01 2023 — 2026 · Manufacturing quality Semi-supervised vision on the line
Computer Vision for Assembly Line Quality Control
A camera system on the assembly line that detects foreign objects and defects in real time, trained semi-supervised because a labelled defect dataset did not — and could not — exist.
Computer VisionDeep LearningAnomaly Detection
- Approach
- Semi-supervised
- Detection
- Real time
- Target
- Foreign objects
- Defect labels
- Not required
Read the case study → 02 2023 — 2026 · Process monitoring 5 million datapoints a day
Anomaly Detection at Line Scale
An end-to-end anomaly detection pipeline for manufacturing process data, with an optimisation framework that evaluated 48 000 model variants against performance metrics designed for the actual production question.
Anomaly DetectionTime SeriesMLOps
- Throughput
- up to 5M points/day
- Variants evaluated
- 48 000
- Latency
- Low, near real time
- Metrics
- Custom designed
Read the case study → 03 2024 — 2025 · Precision assembly Physics and statistics, together
Hybrid Physics / Data-Driven Assembly Model
A model that keeps the physical description of the assembly and learns what it cannot capture, reducing scrap and rework rates in assembly operations by 10 %.
RegressionHybrid ModellingProcess Optimisation
- Scrap & rework
- −10 %
- Formulation
- Physics + ML
- Model search
- AutoGluon
- Fallback
- Physical model
Read the case study → 04 2024 — 2025 · Knowledge & support Generative AI that stays in the building
On-Premise RAG Assistant for the Company Wiki
A locally hosted retrieval-augmented chatbot over the internal wiki, plus a benchmarking framework to compare LLMs on company-relevant prompts and data rather than on public leaderboards.
LLMsRAGGenerative AI
- Hosting
- Fully on-premise
- Source
- Company wiki
- Benchmark
- Company prompts
- Data leaving site
- None
Read the case study → 05 2024 · Process understanding Modelling what you do not know
Bayesian Network for Uncertainty Quantification
A probabilistic graphical model mapping the dependencies between process parameters, with Monte Carlo simulation used for rigorous uncertainty quantification and robust system optimisation.
Probabilistic ModellingUncertainty QuantificationOptimisation
- Model
- Bayesian network
- Sampling
- Monte Carlo
- Output
- Full distributions
- Use
- Robust optimisation
Read the case study → 06 2023 — 2024 · Design optimisation Optimisation in the loop with the solver
Genetic Algorithms Coupled to FEM
A global optimisation framework using genetic algorithms, coupling Python directly to Abaqus to automate synthetic data generation and accelerate design convergence.
OptimisationSimulationMechanical Design
- Solver
- Abaqus FEM
- Search
- Genetic algorithm
- Data
- Synthetic, automated
- Goal
- Faster convergence
Read the case study → 07 2019 — 2020 · Structural health monitoring MSc thesis · peer-reviewed publication
Load Monitoring for Aeronautical Structures
An inverse–direct approach for load and strain monitoring in aeronautical structures, based on a calibration matrix, verified both numerically and experimentally — and published in Structural Control and Health Monitoring.
Structural AnalysisInverse ProblemsExperimental Validation
- Publication
- SCHM journal
- Method
- Inverse–direct
- Verification
- Numerical + experimental
- Thesis grade
- 110/110
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