Nottingham

Dr Helia Hooshmand

Prof. Samanta Piano

Software-Driven Generation of Parametric Surfaces for Texture Characterisation

This project entails directing students to develop software aimed at generating surface topographies with customisable texture parameters. These parameters include coherence length, root-mean square of surface height, roughness and waviness profiles, etc. The project encourages students to use Fourier concept particularly emphasizing the application of the power spectral density for surface generation. 

 Nottingham

Dr Helia Hooshmand

Prof. Samanta Piano

The Impact of Surface Texture on the Coherency of Scattered Light Using an Interferometry System

This project aims to explore how the spatial coherence of light alters upon scattering from surfaces possessing distinct texture characteristics. By employing an interferometry setup, the project will delve into the coherence properties of the scattered light from a variety of surface textures. Students will engage in experimental tasks to generate and evaluate surfaces with different texture features, encouraging hands-on exploration as part of the project.

 Nottingham

Dr. Christopher Tompkins

Prof. Samanta Piano

Design and Construction of a Custom Measurement Device

Students working on this project will be involved in the design and building processes of a new type of confocal measurement device. A prototype of this device was recently designed with a company Germany, and the student will be involved in the process of creating a fully custom version.

This will involve various mechanical skills, where the student will help choose, CAD-design, 3D print, and integrates various components together into a complete opto-mechanical measurement device. 

 Nottingham

Dr. Christopher Tompkins

Prof. Samanta Piano

3D imaging and Analysis of Medical Microtubing

On this project, students will be focused on the 3D imaging of medical microtubing, to help identify their key physical characteristics. The student will be using an imaging system developed in-house, and be involved with all the processes involved in taking a new device and verifying it is up to there measurement task.

The majority of the tasks will be software-based, as the student will need to help bridge the gap between machine output data and the physical quantity they represent, through stages of calibration and designing visualisation and measurement software.

 Coventry

Dr. Glen Turley

Dr. Hua Guo

Auto Correlation of Optical in Process inspection with a lab based CMM.

Fundamental to in-process metrology is the concept of the Digital Twin. These systems incorporate geometric information, assembly methods together with measurement data from the shopfloor to optimize the production process through early detection and closed loop manufacture.

Typically, in-process metrology systems are correlated once with a lab-based Coordinate measurement machine. This project will focus on how traditional lab-based systems can be used to maintain the integrity of in-process measurement through periodic correlation.

 Coventry

Dr. Glen Turley

Dr. Hua Guo

Developing a digital thread between product technical specification and metrology inspection. 

Geometrical Dimensioning & Tolerancing (GD&T) is the method by which a component or an assembly’s design intent is embodied in technical specifications. Often these technical specifications are communicated to the Quality Department through a technical drawing for inspection using metrology tools. 

The objective of this product is to understand how model based definition can be used to directly synchronise 3D CAD GD&T technical specifications with the 3D metrology software to enable automated product inspection.

 Coventry

Dr. Glen Turley

Dr. Hua Guo

Tolerance simulation of a 3D Printed Assembly.

To understand whether an assembly is manufacturable and can function to the correct design intent, a tolerance simulation is often needed to be undertaken. This tolerance simulation involves statistically adding up the component tolerances in an assembly, following the bill of process, to obtain an overall assembly tolerance.

The objective of this project is to assess the accuracy of a tolerance simulation for a 3D printed assembly, using metrology tools to inspect the individual components and final assembly, then comparing it to the simulation results.

 Loughbrough

Dr Claire Guo

Robot environment mapping using PMD time of flight cameras

This project involves utilising a set of low cost portable ToF cameras, which can provide fast but noisy 3D scene data. The object will be to fuse data from multiple cameras so that a map of the space around a working robot can be created and maintained. The cameras will be located on and around the robot; so the work will involve calibration of the sensors to determine their position in the robots environment, then fusing the multiple sets of data using appropriate filtering algorithms to reduce noise and produce useful output information. 

 Loughborough

Dr Cong Sun

Prof. Peter Kinnell

Automated 3D reconstruction for robotic scanning

This project will build on previous work that integrated a 3D scanner with a robotic arm. An automated workflow for fusing individual scans into one refined denser mesh of the target will be created. This includes hand-eye calibration to determine the position of the scanner in the robots coordinate system, point cloud transformation & registration using a combination of robot pose information and scan data, ground segmentation/background subtraction to remove unwanted data and speed up the whole process. 

 Loughborough

Dr Cong Sun

Prof. Peter Kinnell

Optimising robot scanning strategy based on digital simulation

This project will investigate methods to simulate a robotic 3D scanning system and test the potential to use this for measurement planning and optimisation. Given the CAD model of a target object and specifications of the scanner (FOV, scanning resolution etc.), a simulation of the expected point cloud from various distances and perspectives will be generated using appropriate software, options include Blender/Gazebo/Issac Sim. Strategies will then be developed that make use of the simulation to help plan appropriate measurement strategies, for example selecting the best set of scan positions to measure set of features on a part. 

 Loughborough

Dr Cong Sun

Prof. Peter Kinnell

Investigating the limits of using simulation data to train AI inspection systems

 This project will investigate the performance of AI systems trained to detecting objects, features or defects using 2D image data and custom trained AI models such as YOLO. The project will test what happens when the AI models are trained to detect objects of varying complexity using only CAD rendered training images. In this project the intern will learn the workflow of finetuning the AI model based on open-sourced datasets, then building a custom dataset from simulation data, and finally training the model