Layer-based Additive Manufacturing Research Articles

Texture-based residual stress analysis of laser powder bed fused Inconel 718 parts.

Although layer-based additive manufacturing methods such as laser powder bed fusion (PBF-LB) offer an immense geometrical freedom in design, they are typically subject to a build-up of internal stress (i.e. thermal stress) during manufacturing. As a consequence, significant residual stress (RS) is retained in the final part as a footprint of these internal stresses. Furthermore, localized melting and solidification inherently induce columnar-type grain growth accompanied by crystallographic texture. Although diffraction-based methods are commonly used to determine the RS distribution in PBF-LB parts, such features pose metrological challenges in their application. In theory, preferred grain orientation invalidates the hypothesis of isotropic material behavior underlying the common methods to determine RS. In this work, more refined methods are employed to determine RS in PBF-LB/M/IN718 prisms, based on crystallographic texture data. In fact, the employment of direction-dependent elastic constants (i.e. stress factors) for the calculation of RS results in insignificant differences from conventional approaches based on the hypothesis of isotropic mechanical properties. It can be concluded that this result is directly linked to the fact that the {311} lattice planes typically used for RS analysis in nickel-based alloys have high multiplicity and less strong texture intensities compared with other lattice planes. It is also found that the length of the laser scan vectors determines the surface RS distribution in prisms prior to their removal from the baseplate. On removal from the baseplate the surface RS considerably relaxes and/or redistributes; a combination of the geometry and the scanning strategy dictates the sub-surface RS distribution.

Topology Optimization of Self-supporting Porous Structures Based on Triply Periodic Minimal Surfaces

With the advent of additive manufacturing (AM), topology optimization (TO) has become increasingly important in structural design. A key component of structural design is generating the interior shape of an object under predefined force conditions and specific constraints. Fabricating such models by layer-based AM suffers from the problem of adding and removing interior supporting structures, which can produce artifacts in the final product. In this paper, we propose an algorithm to design a self-supporting porous structure by integrating overhang constraints into the topology optimization framework. A minimum thickness constraint is also built into the optimization process to automatically enforce printability of the resulting structures. We utilize triply periodic minimal surfaces (TPMSs) to represent interior structures which can be analyzed, optimized and stored directly using analytical functions. We apply several acceleration methods including super element strategy, multigrid algorithm and GPU-based solver to handle models comprising of several million of elements efficiently. Numerical results indicate that the optimized interior structures obtained by our approach exhibit improved printability as they largely satisfy manufacturing requirements on overhang angles and minimal thicknesses.

A data-centric approach to anomaly detection in layer-based additive manufacturing

Abstract Anomaly detection describes methods of finding abnormal states, instances or data points that differ from a normal value space. Industrial processes are a domain where predicitve models are needed for finding anomalous data instances for quality enhancement. A main challenge, however, is absence of labels in this environment. This paper contributes to a data-centric way of approaching artificial intelligence in industrial production. With a use case from additive manufacturing for automotive components we present a deep-learning-based image processing pipeline. We integrate the concept of domain randomisation and synthetic data in the loop that shows promising results for bridging advances in deep learning and its application to real-world, industrial production processes.

An initial feasibility study into ray-based slicing for revolving thin-wall parts using a rotary 3D printer

PurposeWith the development of 3D printing or additive manufacturing (AM), curved layer fused deposition modeling (CLFDM) has been researched to cope with the flat layer AM inherited problems, such as stair-step error, anisotropy and the time-cost and material-cost problems from the supporting structures. As one type of CLFDM, cylindrical slicing has obtained some research attention. However, it can only deal with rotationally symmetrical parts with a circular slicing layer, limiting its application. This paper aims to propose a ray-based slicing method to increase the inter-layer strength of flat layer-based AM parts to deal with more general revolving parts.Design/methodology/approachSpecifically, the detailed algorithm and implementation steps are given with several examples to enable readers to understand it better. The combination of ray-based slicing and helical path planning has been proposed to consider the nonuniform path spacing between the adjacent paths in the same curved layer. A brief introduction of the printing system is given, mainly including a 3D printer and the graphical user interface.FindingsThe preliminary experiments are successfully conducted to verify the feasibility and versatility of the proposed and improved slicing method for the revolving thin-wall parts based on a rotary 3D printer.Originality/valueThis research is early-stage work, and the authors are intended to explore the process and show the initial feasibility of ray-based slicing for revolving thin-wall parts using a rotary 3D printer. In general, this research provides a novel and feasible slicing method for multiaxis rotary 3D printers, making manufacturing revolving thin-wall and complex parts possible.

Removal of Stair-Step Effects in Binder Jetting Additive Manufacturing Using Grayscale and Dithering-Based Droplet Distribution.

Binder jetting is a layer-based additive manufacturing process for three-dimensional parts in which a print head selectively deposits binder onto a thin layer of powder. After the deposition of the binder, a new layer of powder is applied. This process repeats to create three-dimensional parts. The binder jetting principle can be adapted to many different materials. Its advantages are the high productivity and the high degree of freedom of design without the need for support structures. In this work, the combination of binder jetting and casting is utilized to fabricate metal parts. However, the achieved properties of binder jetting parts limit the potential of this technology, specifically regarding surface quality. The most apparent surface phenomenon is the so-called stair-step effect. It is considered an inherent feature of the process and only treatable by post-processing. This paper presents a method to remove the stair-step effect entirely in a binder jetting process. The result is achieved by controlling the binder saturation of the individual voxel volumes by either over or underfilling them. The saturation is controlled by droplet size variation as well as dithering, creating a controlled migration of the binder between powder particles. This work applies the approach to silica sand particle material with an organic binder for casting molds and cores. The results prove the effectiveness of this approach and outline a field of research not identified previously.

On the Accuracy of the Infill Pattern’s Density in Additive Manufacturing

This paper aims to study the accuracy of infill density in additive manufacturing processes especially metal additive manufacturing, considering the commonly used infill patterns in the industry. To achieve this goal, the commonly used 2D infill patterns and their input parameters are analyzed in detail and formulated. The amount of the layers’ infill density errors for various layers of a generic cubic volume are calculated and their deviations from the desired density values are represented for each infill pattern considering various parameter setups. The behavior of different infill patterns are compared to each other in terms of volumetric percentage error and the sources of the errors are investigated. The developed results can be used for proper selection of the infill patterns and to optimize the infill parameters for any layer-based additive manufacturing process. However, the effect of infill density accuracy is more significant in the metal additive manufacturing process, as metal parts are mostly built to serve as functional parts in the actual machines in the industry.

An Investigation of Integrated Multiscale Three-Dimensional Printing for Hierarchical Structures Fabrication

Abstract Nature provides us with a large number of functional material systems consisting of hierarchical structures, where significant variations in dimensions are present. Such hierarchical structures are difficult to build by traditional manufacturing processes due to manufacturing limitations. Nowadays, three-dimensional (3D) objects with complex structures can be built by gradually accumulating in a layer-based additive manufacturing (AM); however, the hierarchical structure measured from macroscale to nanoscale sizes still raises significant challenges to the AM processes, whose manufacturing capability is intrinsically specified within a certain scope. It is desired to develop a multiscale AM process to narrow this gap between scales of feature in hierarchical structures. This research aims to investigate an integration approach to fabricating hierarchical objects that have macro-, micro-, and nano-scales features in an object. Firstly, the process setup and the integrated process of two-photon polymerization (TPP), immersed surface accumulation (ISA), and mask image projection-based stereolithography (MIP-SL) were introduced to address the multiscale fabrication challenge. Then, special hierarchical design and process planning toward integrating multiple printing processes are demonstrated. Lastly, we present two test cases built by our hierarchical printing method to validate the feasibility and efficiency of the proposed multiscale hierarchical printing approach. The results demonstrated the capability of the developed multiscale 3D printing process and showed its future potential in various novel applications, such as optics, microfluidics, cell culture, as well as interface technology.

Adaptive variable layer thickness and perimetral offset planning for layer-based additive manufacturing processes

ABSTRACT This paper presents a methodology to estimate and optimize the process of slicing for a layer-based additive manufacturing process. An objective function for optimizing the process planning parameters is proposed in which perimetral offsets for each layer are considered as a parameter in addition to the layer thickness. The root-mean-square (RMS) value of the deviations between the NURBS representation of the CAD model and its built-up simulation is suggested to estimate a quantitative measure for the uncertainties. The proposed approach eliminates the sophistication of the calculation cusp volume in 3D space and has more compatibility with the corresponding inspection processes. The developed methodology is introduced based on using a metaheuristic algorithm to find the optimal layer thicknesses and perimetral offsets for a built-up model. A data collecting approach is also introduced to reduce the computation time associated with the simulation of the build-up model at each iteration. The developed methodology potentially can be used for layer-based additive manufacturing processes

An automatic optimization method for minimizing supporting structures in additive manufacturing

The amount of supporting structure usage has been a major research topic in layer-based additive manufacturing (AM) over the past years as it leads to increased fabrication time and decreased surface quality. Previous studies focused on deformation and topology optimization to eliminate the number of support structures. However, during the actual fabrication process, the properties of shape and topology are essential. Therefore, they should not be modified casually. In this study, we present an optimizer that reduces the number of supporting structures by identifying the prime printing direction. Without rotation, models are projected in each direction in space, and the basis units involved in the generation of support structures are separated. Furthermore, the area of the supporting structures is calculated. Eventually, the prime printing direction with minimal supporting area is obtained through pattern-searching method. The results of the experiment demonstrated that the printing area was reduced by up to 60% for some cases, and the surface quality was also improved correspondingly. Furthermore, both the material consumption and fabrication time were decreased in most cases. In future work, additional factors will be considered, such as the height of the supporting structures and the adhesion locations to improve the efficiency of this optimizer.

DEVELOPMENT OF A METHOD OF ADDITIVE MANUFACTURING BY MATERIAL EXTRUSION ALONG THREE-DIMENSIONAL CURVES

A method of additive manufacturing (AM) for the extrusion of material along three-dimensional curves is proposed as an alternative to conventional methods of layer-based AM for the manufacture of components designed using topology optimisation. The objectives of the study are to formulate a toolpath-generation algorithm for the extrusion process, to design the testing apparatus and methods for the validation of the proposed extrusion process, and to generate feedback based on the results obtained during testing and validation for possible implementation in topology optimisation software. The outcome of the study is a process by which toolpaths can be generated for simple geometries, and implemented using a mounted extruder serving on to a serial robot-mounted build platform.

A more accurate analytical formulation of surface roughness in layer-based additive manufacturing to enhance the product’s precision

A theoretical formula for surface roughness of layer-based manufactured parts in additive manufacturing is developed considering a more accurate definition of the centerline by minimizing the total arithmetic deviations of the actual surface profile. The developed model is experimentally validated, and it is compared with those that are used in common practices. Considering the uncontrolled process variables and the complexity of the numerical solutions, the analytical and experimental results show satisfying agreement. A methodology is also developed to decide whether the objective surface slope is feasible with the current number of layers and how the layers need to be laid down to achieve the desired surface accuracy. The methodology yields more accurate small features on the surfaces of the layer-based manufactured products.

Fabrication-aware structural optimisation of lattice additive-manufactured with robot-arm

Architectural structures achieving high strength and stiffness with intelligent, but intricate geometry may now be materialisable through additive manufacturing (AM). However, conventional layer-based AM also produces parts with inconsistent structural strength - thereby limiting AM's end-use applications. Expanding on robotics-enabled AM techniques addressing this limitation, a novel design-fabrication framework for producing structurally optimised lattices is presented here. Lattices are geometrically morphed to maximise their structural stiffness-to-weight ratio while respecting fabrication constraints imposed by the robotic printing process, and converted into tool-paths for PLA extrusion with a custom-built end effector mounted on an industrial robot arm. The printing process leverages thermal imaging for calibration, and develops a novel joint detail to increase the reliability and load-transfer capabilities of the print. Together, these techniques and methods - validated through comparative structural load testing - show promise for architecture-scale AM that combines structurally driven geometry with complexity-agnostic materialisation in new and exciting ways.

Fabrication-aware structural optimisation of lattice additive-manufactured with robot-arm

Architectural structures achieving high strength and stiffness with intelligent, but intricate geometry may now be materialisable through additive manufacturing (AM). However, conventional layer-based AM also produces parts with inconsistent structural strength - thereby limiting AM's end-use applications. Expanding on robotics-enabled AM techniques addressing this limitation, a novel design-fabrication framework for producing structurally optimised lattices is presented here. Lattices are geometrically morphed to maximise their structural stiffness-to-weight ratio while respecting fabrication constraints imposed by the robotic printing process, and converted into tool-paths for PLA extrusion with a custom-built end effector mounted on an industrial robot arm. The printing process leverages thermal imaging for calibration, and develops a novel joint detail to increase the reliability and load-transfer capabilities of the print. Together, these techniques and methods - validated through comparative structural load testing - show promise for architecture-scale AM that combines structurally driven geometry with complexity-agnostic materialisation in new and exciting ways.

Thermal expansion coefficients in Invar processed by selective laser melting

This work investigates whether the unique low thermal expansion property of Invar (64Fe–36Ni) is retained after processing using the additive manufacturing process selective laser melting (SLM). Using this process, near-full-density components (99.96%) were formed by melting thin (20 μm) layers of powdered Invar (15–45 μm particle size). The mechanical properties of SLM Invar were comparable to that of cold-drawn Invar36®; however, the thermal coefficient of expansion was observed to be a lower value and negative up until 100 °C. This negative value was attributed to residual stress in the as-deposited parts. The low thermal expansion property of Invar was still maintained when processed using a non-conventional layer-based additive manufacturing technique.

Self-supporting rhombic infill structures for additive manufacturing

Recent work has demonstrated that the interior material layout of a 3D model can be designed to make a fabricated replica satisfy application-specific demands on its physical properties, such as resistance to external loads. A widely used practice to fabricate such models is by layer-based additive manufacturing (AM), which however suffers from the problem of adding and removing interior supporting structures. In this paper, we present a novel method for generating application-specific infill structures on rhombic cells so that the resultant structures can automatically satisfy manufacturing requirements on overhang-angle and wall-thickness. Additional supporting structures can be avoided entirely in our framework. To achieve this, we introduce the usage of an adaptive rhombic grid, which is built from an input surface model. Starting from the initial sparse set of rhombic cells, via numerical optimization techniques an objective function can be improved by adaptively subdividing the rhombic grid and thus adding more walls in cells. We demonstrate the effectiveness of our method for generating interior designs in the applications of improving mechanical stiffness and static stability.

Meniscus process optimization for smooth surface fabrication in Stereolithography

In the layer-based additive manufacturing processes, it is well known that the surface finish is usually poor due to the stair-stepping effect. In our previous study, it was shown that the meniscus approach can be used in the Stereolithography process to achieve much better surface finish. A related challenge is how to optimize parameters such that the formed meniscuses can lead to high surface finish and accurate shape. In this paper, a systematic process planning method is presented for the Stereolithography process that is integrated with the meniscus approach. Process planning, parameters characterization and meniscus parameters optimization are presented with experimental verifications. To demonstrate the systematic process, surface profile simulation, meniscus database construction, meniscus forming parameter optimization, and shape accuracy prediction have been performed using a test case based on convex surfaces. A comparison between the experimental results with and without the process planning method is presented, illustrating the effectiveness of the developed meniscus optimization method in simultaneously controlling the shape and surface finish of fabricated objects. Subsequently the simulation results are also verified with experimental results.

Direct porous structure generation of tissue engineering scaffolds for layer-based additive manufacturing

Three-dimensional modeling of porous objects consisting of freeform surfaces and possessing complex internal structure induces significant difficulties for CAD software even on state-of-the-art computers. A representative case concerns tissue-engineering scaffolds containing structured macro-pores which can be produced following the additive manufacturing paradigm. A modeling algorithm is presented in this work, exploiting the macro-pore as a periodically repeated unit cell. Different types of unit cells may be designed on the CAD system as standard modules populating a library. All unit cells lying on the outer boundary of the scaffold are represented in their exact shape, consisting mostly of incomplete unit cells resulting from intersection operations with the scaffold boundary. The rest of the unit cells, lying totally inside the scaffold boundary and constituting the vast majority of the total number of unit cells, are represented in essence by a reference point and a reference direction. A slicing algorithm generates the 2D geometry of each layer which, in turn, may be used to generate a 2D scanning pattern and, ultimately, G-code that is fed to the 3D printer. The algorithm is termed “procedural” since it models part shape using an additive process-oriented approach. It was implemented on a commercially available CAD system. As a result, the need to create huge complex CAD models and convert them to error-prone and extremely large stereolithography (STL) files is bypassed.

Smooth Surface Fabrication Based on Controlled Meniscus and Cure Depth in Microstereolithography

In the layer-based additive manufacturing (AM) processes, a three-dimensional (3D) model is converted into a set of two-dimensional (2D) layers. Due to such conversion, one of the major problems in the layer-based AM processes is the poor surface finish associated with the layer-based stair-stepping effect. However, the surface finish is critical for various microscale applications such as micro-optics and microfluidics. The adoption of AM technologies as a means for fabricating end-use microcomponents and tooling has been limited by such poor surface finish. The aim of this research work is to apply the state-of-the-art meniscus approach and controlled cure depth planning in the mask image projection-based microstereolithography (MIP-μSL) process to address its surface finish challenge. Mathematical models of meniscus shapes and cure depths are developed for the MIP-μSL process. Related process parameters including the minimum meniscus points, sliced layer shapes for forming meniscus, grayscale image values, and Z offsetting values are optimized to achieve the minimum approximation errors between a built part and a given nominal geometric model. A set of test cases with various curved surfaces are designed to test the developed smooth surface fabrication method. The experimental results verify the effectiveness of the proposed methods for the MIP-μSL process.

Ceramic fabrication using Mask-Image-Projection-based Stereolithography integrated with tape-casting

Ceramic components with complex geometry are difficult to fabricate. Layer-based additive manufacturing processes such as ceramic-suspension-based stereolithography (SL) provide a direct way of fabricating ceramic components from computer-aided design (CAD) models. In such an SL process, fine ceramic powders are mixed with liquid photocurable resin into ceramic suspension. The suspension-based slurry is then used in the SL process to fabricate green parts with desired shapes. A sintering process is further required to convert the green parts into dense ceramic components. In this paper, several key challenges of the ceramic-suspension-based SL process are discussed including the recoating and curing ceramic suspension with high solid loading. A novel Mask-Image-Projection-based Stereolithography (MIP-SL) process by integrating ceramic tape-casting and bottom-up projection methods is presented for fabricating dense ceramic components from CAD models. Various approaches to increase the solid loading in green parts are discussed including suspension preparation, image projection, layer recoating and separation. A prototype system based on the presented ceramics fabrication process has been developed. Test cases of different types of ceramics are presented to demonstrate the effectiveness of the presented fabrication method. The post-processing of green parts to convert them into dense ceramic components is also discussed with some sintering results presented.

An improved slicing algorithm with efficient contour construction using STL files

Slicing is an important step for all layer-based additive manufacturing (AM) processes. This paper proposes an improved and robust slicing algorithm with efficient contour construction to reduce the slicing time and be able to slice a complex STereoLithography (STL) model with millions of triangles (resulting from high-accuracy STL files). Also, another important feature of the proposed method is it can identify outer and inner contours automatically. Test results to demonstrate the improvements in execution time and comparisons with results from published papers have been given to illustrate the algorithm efficiency. The robustness of this slicing algorithm is demonstrated by several complex models with large numbers of nested contours on each slice.