An investigation into non-destructive testing strategies and in-situ surface finish improvement for direct metal printing with SS 17-4 PH : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Engineering at Massey University, Albany, New Zealand

Figure 1.1 is re-used under an Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licenceAdditive Manufacturing (AM) technologies have the potential to create complex geometric parts that can be used in high-end product industries, aerospace, automotive, medical etc. However, the surface finish, part-to-part reliability, and machine-to-machine reliability has made it difficult to qualify the process for load dependent structures. The improvement of surface finish on metal printed parts, is a widely sought solution by these high-end industries and non-destructively characterizing the mechanical aptitude of metal printed parts, would pave the way for quality assessment strategies used to certify additively manufactured parts. This thesis examines the capability of laser polishing and non-destructive testing technologies and methods to address these difficulties. This research study presents an investigation into quality management strategies for Direct Metal Printing (DMP) with powdered Stainless Steel 17-4 PH. The research aim is split into two key categories: to improve the surface finish of metal additive manufactured parts and to non-destructively characterize the impact of defects (metallurgical anomalies) on the mechanical properties of the printed part. To improve surface finish of a printed part, a novel methodology was tested to laser polish the Laser-Powder Bed Fusion (L-PBF) parts during print with the built-in laser. Numerous technologies for non-destructive testing techniques already exist, and in the duration of this doctoral study various technologies were explored. However, the final solution focuses on layer-wise capture with a versatile low-cost imaging system, retrofitted within the DMP machine, to capture each layer following the lasering process. In addition, the study also focuses on progressing the characterization of data (images), using a combination of image processing, 3D modelling and Finite-Element-Analysis to create a novel strategy for replicating the as-built specimen as a computer-aided design model and performing simulated fatigue failure analysis on the part. This thesis begins with a broadened justification of the research need for the solutions described, followed by a review of literature defining existing techniques and methods pertaining to the solutions, with validation of the research gap identified to provide novel contribution to the metal additive manufacturing space. This is followed by the methodologies developed, to firstly, control the laser parameters within the DMP and examine the influence of these parameters using surface profilometry, scanning electron microscopy and mechanical hardness testing. The control variables in this methodology combines laser parameters (laser power, scan speed and polishing iterations) and print orientation (polished surface angled at 0º, 20º, 40º, 60º, 80º and 90º degree increments from the laser), using several Taguchi designs of experiments and statistical analysis to characterize the experimental results. The second methodology describes the retrofitted imaging system, image processing techniques and analysis methods used to reconstruct the 3D model of a standard square shaped part and one with synthesized defects. The method explores various 2D to 3D extrusion-based techniques using a combination of code-based image processing (Python 3, OpenCV and MATLAB image processing toolbox) and ready-made software tools (Solidworks, InkTrace, ImageJ and more). Finally, the new research findings are presented, including the results of the laser polishing study demonstrating the successful improvement of surface finish. The discussion surrounding these results, highlights the most effective part orientation for laser polishing the outline of an AM part and the most effective laser parameter combination resulting in the most significant improvement to surface finish (roughness and profile height variation). Summarily, the best improvement in surface roughness was achieved with the <80 angled surface with the laser speed, laser power and polishing iterations set to 500mm/s, 30W, 3 respectively. The sample set total average measured a 16.7% decrease in Ra. NDT digital imaging, thermal imaging and acoustic technologies were considered for defect capture in metal AM parts. The solution presented is primarily focused on the expansion of research to process digital images of each part layer and examine strategies to move the research from a data capture stage to a data processing strategy with quantitative measurement (FEA analysis) of the printed part’s mechanical properties. In addition, the results discuss a method to create feedback to the DMP to selectively melt problematic areas, by re-creating the sliced part layers but removing the well-melted areas from the laser scanning pattern. The methods and technological solutions developed in this research study, have presented novel data to further research these methods in the pursuit of quality assurance for AM parts. The work done has paved the way for more the research opportunities and alternative methods to be explored that complement the methods detailed here. For example, using a combination of in-situ laser polishing, followed by post-processing the AM specimens in an acid-based chemical bath. Alternatively, further exploring acoustic NDT techniques to create an in-built acoustic-based imaging device within the AM machine. Finally, this thesis cross-examines the work done to answer the research questions established at the start of the thesis and verify the hypotheses stated in the methods chapter

Part clamping and fixture geometric adaptability for reconfigurable assembly systems.

Masters of Science in Mechanical Engineering. University of KwaZulu-Natal. Durban, 2017.The Fourth Industrial Revolution is leading towards cyber-physical systems which justified research efforts in pursuing efficient production systems incorporating flexible grippers. Due to the complexity of assembly processes, reconfigurable assembly systems have received considerable attention in recent years. The demand for the intricate task and complicated operations, demands the need for efficient robotic manipulators that are required to manoeuvre and grasp objects effectively. Investigations were performed to understand the requirements of efficient gripping systems and existing gripping methods. A biologically inspired robotic gripper was investigated to establish conformity properties for the performance of a robotic gripper system. The Fin Ray Effect® was selected as a possible approach to improve effective gripping and reduce slippage of component handling with regards to pick and place procedures of assembly processes. As a result, the study established the optimization of self-adjusting end-effectors. The gripper system design was simulated and empirically tested. The impact of gripping surface compliance and geometric conformity was investigated. The gripper system design focused on the response of load applied to the conformity mechanism called the Fin Ray Effect®. The appendages were simulated to determine the deflection properties and stress distribution through a finite element analysis. The simulation proved that the configuration of rib structures of the appendages affected the conformity to an applied force representing an object in contact. The system was tested in real time operation and required a control system to produce an active performance of the system. A mass loading test was performed on the gripper system. The repeatability and mass handling range was determined. A dynamic operation was tested on the gripper to determine force versus time properties throughout the grasping movement for a pick and place procedure. The fluctuating forces generated through experimentation was related to the Lagrangian model describing forces experienced by a moving object. The research promoted scientific contribution to the investigation, analysis, and design of intelligent gripping systems that can potentially be implemented in the operational processes of on-demand production lines for reconfigurable assembly systems

Enhancing reinforcement learning with a context-based approach

Reinforcement Learning (RL) has shown outstanding capabilities in solving complex computational problems. However, most RL algorithms lack an explicit method for learning from contextual information. In reality, humans rely on context to identify patterns and relations among elements in the environment and determine how to avoid making incorrect actions. Conversely, what may seem like obvious poor decisions from a human perspective could take hundreds of steps for an agent to learn how to avoid them. This thesis aims to investigate methods for incorporating contextual information into RL in order to enhance learning performance. The research follows an incremental approach in which, first, contextual information is incorporated into RL in simulated environments, more concisely in games. The experiments show that all the algorithms which use contextual information significantly outperform the baseline algorithms by 77 % on average. Then, the concept is validated with a hybrid approach that comprises a robot in a Human-Robot Interaction (HRI) scenario dealing with rigid objects. The robot learns in simulation while executing actions in the real world. For this setup, based on contextual information, the proposed algorithm trains in a reduced amount of time (2.7 seconds). It reaches an 84% success rate in a grasp and release-related task while interacting with a human user, while the baseline algorithm with the highest success rate reached 68% after learning during a significantly longer period of time (91.8 seconds). Consequently, CQL suits the robot’s learning requirements in observing the current scenario configuration and learning to solve it while dealing with dynamic changes provoked by the user. Additionally, the thesis explores using an RL framework that uses contextual information to learn how to manipulate bags in the real world. A bag is a deformable object that presents challenges from grasping to planning, and RL has the potential to address this issue. The learning process is accomplished through a new RL algorithm introduced in this work called Π-learning, designed to find the best grasping points of the bag based on a set of compact state representations. The framework utilises a set of primitive actions and represents the task in five states. In the experiments, the framework reaches a 60% and 80% success rate after around three hours of training in the real world when starting the bagging task from folded and unfolded positions, respectively. Finally, the trained model is tested on two more bags of different sizes to evaluate its generalisation capacities. Overall, this research seeks to contribute to the broader advancement of RL and robotics, aiming to enhance the development of intelligent, autonomous systems that can effectively operate in diverse and dynamic real-world settings. Besides that, this research seeks to explore new possibilities for automation, HRI, and the utilisation of contextual information in RL

Mobile depth sensing technology and algorithms with application to occupational therapy healthcare

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe UK government is striving to shift its current healthcare delivery model from clini-cian–oriented services, to that of patient and self–care–oriented intervention strategies. It seeks to do so through Information Communication (ICT) and Computer Mediated Re-ality Technologies (CMRT) as a key strategy to overcome the ever–increasing scarcity of healthcare resources and costs. To this end, in the UK the use of paper–based information systems have exhibited their limitations in providing apposite care. At the national level, The Royal College of Occupational Therapists (RCOT) identify home visits and modifica-tions as key levers in a multifactorial health programme to evaluate interventions for older people with a history of falling or are identified as being prone to falling. Prescribing Assistive Equipment (AE) is one such mechanism that seeks to reduce the risk of falling whilst promoting the continued independence of physical dexterity and mobility in older adults at home. In the UK, the yearly cost of falls is estimated at £2.3 billion. Further evidence places a 30% to 60% abandonment rate on prescribed AE by and large due to a ‘poor fit’ and measurement inaccuracies. To remain aligned with the national strategy, and assist in the eradication of measurement inaccuracies, this thesis employs Mobile Depth Sensing and Motion Track-ing Devices (MDSMTDs) to assist OTs in in the process of digitally measuring the extrin-sic fall–risk factors for the provision of AE. The quintessential component in this assess-ment lies in the measurement of fittings and furniture items in the home. To digitise and aid in this process, the artefact presented in this thesis employs stereo computer–vision and camera calibration algorithms to extract edges in 3D space. It modifies the Sobel–Feldman convolution filter by reducing the magnitude response and employs the camera intrinsic parameters as a mechanism to calculate the distortion matrix for interpolation between the edges and the 3D point cloud. Further Augmented Reality User Experience (AR-UX) facets are provided to digitise current state of the art clinical guidance and over-lay its instructions onto the real world (i.e., 3D space). Empirical mixed methods assessment revealed that in terms of accuracy, the arte-fact exhibited enhanced performance gains over current paper–based guidance. In terms of accuracy consistency, the artefact can rectify measurement consistency inaccuracies, but there are still a wide range of factors that can influence the integrity of the point-cloud in respect of the device’s point-of-view, holding positions and measurement speed. To this end, OTs usability, and adoption preferences materialise in favour of the artefact. In conclusion, this thesis demonstrates that MDSMTDs are a promising alterna-tive to existing paper–based measurement practices as OTs appear to prefer the digital–based system and that they can take measurements more efficiently and accurately