2020.1715507.
[110] W Guo, K Q Zhang, Z L Cui, et al. A cloud resources placement method supporting SaaS applications with multi-dimensional and heterogen requirements. Chinese Journal of Computers, 2018, 41(6): 1005-1017. (in Chinese)
[111] D P Tan, S T Chen, G J Bao, et al. An embedded lightweight GUI component library and the ergonomics optimization method for industry process monitoring. Frontiers of Information Technology & Electronic Engineering, 2018, 19(5): 604-625.
[112] H B Li, F Cheng, Juan A Robledo-Lara, et al. Fabrication of paper-based devices for in vitro tissue modeling. Bio-Design and Manufacturing, 2020, 3: 252-265.
[113] Z C Yin, J F Lu, L Li, et al. Optimized scheme for accelerating the slagging reaction and slag-metal-gas emulsification in a basic oxygen furnace. Applied Sciences, 2020, 10(15): 5101
[114] C X Wang, Z Peng, Y Z Wang, et al. Research on structure designation and cutting performance of the damping tool. Cemented Carbide, 2018, 35(06): 441-446. (in Chinese)
[115] Y Q Yang, Y W Pian, Y F Wang. Experimental tests of damped milling cutter based on embedded passive damper. Journal of Vibration, Measurement & Diagnosis, 2019, 39(06): 1177-1182+1357. (in Chinese)
[116] S Ema, E Marui. Suppression of chatter vibration of boring tools using impact dampers. International Journal of Machine Tools and Manufacture, 2000, 40(8): 1141-1156.
[117] S K Choudhury, N N Goudimenko, V A Kudinov. On-line control of machine tool vibration in turning. International Journal of Machine Tools & Manufacture, 1997, 37(6): 801-811.
[118] C H Chiou, M S Hong, K F Ehmann. The feasibility of eigenstructure assignment for machining chatter control. International Journal of Machine Tools and Manufacture, 2003, 43(15): 1603-1620.
[119] T R Kong. Study on the theory and method for MR intelligent boring bar with self-chatter-suppression. Hangzhou: Zhejiang University, 2009. (in Chinese)
