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A collaborative resequencing approach enabled by multi-core PREA for a multi-stage automotive flow shop.

, , , , and . Expert Syst. Appl., 237 (Part C): 121825 (March 2024)

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Deep Learning Based Modeling for Cutting Energy Consumed in CNC Turning Process., , , , and . SMC, page 1398-1403. IEEE, (2018)Optimization of CNC machine processing parameters for low carbon manufacturing., , , and . CASE, page 498-503. IEEE, (2013)Meta-Reinforcement Learning of Machining Parameters for Energy-Efficient Process Control of Flexible Turning Operations., , , and . IEEE Trans Autom. Sci. Eng., 18 (1): 5-18 (2021)Realistic wrinkle generation for 3D face modeling based on automatically extracted curves and improved shape control functions., , , and . Comput. Graph., 35 (1): 175-184 (2011)Reinforcement Learning-Based Selective Disassembly Sequence Planning for the End-of-Life Products With Structure Uncertainty., , , and . IEEE Robotics Autom. Lett., 6 (4): 7807-7814 (October 2021)An industrial data based investigation into effects of process parameters on cutting power and energy efficiency., , , and . CASE, page 1481-1486. IEEE, (2017)Energy-Saving Trajectory Planning for Robotic High-Speed Milling of Sculptured Surfaces., , , , , and . IEEE Trans Autom. Sci. Eng., 19 (3): 2278-2294 (2022)A new operational framework to job shop scheduling for reducing carbon emissions., , , and . CASE, page 58-63. IEEE, (2012)A data and knowledge-driven cutting parameter adaptive optimization method considering dynamic tool wear., , , , and . Robotics Comput. Integr. Manuf., (June 2023)A Collaborative Resequencing Optimization Method for Multi-stage Automotive Production Line Considering Emergency order., , , , and . SMC, page 1224-1229. IEEE, (2022)