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  Revolutionizing Precision: Optical Sensors and Robotics in Advanced Manufacturing

   Department of Mechanical Engineering

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  Dr Runan Zhang  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

This project addresses a pressing challenge in large-volume manufacturing: the need for precise, timely inspection of large mechanical parts and structures. These items are often difficult to move for standard inspections using Coordinate Measuring Machines (CMMs). Therefore, an in-situ measuring system is key to promptly identifying and rectifying manufacturing errors.

One promising solution is the use of optical sensors operated by serial robots. These robots have small footprints and large working volumes, making them a potentially effective tool for in-situ measurements. However, serial robots have limitations, notably, their accuracies are limited to millimetre levels, a stark contrast to the micrometre level accuracy of positioning stages used in surface measurements.

To overcome this challenge, this project proposes the development of a smart sensor handling end effector to stabilize sensor movements during measurements. This will enable us to take advantage of the serial robot's large work volume and the end effector's high-precision movements, thus bridging the gap in accuracies.

The project's main challenges are trajectory planning and motion control for this robotic sensing system. The robot arm will be characterized to identify its limitations. A positioning technology with micrometre level accuracy will be embedded in the sensor handling end effector. Algorithms will be developed to coordinate the robot and end effector movements, minimize induced errors, and segment large surface scanning tasks.

Upon task completion, the obtained data will be fused to create a model of the actual part, and compared with the design to generate a map of machining errors. This PhD project encompasses the design, creation, modelling, and characterization of a novel robotic sensing system, as well as the development of algorithms for trajectory planning, motion control, and data fusion. This provides an opportunity to transform theoretical concepts and design solutions into practical implementations, evaluated through experimental testing.

Engineering (12)

Funding Notes

A variety of competitive funding opportunities would be available for this project. Self-funded project is acceptable.

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