Remanufacturing production planning with compensation function approximation method. - Haijun Wen; Mingzhou Liu 002; Changyi Liu; Conghu Liu (Appl. Math. Comput., 2015)

Research on assembly quality adaptive control system for complex mechanical products assembly process under uncertainty. - Xiaoqiao Wang; Mingzhou Liu 002; Maogen Ge; Lin Ling; Conghu Liu (Comput. Ind., 2015)

Tolerance Redistributing of the Reassembly Dimensional Chain on Measure of Uncertainty. - Conghu Liu (Entropy, 2016)

Research on the Connotation and Measurement of Uncertainty for Reassembly Dimensions Based on Entropy. - Conghu Liu; Kang He 003 (INCoS, 2017)

Intelligent assembly system for mechanical products and key technology based on internet of things. - Mingzhou Liu 002; Jing Ma; Lin Ling; Maogen Ge; Qiang Wang 040; Conghu Liu (J. Intell. Manuf., 2017)

A Review of Optimal Sensor Deployment to Diagnose Manufacturing Systems. - Kang He 003; Minping Jia; Conghu Liu (IEEE Access, 2018)

Dynamic Bayesian Network-Based Approach by Integrating Sensor Deployment for Machining Process Monitoring. - Kang He 003; Zhuanzhe Zhao; Minping Jia; Conghu Liu (IEEE Access, 2018)

Research on data mining technology for the connotation and measurement of uncertainty for reassembly dimensions. - Conghu Liu; Kang He 003; Yingfeng Zhang; Changyi Liu (Int. J. High Perform. Syst. Archit., 2018)

An Integrated Optimization Decision Method for Remanufacturing Process Based on Conditional Evidence Theory Under Uncertainty. - Zongke Bao; Wenyi Li; Mengdi Gao; Conghu Liu; Xugang Zhang; Wei Cai 007 (IEEE Access, 2020)

Error propagation model and optimal control method for the quality of remanufacturing assembly. - Wenyi Li; Cuixia Zhang; Conghu Liu; Xiao Liu (J. Intell. Fuzzy Syst., 2022)

Promoting the efficiency of scientific and technological innovation in regional industrial enterprises: Data-driven DEA-Malmquist evaluation model. - Yaliu Yang; Xue Wu; Fan Liu; Yingyan Zhang; Conghu Liu (J. Intell. Fuzzy Syst., 2022)

Data-Driven Remanufacturability Evaluation Method of Waste Parts. - Conghu Liu; Jian Chen 016; Wei Cai 007 (IEEE Trans. Ind. Informatics, 2022)

Research on surface defects detection method and system in manufacturing processes based on the fusion of multi-scale features and semantic segmentation for intelligent manufacturing. - Yu Gong; Mingzhou Liu 002; Xiaoqiao Wang; Conghu Liu; Jing Hu (J. Intell. Fuzzy Syst., 2023)

Data-Driven Evaluation of Regional Innovation Capability: A Case Study of Anhui Province. - Yaliu Yang; Xue Wu; Yingyan Zhang; Cui Wang; Fan Liu; Shuling Zhou; Fagang Hu; Conghu Liu (J. Glob. Inf. Manag., 2023)

Data-driven and Knowledge-based predictive maintenance method for industrial robots for the production stability of intelligent manufacturing. - Xiaoqiao Wang; Mingzhou Liu 002; Conghu Liu; Lin Ling; Xi Zhang (Expert Syst. Appl., 2023)

Integration of lean production and low-carbon optimization in remanufacturing assembly. - Cuixia Zhang; Conghu Liu; Huiying Mao; Guangdong Tian; Zhigang Jiang; Wei Cai 007; Wenbin Wang (Adv. Eng. Informatics, 2024)

Graph reinforcement learning for flexible job shop scheduling under industrial demand response: A production and energy nexus perspective. - Zhangjie Rui; Xi Zhang; Mingzhou Liu; Lin Ling; Xiaoqiao Wang; Conghu Liu; Mengyuan Sun 003 (Comput. Ind. Eng., 2024)

Quantitative Evaluation Model of the Quality of Remanufactured Product. - Conghu Liu; Jian Chen 016; Xiaoqiao Wang (IEEE Trans. Engineering Management, 2024)

Few-shot defect detection using feature enhancement and image generation for manufacturing quality inspection. - Yu Gong; Mingzhou Liu 002; Xiaoqiao Wang; Conghu Liu; Jing Hu (Appl. Intell., 2024)

EFJSP-IBDR: Energy-efficient flexible job shop scheduling under incentive-based demand response via graph reinforcement learning with dual attention mechanism. - Mingzhou Liu 002; Zhangjie Rui; Xi Zhang; Maogen Ge; Lin Ling; Xiaoqiao Wang; Conghu Liu (Expert Syst. Appl., 2025)

Human-machine knowledge hybrid augmentation method for surface defect detection based few-data learning. - Yu Gong; Xiaoqiao Wang; Chichun Zhou 001; Maogen Ge; Conghu Liu; Xi Zhang (J. Intell. Manuf., 2025)