6 papers
Towards Agentic Defect Reasoning: A Graph-Assisted Retrieval Framework for Laser Powder Bed Fusion
Muhammad Rizwan Awan, Volker Pickert, Muhammad Waqar Ashraf +3
Laser Powder Bed Fusion (LPBF) is highly sensitive to process parameters, which influence defect formation through complex thermal and fluid mechanisms. However, defect-related kno…
Data-driven Bi-level Optimization of Thermal Power Systems with embedded Artificial Neural Networks
Talha Ansar, Muhammad Mujtaba Abbas, Ramit Debnath +2
Industrial thermal power systems have coupled performance variables with hierarchical order of importance, making their simultaneous optimization computationally challenging or inf…
Code, Capital, and Clusters: Understanding Firm Performance in the UK AI Economy
Waqar Muhammad Ashraf, Diane Coyle, Ramit Debnath
The UK has established a distinctive position in the global AI landscape, driven by rapid firm formation and strategic investment. However, the interplay between AI specialisation,…
From drift to adaptation to the failed ml model: Transfer Learning in Industrial MLOps
Waqar Muhammad Ashraf, Talha Ansar, Fahad Ahmed +3
Model adaptation to production environment is critical for reliable Machine Learning Operations (MLOps), less attention is paid to developing systematic framework for updating the…
Neural Network-enabled Domain-consistent Robust Optimisation for Global CO Reduction Potential of Gas Power Plants
Waqar Muhammad Ashraf, Talha Ansar, Abdulelah S. Alshehri +3
We introduce a neural network-driven robust optimisation framework that integrates data-driven domain as a constraint into the nonlinear programming technique, addressing the overl…
Domain-Informed Operation Excellence of Gas Turbine System with Machine Learning
Waqar Muhammad Ashraf, Amir H. Keshavarzzadeh, Abdulelah S. Alshehri +3
The domain-consistent adoption of artificial intelligence (AI) remains low in thermal power plants due to the black-box nature of AI algorithms and low representation of domain kno…