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YING LIU

Reader in Intelligent Manufacturing

Cardiff University

United Kingdom

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About

Ying Liu is a Reader in Intelligent Manufacturing at Cardiff University, UK. His research focuses on intelligent manufacturing systems, data integration for energy consumption modeling, and human-machine interaction in the context of Industry 5.0. Recent publications include works on agile design using large language models, deep learning applications for human fatigue analysis, and advanced methods for battery situation awareness and robotic fault diagnosis.

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Collaborators (3)

Michael Packianather

Reader

Cardiff University Cardiff School of Engineering

UNITED KINGDOM

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Xiao GUO

Senior Lecturer

Cardiff University

UNITED KINGDOM

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Xin Guo

Research Professor

Sichuan University

CHINA

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YING LIU

Research Interests

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About

Articles (26)

An LLM-Driven Triple-Stage Prompt for Automatic Disassembly Knowledge Graph Construction of End-of-Life Power Batteries Towards Industry 5.0

An Improved Consistency Optimization Model and VIKOR Approach for Supplier Selection of Port Shipping Equipment Under Fuzzy and Stochastic Environments

Generative AI-enabled chatbots for user-centred design: a state-of-the-art review

An Open-Access Journal for Digital, Smart, Sustainable, and Human-Centric Industry

Noise-Conditioned Denoising Autoencoder with Temporal Attention for Bearing RUL Prediction

Agile conceptual design and validation based on multi-source product data and large language models: a review, framework, and outlook

A multi-dimensional data integration approach for machining system multi-level energy consumption modeling and prediction

Generating Synthetic Datasets with Deep Learning Models for Human Physical Fatigue Analysis

A Hierarchical and Self-Evolving Digital Twin (HSE-DT) Method for Multi-Faceted Battery Situation Awareness Realisation

Enhanced bearing RUL prediction based on dynamic temporal attention and mixed MLP

Empowering design innovation using AI-generated content

A multi-scale graph pyramid attention network with knowledge distillation towards edge computing robotic fault diagnosis

Assessing the Circular Transformation of Warehouse Operations Through Simulation

A knowledge graph-supported information fusion approach for multi-faceted conceptual modelling

An investigation of mixed-model assembly line balancing problem with uncertain assembly time in remanufacturing

Compact convolutional transformers- generative adversarial network for compound fault diagnosis of industrial robot

Human–machine interaction towards Industry 5.0: Human-centric smart manufacturing

A hybrid model compression approach via knowledge distillation for predicting energy consumption in additive manufacturing

Regional-based strategies for municipality carbon mitigation: A case study of Chongqing in China

A Conceptual Design Specification Based on User Aesthetic Information Analysis and Product Functional Reasoning

An Energy Data-Driven Approach for Operating Status Recognition of Machine Tools Based on Deep Learning

Adaptive Genetic Algorithm Based on Fuzzy Reasoning for the Multilevel Capacitated Lot-Sizing Problem with Energy Consumption in Synchronizer Production

A New Method of Predicting the Energy Consumption of Additive Manufacturing considering the Component Working State

Multi-Indicators Decision for Product Design Solutions: A TOPSIS-MOGA Integrated Model

Multi-faceted modelling for strip breakage in cold rolling using machine learning

A smart knowledge deployment method for the conceptual design of low-carbon products

Collaborators (3)

Michael Packianather

Xiao GUO

Xin Guo

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