Implicit toolpath generation for functionally graded additive manufacturing via gradient-informed slicing

AM, generally known as 3D printing, is a promising technology. Robotic AM enables the direct fabrication of products possessing complex geometry and high performance without extra support structures. Process planning of slicing and tool path generation has been a challenging issue due to geometric complexity, material property, etc. Simple and robust planar slicing has been widely researched and applied. However, support structures usually result in time-consuming and cost-expensive. Notwithstanding multi-direction slicing and non-planar slicing (curved layer slicing) have been proposed respectively to decrease support structures, capture some minute but critical features and improve the surface quality and part strength. There is no slicing method aiming at features of part’s sub-volumes. A comprehensive literature review is given first to illustrate the problems and features of available slicing methods better. Then, in order to combine the merits of planar and non-planar slicing to realize intelligent manufacturing further, this paper reports the concept and implementation of a mixed-layer adaptive slicing method for robotic AM. Different from applying planar slicing in any cases or adopting the decomposing and regrouping based multi-direction planar slicing for finding the optimal slicing directions, the proposed method mainly focuses on how to apply planar and non-planar slicing for each sub-volume according to the geometrical features. Additionally, the requirements for robotic AM equipment in possessing multi-mode of printing and slicing are investigated.

Cloud-based Design and Additive Manufacturing of Custom Orthoses

In this paper, we demonstrate a Hybrid Manufacturing software-HybridCAM. HybridCAM provides a variety of tool path generation methods for sculpture surfaces. The tool path patterns include contour-parallel pattern, zigzag pattern, and helical pattern. HybridCAM can input multiple format of models, such as IGS, STL, and STP, and can be applied to multi-axis Additive Manufacturing (AM) and multi-axis Subtractive Manufacturing (SM). We present several tool path patterns for different parts and different applications generated by HybridCAM. An actual experiment was carried out to verity the feasibility and practicality of the software.

This article highlights work at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility to develop closed-loop, feedback control for laser-wire based Directed Energy Deposition, a form of metal Big Area Additive Manufacturing (m-BAAM), a process being developed in partnership with GKN Aerospace specifically for the production of Ti-6Al-4V pre-forms for aerospace components. A large-scale structural demonstrator component is presented as a case-study in which not just control, but the entire 3D printing workflow for m-BAAM is discussed in detail, including design principles for large-format metal AM, toolpath generation, parameter development, process control, and system operation, as well as post-print net-shape geometric analysis and finish machining. In terms of control, a multi-sensor approach has been utilized to measure both layer height and melt pool size, and multiple modes of closed-loop control have been developed to manipulate process parameters (laser power, print speed, deposition rate) to control these variables. Layer height control and melt pool size control have yielded excellent local (intralayer) and global (component-level) geometry control, and the impact of melt pool size control in particular on thermal gradients and material properties is the subject of continuing research. Further, these modes of control have allowed the process to advance to higher deposition rates (exceeding 7.5 lb/hr), larger parts (1-meter scale), shorter build times, and higher overall efficiency. The control modes are examined individually, highlighting their development, demonstration, and lessons learned, and it is shown how they operate concurrently to enable the printing of a large-scale, near net shape Ti-6Al-4V component.

Additive manufacturing has gained worldwide popularity in the last 20 years as many different methods and technologies for adding materials have been developed. Among them, wire and arc additive manufacturing (WAAM) is a promising alternative for fabricating high quality aerospace metal components economically. This study introduces a process planning strategy for WAAM that produces the path and parameters for the deposition process from CAD and process models. After introducing the framework for process planning, two important steps, tool-path generation and optimization of welding parameters, will be presented in detail. Based on the general requirements for a good quality AM tool-path, including high geometrical accuracy and a minimal number of tool-path passes and elements, two novel tool-path patterns suitable for various geometries are introduced. Using the proposed weld bead model and the overlapping model, appropriate welding parameters, such as the travel speed, wire-feed rate, and layer thickness, can be determined. The performance of the proposed process planning strategy is verified through building a sample impeller.

The support generation technique in some rapid prototyping manufacturing process plays an important role in fabricating parts of overhang geometry structures and guaranteeing the part fabrication process smoothly. A new robust and automated support generation method is proposed based on slice in this paper. During the support generation process, the self-support of part and the self-support of the support structure itself are designed to save support material. Furthermore, the different contour offsetting method corresponding to different toolpath generation method (offset toolpath generation and Zigzag toolpath generation) is also proposed to separate the part and the support structure so that the support structure can be removed easily.

Additive manufacturing has been adopted in several industries including the medical field to develop new personalised medical implants including tissue engineering scaffolds. Custom patient-specific scaffolds can be additively manufactured to speed up the wound healing process. The aim of this study was to design, fabricate, and evaluate a range of materials and scaffold architectures for 3D-printed wound dressings intended for soft tissue applications, such as skin repair. Multiple biocompatible polymers, including polylactic acid (PLA), polyvinyl alcohol (PVA), butenediol vinyl alcohol copolymer (BVOH), and polycaprolactone (PCL), were fabricated using a material extrusion additive manufacturing technique. Eight scaffolds, five with circular designs (knee meniscus angled (KMA), knee meniscus stacked (KMS), circle dense centre (CDC), circle dense edge (CDE), and circle no gradient (CNG)), and three square scaffolds (square dense centre (SDC), square dense edge (SDE), and square no gradient (SNG), with varying pore widths and gradient distributions) were designed using an open-source custom toolpath generator to enable precise control over scaffold architecture. An in vitro degradation study in phosphate-buffered saline demonstrated that PLA exhibited the greatest material stability, indicating minimal degradation under the tested conditions. In comparison, PVA showed improved performance relative to BVOH, as it was capable of absorbing a greater volume of exudate fluid and remained structurally intact for a longer duration, requiring up to 60 min to fully dissolve. Tensile testing of PLA scaffolds further revealed that designs with increased porosity towards the centre exhibited superior mechanical performance. The strongest scaffold design exhibited a Young’s modulus of 1060.67 ± 16.22 MPa and withstood a maximum tensile stress of 21.89 ± 0.81 MPa before fracture, while maintaining a porosity of approximately 52.37%. This demonstrates a favourable balance between mechanical strength and porosity that mimics key properties of engineered tissues such as the meniscus. Overall, these findings highlight the potential of 3D-printed, patient-specific scaffolds to enhance the effectiveness and customisation of tissue engineering treatments, such as meniscus repair, offering a promising approach for next-generation regenerative applications.

Current Fused Deposition Modelling (FDM) techniques use fixed diameter nozzles to deposit a filament of plastic layer by layer. The consequence is that the same small nozzle, essential for fine details, is also used to fill in relatively large volumes. In practice a Pareto-optimal nozzle diameter is chosen that attempts to maximise resolution while minimising build time. This paper introduces a concept for adapting an additive manufacturing system, which exploits a variable diameter nozzle for the fused deposition of polymers. The variable nozzle allows the print resolution and the build speed to become independent variables which may be optimised. The paper discusses a concept design for the variable diameter nozzle to be fitted to a RapMan 3D printer and the software used to generate the tool paths for the extrusion head. The methodology involves the use of existing software solutions to gather basic data from STL files and generate the tool paths. A method for integrating the data and the deposition system is proposed. The challenges and possibilities of the technology are discussed as well as future research.

Experimental prediction of material deformation in large-scale additive manufacturing of concrete

Additive manufacturing has the potential to revolutionize industrial hardware and unlock efficiency gains through the fabrication of geometries and architectures not possible by conventional processing. Wire Arc Additive manufacturing (WAAM) process is a class of directed energy deposition process enabling higher build rate and allowing custom wire feedstock allowing spatial variation of microstructure. The larger spot size and lower speed creates a larger melt pool, reducing residual stress and often time creating directional/columnar microstructure for Ni-superalloy. The use of flexible platform provides freedom in deposition strategy, which can accommodate complex substrates, including feature addition onto existing structures, non-flat layers, and repair methods. However, the certification of the final component needs to match the strength requirement. Hence, the quality of the component produced is stringently monitored to avoid buildup of residual stress, cracks, porosity and to reduce detrimental segregated phases commonly observed during alloy solidification. Simulation plays a huge role in predicting the melt pool dimension and can be used to optimize the process parameter. Similar development is also required to perform physics-based modeling of microstructural development in WAAM that can predict the microstructural features during solidification and can be used to optimize the process more effectively. To move toward this goal, Raytheon Technologies Research Center together with Siemens worked to create a set of computational tools to control the process parameters, enable on-line measurements and acquisition with feedback to the optimized process parameters, and eventually track material evolution through each step of the additive process. Computational fluid dynamics is used for accurate prediction and calibration of the thermal field during WAAM process. and phase field models for microstructure evolution as a function of processing parameters to establish a connection between additive parameters and the final microstructure. Here we report cellular automata (CA) model development to predict the dendritic microstructure evolution with surface and bulk nuclei for single track and multiple layers. The CA model was developed to account for secondary element addition and predict segregation, local melting, and latent heat release as well as prediction of Euler angles from orientation information and validated against experiments. This framework was utilized to tailor spatially-varying composition in a part by appropriately controlling the microstructure evolution during the additive process. Functionally graded Haynes 282 alloy with high Cr content at the surface was tested for oxidation and mechanical properties. An advanced physics-based reaction-diffusion model predicting the simultaneous creation of chromium oxide and alumina is developed and validated to extend life expectancy of the WAAM manufactured high temperature part. A machine-learning data-driven framework establishing the process-structure relationship from a dataset of real microstructure images and corresponding process history data has been developed and implemented in the NX Siemens design system. The digital twin configuration along with the tool path generation enabled prediction of WAAM component buildup time and the techno-economic analysis provided a favorable option for all 4 cases with 15-40% cost reduction.

This article addresses the issue of educating engineering students with the knowledge and skills of Computer-Aided Design and Manufacturing (CAD/CAM). In particular, three carefully designed tutorials—cutting tool offsetting, tool-path generation for freeform surfaces, and the integration of advanced machine tools (e.g., hexapod-based machine tools) with solid modeling—are described. The tutorials help students gain an in-depth understanding of how the CAD/CAM-relevant hardware devices and software packages work in real-life settings. At the same time, the tutorials help students achieve the following educational outcomes: (1) an ability to apply the knowledge of mathematics, science, and engineering; (2) an ability to design a system, component, or process to meet the desired needs, (3) an ability to identify, formulate, and solve engineering problems; and (4) an ability to use the techniques, skills, and modern engineering tools that are necessary for engineering practice. The tutorials can be modified for incorporating other contemporary issues (e.g., additive manufacturing, reverse engineering, and sustainable manufacturing), which can be delved into as a natural extension of this study.

Automated remanufacturing process is of significant interest in many sectors of industry as current manual remanufacturing process is prone to human error, inconsistent in quality and costly to process. Current advancements in additive manufacturing and 3D scanning technology supports opportunities for realizing automated remanufacturing. However, to date, a fully automated remanufacturing process has not yet been achieved. Current limitations were identified to the absence of effective damage detection algorithm, nominal model reconstruction algorithm, and automated machine toolpath generation process. The existing shortfall in capabilities required time consuming human input in the assessment of damage(s) and in defining the appropriate remanufacturing toolpath profiles. For widespread acceptance of “automation of remanufacturing process”, all steps should be carried out automatically by software with no human interaction except for the final verification. Automated flow should be seamless with information obtained from scan data to the final machining processes. This thesis aims to work towards achieving a fully automated remanufacturing process by establishing and proposing an automated remanufacturing process framework exploiting current state-of-the-art technologies, such as directed energy deposition technology and automated 3D scanning technology. This framework was designed with the practical considerations where, the scan input obtained from the automated scanning process is in the form of partial scan data. The object’s nominal model is often unavailable or not suitable for use. There are also multiple damages located at different locations, and the need of generating machine toolpaths directly and automatically from the scan data and the reconstructed nominal shape. Various existing frameworks have tackled some of these considerations, however, a framework incorporating all considerations have not yet been proposed. Having all considerations, incorporated, would enable a fully automated remanufacturing process for single or multiple damages located at different locations. A nominal model reconstruction algorithm for multiple damages at different locations and a direct derivation methodology of the machine toolpath shapes from the scan data have been developed to support the realisation of this framework. A case study has been carried out and it has demonstrated the feasibility of using the proposed process framework, the developed algorithm and methodology for automated remanufacturing process. The scanning boundary of the partial scan data has been successfully detected and the edge damage type has been correctly identified. Consequently, the nominal shape of the damage region has been successfully reconstructed according to the identified damage type, and the cavity cutting shape dimensions have been successfully derived from the scan data.

Algorithms-aided design applied to the tool-paths generation for hybrid manufacturing

By considering the customer as a partner in value creation, co-design, as a customer-supplier collaborative design endeavor, is becoming more common to integrate users into design and production processes as a promising strategy for companies to react to the growing individualization of demand. The computer mouse, a critical human-machine interface device, still has very little choice in terms of end user customization even though mouse designs have branched away from a single design to multiple designs, types, and sizes. This paper proposes a co-design method for engineered products that can be parameterized and illustrates the application of the method for the customization of computer mice. An interactive co-design tool was developed that allows customers to customize the size and shape of a mouse to suit their needs. The tool also provides interfaces to manufacturing for 3-axis tool path generation and for additive manufacturing. Examples are presented to demonstrate the tool's capabilities.

A grammar-based algorithm for toolpath generation: Compensating for material deformation in the additive manufacturing of concrete