A continues multi-material toolpath planning for tissue scaffolds with hollowed features

This paper presents a new multi-material based toolpath planning methodology for porous tissue scaffolds with multiple hollowed features. Ruled surface with hollowed features generated in our earlier work is used to develop toolpath planning. Ruling lines are reoriented to enable continuous and uniform size multi-material printing through them in two steps. Firstly, all ruling lines are matched and connected to eliminate start and stops during printing. Then, regions with high number of ruling lines are relaxed using a relaxation technique to eliminate over deposition. A novel layer-by-layer deposition process is progressed in two consecutive layers: The first layer with hollow shape based zigzag pattern and the next layer with spiral pattern deposition. Heterogeneous material properties are mapped based on the parametric distances from the hollow features

Reconfigurable laser micro-processing systems: development of generic system-level tools for implementing modular laser micro-manufactoring platforms

Laser micro-machining (LMM) is an attractive manufacturing technology for the fabrication of a wide range of micro-components due to its intrinsic processing attributes. In addition, LMM can be integrated in hybrid manufacturing platforms and thus to combine LMM with other complementary processes for the cost effective fabrication of a broader range of miniaturised products. Nevertheless, the broader industrial uptake of LMM is still to come due to system-level issues in designing and implementing LMM systems. In this context, the research reported in this thesis is aimed at improving the system-level performance of reconfigurable LMM platforms and thus to create the necessary pre-requisites for achieving a much better machining accuracy, repeatability and reproducibility (ARR) in different processing configurations. First, a systematic approach for assessing and characterizing the manufacturing capabilities of LMM platforms in terms of ARR is proposed. Then, the development of generic integration tools for improving the system-level performance of reconfigurable LMM platforms in terms of manufacturing flexibility and reliability both as stand-alone machine tool configurations and also as component technologies in multi-process manufacturing solutions is presented. Next, generic software tools are proposed and validated for improving the manufacturing capabilities of LMM systems for realizing complex multi-axis laser processing strategies with a closed-loop manufacturing control. Finally, the integration of LMM in process chains is validated to extend the capabilities of well proven conventional manufacturing routes, i.e. micro milling, for the fabrication of miniaturised products, i.e. Terahertz technology devices, which have complex and challenging-to-fabricate functional features and overall designs

Time-Optimal Trajectory Generation and Way-Point Sequencing for 5-Axis Laser Drilling

Laser drilling provides a highly productive method for producing arrays of holes on planar and freeform shaped components. Industrial applications include fuel injection nozzles, printed circuit boards (PCB’s), inkjet printer heads, pinholes and slits for scientific instrumentation, high-resolution circuitry, sensors, fiber-optic interconnects, medical devices, and gas turbine combustion chamber panels. This thesis deals with time-optimal trajectory planning for two mainstream laser drilling methods: on-the-fly drilling and percussion drilling, which are used in the aerospace industry. The research has been conducted in collaboration with the Canadian aero-engine producer, Pratt & Whitney Canada (P&WC). The algorithms developed have been tested in a target application involving the laser drilling of cooling hole arrays on gas turbine engine combustion chamber panels. On-the-fly drilling is an operation in which each hole receives one low powered shot at a time while the workpiece is in motion, and the beam focal point is continuously proceeding to the next hole location. The positioning sequence repeats itself until all holes are gradually opened up in small increments. Each hole location has ample time to cool down before the next shot is received. Thus, this process can yield favorable material properties in terms of preserving the desired crystal structure, and also hole quality in terms of dimensional (size) and form (shape) accuracy, due to the reduction of local thermal loading. However, there is no existing trajectory planner, in industry, or in literature, capable of generating time-optimized positioning trajectories for on-the-fly laser drilling. This thesis studies this problem and presents a new algorithm, capable of handling 5 degree-of-freedom (axis) positioning capability. The ability to generate spline-based smooth trajectories is integrated within a Traveling Salesman Problem (TSP) type sequencing algorithm. The sequencing algorithm optimizes both the order of the waypoints (i.e., hole locations) and also the timing levels in between, which affect the temporal (time-dependent) nature of the motions commanded to the laser drilling machine’s actuators. Furthermore, the duration between consecutive holes has to be an integer multiple of the laser pulsing period, considering a machine configuration in which the laser is firing at a constant frequency, and unused pulses are diverted away using a quick shutter. It is shown that the proposed algorithm is capable of generating 17-25% reduction in the beam positioning time spent during a manufacturing cycle, compared to some of the contemporary practices in industry. 17% reduction in the vibrations induced onto the laser optics is also observed, which helps prevent downtime due to the optics hardware gradually losing alignment. The second type of laser drilling operation for which optimized 5-axis trajectory planning has been developed is percussion drilling. In this process, a series of pulses are sent to each hole while the part is stationary. Once the hole is completely opened up, then positioning to the next hole proceeds. While percussion drilling is less advantageous in terms of local thermal loading and achievable part quality, it is used extensively in industry; due to its simplicity of automation compared to on-the-fly drilling. Thus, a TSP-style trajectory planning algorithm has also been developed for percussion laser drilling. The novelty, in this case, is concurrent planning of 5-axis time-optimal point-to-point movements within the sequencing algorithm, and direct minimization of the total travel time, rather than just distance (in two Cartesian axes); as is the method for which significant portion of TSP solvers and trajectory planners in literature have been developed. Compared to currently applied methods at P&WC, 32-36% reduction in the beam positioning time has been achieved. Also, 39-45% reduction in the peak magnitude of vibration has been realized. Limited benchmarking with state-of-the-art TSP solvers from combinatorial mathematics, considering only 2-axis Euclidean distance as the objective function, indicate that the proposed sequencing algorithm for percussion drilling is sub-optimal by 9-12%. Thus, it can still use further improvement in future research. Nevertheless, the two trajectory planners that have been developed in this thesis for on-the-fly drilling and percussion drilling have experimentally demonstrated very promising improvements in terms of motion time and smoothness. As more advanced Computer Numerical Control (CNC) systems and laser control electronics with deterministic execution and rapid synchronization capability become available, such algorithms are expected to facilitate significant production gains in laser drilling processes used in different industries

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

Design and development of magnetic resonance imaging (MRI) compatible tissue mimicking phantoms for evaluating focused ultrasound thermal protocols

Animal models are often used to test the efficacy and safety of clinical applications employing focused ultrasound that range in various stages of research, development and commercialization. The animals are usually subjected to conditions that cause pain, distress and euthanasia. Access to cadaveric models is not easy and affordable for all research institutions, whereas conservation and changes of their physical properties over time can be a delimiting factor for translational research. The above set the motivation for this project, which its primary objective is to design and develop appropriate tissue mimicking phantoms using a simplistic and cost effective methodology. These phantoms are expected to contribute in reducing the need for animal testing and allow researchers to get hands experience with tools that will promote and accelerate testing in focused ultrasound thermal protocols. The main requirements for these phantoms are to be geometrically accurate, compatible with magnetic resonance imaging (MRI) and to be composed of materials that approximate the acoustic and thermal properties of the replicated tissues. Throughout the duration of the project three ultrasonic composite phantoms (head, femur bone-muscle and breast-rib) were developed. The acoustic properties of candidate materials were assessed using pulse-echo immersion and through transmission techniques. The thermal properties were estimated by observing the rate of heat diffusion following a sonication in the soft tissue parts with MR thermometry. Acrylonitrile butadiene styrene (ABS) was used to replicate bone tissue, where its acoustic attenuation coefficient was found to be 16.01 ± 6.18 dB/cm at 1 MHz and the speed of sound at 2048 ± 79 m/s. Soft tissue parts consisted out of agar-based gels doped with varying concentrations of additives that controlled the relative contribution of acoustic absorption (evaporated milk) and scatter (silica dioxide) to total attenuation independently. Brain tissue phantom (2 % w/v agar - 1.2 % w/v SiO2 - 25 % v/v evaporated milk) matched an attenuation coefficient of 0.59 ± 0.05 dB/cm-MHz whereas muscle and breast mimicking phantom (2 % w/v agar - 2 % w/v SiO2 - 40 % v/v evaporated milk) were estimated of inducing an attenuation coefficient of the order of 0.99 ±0.08 dB/cm-MHz. The speed of sound for the brain and muscle/breast recipe were estimated at 1485 ± 12 m/s and 1529 ± 13 m/s respectively. The thermal conductivity of the brain phantom was estimated to be 0.52 ± 0.06 W/mº-C and 0.57 ± 0.10 W/mº-C for the muscle/breast phantom. The acoustic and thermal properties of candidate materials were within range of the replicated tissues extracted from literature, except the speed of sound in ABS compared which was lower compared to bone (~3000 m/s). Three dimensional models of bone parts (skull, femur, rib) were reconstructed in Standard Tessellation Language (STL) format by segmenting bony tissue of interest from adult human computed tomography (CT) images. The STL bone models were 3D printed in ABS using a fused deposition modelling (FDM) machine. The final composite phantoms were fabricated by molding the agar based soft tissue phantoms inside/around the ABS bone phantoms. The functionality of all three composite phantoms was assessed with focused ultrasound sonications applied by a 1 MHz single element transducer while temperature was monitored with 1.5 Tesla MRI scanner. A spoiled gradient recalled (SPGR) pulse sequence was used to produce phase images that were analyzed using a custom coded software developed in Matlab that employed proton-resonance frequency shift (PRFS) thermometry

High-precision micro-machining of glass for mass-personalization

With the fourth industrial revolution manufacturing industry faces new challenges. Small batches of personalized parts, where the geometry changes per part, must be produced in an economically viable manner. In such cases of mass personalization new manufacturing technologies are required which can keep manufacturing overhead related to change of part geometries low. These processes need to address the issues of extensive calibration and tooling costs, must be able to handle complex parts and reduce production steps. According to recent studies hybrid technologies, including electrochemical technologies, are promising to address these manufacturing challenges. At the same time, glass has fascinated and attracted much interest from both the academic and industrial world, mainly because it is optically and radio frequency transparent, chemically inert, environmentally friendly and it has excellent mechanical and thermal properties, allowing tailoring of new and dedicated applications. However, glass is a hard to machine material, due to its hardness and brittleness. Machining smooth, high-aspect ratio structures is still challenging due to long machining times, high machining costs and poor surface quality. Hybrid methods like Spark Assisted Chemical Engraving (SACE) perform well to address these issues. Nevertheless, SACE cannot be deployed for high-precision glass mass-personalization by industry and academia, due to 1) lack of process models for glass cutting and milling, relating SACE input parameters to a desired output, 2) extensive calibration needed for tool-workpiece alignment and tool run-out elimination, 3) part specific tooling required for proper clamping of the glass workpiece to attain high precision. In this study, SACE technology was progressively developed from a mass-fabrication technology towards a process for mass-personalization of high-precision glass parts by addressing these issues. Key was the development of 1) an (empirically validated) model for SACE cutting and milling process operations allowing direct relation of the machining input to the desired machining outcome, enabling a dramatical increase of automation across the manufacturing process workflow from desired design to establishing of machinable code containing all necessary manufacturing execution information, 2) in-situ fabrication of the needed tooling and 3) the use of low-cost rapid prototyping, eliminating high indirect machining costs and long lead times. To show the viability of this approach two novel applications in the microtechnology field were proposed and developed using glass as substrate material and SACE technology for rapid prototyping: a) fabrication of glass imprint templates for microfabricating devices by hot embossing and b) manufacturing of glass dies for micro-forming of metal micro parts

Study, automation and planning of micromachining processes based on infrared pulsed Fiber Laser

Short-pulsed Fiber Lasers represent an ideal solution for many micromachining operations due to their high quality laser beam and strong focusability. In this thesis, micromachining processes based on infrared pulsed Fiber Laser were investigated. A laser micromachining setup based on a 10 W Yb-doped pulsed Fiber laser source was designed, integrated and automated in order to conduct experimental activity. A new approach to part programming for laser micromachining based on syntax-free, non-structured natural language text was proposed. Experimental work was conducted by means of the pulsed Fiber Laser micromachining setup on metal and non-metal surfaces. The experiments proved that Fiber Lasers are well suited to the micromachining tasks