Ming Zhang

Aston University

United Kingdom

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Articles (21)

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Collaborators (10)

Lucy Bastin

Aston University

UNITED KINGDOM

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Chao Liu

Aston University

UNITED KINGDOM

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Abul Hossain

Aston University

UNITED KINGDOM

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Gareth Thomson

Aston University

UNITED KINGDOM

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Yuchun Xu

Prof

Aston University

UNITED KINGDOM

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Nasser Amaitik

Aston University

UNITED KINGDOM

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tony clark

Aston University

UNITED KINGDOM

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Yuqian Lu

Lecturer

University of Auckland

NEW ZEALAND

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Yang Lu

York St John University

UNITED KINGDOM

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Yu Jia

Aston University

UNITED KINGDOM

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Ming Zhang

Research Interests

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Articles (21)

A Novel Comprehensive Semi-supervised Learning Method for Fault Diagnosis Under Extremely Low Label Rate

Leveraging AI for energy-efficient manufacturing systems: Review and future prospectives

An ontology and rule-based method for human–robot collaborative disassembly planning in smart remanufacturing

Reliability enhancement of state of health assessment model of lithium-ion battery considering the uncertainty with quantile distribution of deep features

A novel health indicator by dominant invariant subspace on Grassmann manifold for state of health assessment of lithium-ion battery

GPSC-GAN: A Data Enhanced Model for Intelligent Fault Diagnosis

Self-adaptive digital twin of fuel cell for remaining useful lifetime prediction

A Fuzzy Synthesis Approach for Hierarchical Decision Analysis to Select Optimum Repair Technique

Manifold learning-empowered lightweight unsupervised deep representation for edge-side fault detection

GPSC-GAN: A Data Enhanced Model for Intelligent Fault Diagnosis

Towards sustainable manufacturing by enabling optimum selection of life extension strategy for industrial equipment based on cost modelling

A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing

Online Big-Data Monitoring and Assessment Framework for Internal Combustion Engine with Various Biofuels

Semi-Supervised Deep Kernel Active Learning for Material Removal Rate Prediction in Chemical Mechanical Planarization

A Novel Deep Model with Meta-learning for Rolling Bearing Few-shot Fault Diagnosis

Few-Shot Learning Approaches for Fault Diagnosis Using Vibration Data: A Comprehensive Review

Dynamic Scheduling Method for Job-Shop Manufacturing Systems by Deep Reinforcement Learning with Proximal Policy Optimization

Predictive Maintenance for Remanufacturing Based on Hybrid-Driven Remaining Useful Life Prediction

Cost Modelling to Support Optimum Selection of Life Extension Strategy for Industrial Equipment in Smart Manufacturing

A Distributional Perspective on Remaining Useful Life Prediction With Deep Learning and Quantile Regression

An early warning method for mechanical fault detection based on adversarial auto-encoders

Collaborators (10)

Lucy Bastin

Chao Liu

Abul Hossain

Gareth Thomson

Yuchun Xu

Nasser Amaitik

tony clark

Yuqian Lu

Yang Lu

Yu Jia

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