McMullen, Kieran ORCID: https://orcid.org/0000-0003-1477-3082 (2022) Industrial Robotics for Advanced Machining. MPhil thesis, University of Sheffield.
Abstract
This work presents a literature review of the current state of robotic machining with industrial machining robots, primarily those with 6-axis end effectors and serial link (anthropomorphic) construction. Various disadvantages of robotic machining in industry are presented, as well as the methods applied to mitigate them and discussions of their effects. From this review, the methods of dynamic modelling, stability prediction and configuration control are selected for application to the task of optimisation of a robotic machining cell for drilling operations. Matrix Structural Analysis (MSA) and methods developed by Klimchik et al. are used for compliance modelling, stability prediction methods developed by Altintas et al. and machining stability lobe prediction are then applied to a robotic drilling process, as explored by Mousavi et al. This optimisation method is applied using the measured and estimated properties of an ABB IRB 6640 robot and results are presented in comparison with previous experimentation with the physical robot, and analytical stability predictions from the same cutting parameters with Cutpro software. Results are discussed in the concluding chapters, as well as discontinued parts of the project and suggestions for future work.
Metadata
Supervisors: | Ozturk, Erdem and Lord, Charles |
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Related URLs: | |
Keywords: | Matrix Structural Analysis; Matlab; Industrial Robot; Drilling; Machining; Stability Lobes; Cutpro |
Awarding institution: | University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Advanced Manufacuring Research Centre (Sheffield) The University of Sheffield > Faculty of Engineering (Sheffield) The University of Sheffield > Faculty of Engineering (Sheffield) > Mechanical Engineering (Sheffield) |
Depositing User: | Mr Kieran McMullen |
Date Deposited: | 20 Sep 2022 13:02 |
Last Modified: | 20 Sep 2022 13:02 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:31428 |
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Description: Kieran McMullen; MPhil; Corrected Thesis Submission
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