Staircase Effect Research Articles

COMPARATIVE STUDY OF MATERIAL EXTRUSION AND VAT PHOTOPOLYMERIZATION ADDITIVE MANUFACTURING TECHNIQUE USING SQUARE BASE PYRAMID AS AN ARTIFACT AND APPLICATIONS

A comparative analysis of Material Extrusion and VAT Photopolymerization 3D printing is done using various geometrical models, including square base pyramid, co-centric circular stamps, and lattice structures. The pyramid with Council of Scientific and Industrial Research (CSIR) and National Physical Laboratory (NPL) logos, texts printed by both techniques is studied for its dimensional accuracy as per the process parameters. The 3D printed specimen by Material Extrusion measured an average layer thickness of ~ 104 µm and VAT Photopolymerization measured a layer thickness of ~ 54 µm. The calculated void volume of the printed pyramid due to the staircase effect is ~ 2.9 % for the Material Extrusion and ~ 0.14 % for the VAT Photopolymerization. Mechanical properties of ASTM D638 tensile test samples based on build orientation showed anisotropy for Material Extrusion, whereas VAT Photopolymerization printed test samples are isotropic. The degree of anisotropy (DOA) of 0.35, modulus of elasticity (MOE) of 1.7 GPa and ultimate tensile strength (UTS) of 62 MPa are measured for the Material Extrusion printed test sample. The ZXY build-oriented test sample showed the lowest values compared to all the other build orientations. Comparatively, the MOE and UTS for the VAT Photopolymerization printed samples are equal for all build orientations and are ~ 950 MPa and ~ 39 MPa, respectively. The applicability of the present comparison of 3D printing techniques is demonstrated through functionality studies of printed stamps for ring electrodes and lattice structures as templates. The active area of the Fused deposition modeling (FDM) printed ring electrodes for maximum resolution is 17 times larger compared to that of Digital light processing (DLP) printed stamps. Additionally, the mean pore size for FDM-printed lattice structures was found to be ~ 650 µm, while the lattice structure printed by DLP using Polyurethan acrylate resin exhibited a pore size of ~ 220 µm. This analysis evaluates the dependence of stamp size due to print resolution specific to the technique. The importance of this research lies in addressing the growing demand for optimized 3D printing processes in manufacturing applications, such as sensors, electrodes, and structural components. By comparing dimensional accuracy, surface finish, print resolution, and mechanical properties, this study offers valuable insights into how the selection of printing techniques and process parameters can significantly influence the final product's performance.

Investigations on the effect of vapor smoothing process in trichloromethane (chloroform) on the surface characteristics, mechanical properties and chemical structure of 3D printed Poly-Lactic-Acid (PLA)

Abstract 3D printing has become a prominent method for prototyping and manufacturing intricate geometric components. However, the inherent staircase effect often leaves 3D printed parts with suboptimal surface smoothness. To address this issue, post-processing techniques like vapor smoothing, involving the use of trichloromethane (chloroform) vapors, are employed. This paper presents experimental investigations on 3D printed PLA parts subjected to vapor smoothing, with a focus on varying the process time. Experimental determinations of elongation, tensile strength, and surface finish provide insights into the influence of process time on these critical features of 3D printed PLA components. The selection of an optimal process time emerges as a crucial factor in achieving a harmonious balance between surface characteristics and mechanical properties. The novelty of this research lies in establishing correlations between changes in PLA elongation, tensile strength, and surface finish post-vapor smoothing and the corresponding alterations in the chemical structure of PLA. The study reveals the synergistic physical and chemical interactions between chloroform vapors and PLA structure that result in enhanced surface finish. Simultaneously, the process time is identified as a key determinant governing the extent of changes in mechanical properties. Consequently, this work aims to elucidate the mechanisms responsible for the observed combination of properties and surface characteristics through Fourier-transform infrared (FTIR) analysis concerning vapor smoothing process time.

A First-Order Image Super-Resolution Model Promoting Sharp Boundaries and Suppressing the Staircase Effect

A First-Order Image Super-Resolution Model Promoting Sharp Boundaries and Suppressing the Staircase Effect

Synergistic impact of scan strategy and scan angles in laser powder bed fusion process on mechanical, tribological and cell viability properties of porous 316L SS structure

Poor load bearing ability and concentrated stress within cross-linked porous structures was found to be the major cause for the mechanical and wear failure of SS (Stainless Steel) 316L implants. Therefore, the present study introduces a novel scan pattern to enhance the mechanical and wear properties. Importantly, the role of porous structures on the constituents and formation of Tribo-film regimes under the simulated body fluid (SBF) condition were assessed using the X-ray photoelectron spectroscopy (XPS). Furthermore, the impact of the surface roughness of porous structures on the cell adhesion and cytotoxicity were explored. Various cross-linked porous structures are produced at three different scanning rotation angles (0°, 45°, and 90°) using the Laser powder bed fusion (LPBF) process. Morphology analysis reveals balling and stair-case effects at 0°, controlled for structures built at 45° and 90°. Porous-90° structure exhibits negative skewness and a platykurtic surface with low peaks and more valleys. It demonstrates higher strength with low density due to better particle fusion, net-like structure, and uniform element distribution. X-ray photoelectron spectroscopy (XPS) evaluates the impact of porous structures on Tribo-film regimes in simulated body fluid. Surface roughness effects on cell adhesion and cytotoxicity are also investigated. Cross linked porous structures presented two major compression failure modes include wrinkling and diagonal shearing. The densified structure of Porous-45° reduces contamination and cell death, facilitating stable cell growth. Tribo-film formation and load bearing ability of Porous-90° structure was better than the other structures, due to the cross-linked netlike structure and further more detailed in the XPS study.

Poisson noise removal based on non-convex hybrid regularizers

The presence of TV regularizer always induces an unsatisfactory staircase effect. To overcome the staircase while better sustaining edge information, this work proposes a novel model for Poisson noise removal. The model is based on non-convex mixed regularizers, which involves introducing a non-convex penalty into a composition of the total variation and the higher-order total variation. The iterative reweighted l1 algorithm was used to convert the non-convex model into a convex one. The classic alternating direction method of multipliers was then employed to obtain approximate solutions of the model. When applying this model to degraded images contaminated by Poisson noise of medium to high intensity, its performance in noise suppression was tested. The regularizer was compared with others in the terms of the visual effect of the picture, time cost, and several commonly accepted quantitative indicators for evaluation, such as peak signal-to-noise ratio, feature similarity index and structural similarity index. Numerical experiments showed that the present model not only eliminates block artifacts but also retains sharp edges.

Surface Anisotropy on 3D Printed Parts

It is well known that the surface quality obtained in additive manufacturing processes is highly variable. There are several reasons for this, of which the most prominent is the staircase effect, which results from the fact that 3D printing can be actually considered as a 2.5 machining process, as we build the part layer by layer. However, this staircase effect can be very different on surfaces that are arranged in different ways. By measuring the values that characterise the surfaces (Ra, Rz), however, we can observe that they are direction dependent, i.e. it does not matter how we measure them. This phenomenon is called surface anisotropy. It is clear that the surface roughness also has an effect on the tribological behaviour. In the case of a component where it is in contact with another component and relative displacement occurs between them, frictional properties may play a prominent role, which may thus also become direction dependent. Surface roughness also has a clear effect on fatigue properties. Consequently, for parts undergoing periodic dynamic stresses, it may be important to choose the right manufacturing orientation. The present study aims to demonstrate the extent of variation in surface roughness on different surfaces of a part produced by FDM. For this purpose, surface quality factors are investigated and evaluated on a self-designed model produced with given manufacturing parameters.

Primal-dual hybrid gradient image denoising algorithm based on overlapping group sparsity and fractional-order total variation

This study introduces a non-convex fractional-order hyper-Laplacian variational model for Gaussian noise removal. It employs first the primal-dual hybrid gradient algorithm to solve problems involving overlapping group sparse structures. Additionally, this paper designs a new algorithm leveraging the framework of the Chambolle-Pock algorithm with convergence and aims to recover high-quality images. The model, integrating the overlapping group sparse structure of the hyper-Laplacian prior with the non-convex fractional-order total variation, exhibits superior performance in reducing the staircase effect and maintaining sharp edge contours. To further improve the performance of the algorithm, a semi-adaptive p(x) non-convex penalty weight assignment mechanism is designed by introducing the structure tensor, which according to the characteristics of each region of the image and the noise level. The effectiveness and superiority of the proposed algorithm in image denoising with simulation experiments and comparative analyses are fully verified.

Extreme roughness reduction and ultrafine quality of innovative dual function material extrusion 3D printer

PurposeThis paper aims to use hybrid manufacturing (HM) to overcome several drawbacks of material extrusion three-dimensional (3D) printers, such as low dimension ranging from 0.2 to 0.5 µm, resulting in a noticeable staircase effect and elevated surface roughness.Design/methodology/approachSubtractive manufacturing (SM) through computer numerical control milling is renowned for its precision and superior surface finish. This study integrates additive manufacturing (AM) and SM into a single material extrusion 3D printer platform, creating a HM system. Two sets of specimens, one exclusively printed and the other subjected to both printing and milling, were assessed for dimension accuracy and surface roughness.FindingsThe outcomes were promising, with postmilling accuracy reaching 99.94%. Significant reductions in surface roughness were observed at 90° (93.4% decrease from 15.598 to 1.030 µm), 45° (89% decrease from 26.727 to 2.946 µm) and the face plane (71% decrease from 12.176 to 3.535 µm).Practical implicationsThe 3D printer was custom-built based on material extrusion and modified with an additional milling tool on the same gantry. An economic evaluation based on cost-manufacturing demonstrated that constructing this dual-function 3D printer costs less than US$560 in materials, offering valuable insights for researchers looking to replicate a similar machine.Originality/valueThe modified general 3D printer platform offered an easy way to postprocessing without removing the workpiece from the bed. This mechanism can reduce the downtime of changing the machine. The proven increased dimension accuracy and reduced surface roughness value increase the value of 3D-printed specimens.

Development of a hybrid model to estimate surface roughness of 3D printed parts

The research aims to develop a hybrid model to estimate the surface roughness of 3D printed parts, considering the significant process parameters and measurement uncertainties inherent in additive manufacturing (AM). The methodology involves a Taguchi L-27 orthogonal array design of experiments (DOE) to identify significant factors. This is followed by a deep dive analysis of the roughness profile and the modelling of the measurement process uncertainties. The ANOVA tests reveal that build orientation and layer height are critical contributors to surface roughness. However, it was evident from the experimental analysis that the layer height and build orientation shares a complex relation on surface roughness. The two novelties of this paper are: one, the development of a hybrid model of surface roughness by mathematically quantifying the staircase (step and stack) and corner geometry effects of the part geometry. Two, strengthening the model’s surface roughness prediction accuracy by incorporating the stylus flight and probe reachability measurement uncertainty functions. The final mathematical function was validated with multiple experimental data as well as literature data. The results show that the proposed model is robust to estimate the surface finish accurately at build orientations in the full range of 0–90 degree. The statistical analysis shows that the proposed model is capable of accurately predicting about 90 % variations in the data at different layer heights and build orientations. The proposed model is useful to accurately predict the surface finish of 3D printed parts, a priori, during the part design or before printing, thereby improving the surface quality of the AM parts.

Investigation of remeshing parameters for deviation analysis in reverse engineering

The use of additive manufacturing technologies in industry is increasingly common, particularly with the emergence of Industry 4.0. These technologies can produce parts quickly and efficiently, but they also place higher demands on the quality of the manufactured products. The layer-by-layer processes create an anisotropic material model, which complicates component sizing. While the topic has been extensively researched, surface anisotropy has received less attention. The surface quality of a product may be affected by various factors, including the file conversion process or the staircase effect generated by the technology. Manufacturing parameters, such as layer thickness and orientation, can also have an impact. This paper focuses on the impact of reverse engineering step adjustment on surface quality.

Spectral Behavior of Fiber Bragg Gratings during Embedding in 3D-Printed Metal Tensile Coupons and Cyclic Loading.

Additive manufacturing (AM) enables the spatially configurable 3D integration of sensors in metal components to realize smart materials and structures. Outstanding sensing capabilities and size compatibility have made fiber optic sensors excellent candidates for integration in AM components. In this study, fiber Bragg grating (FBG) sensors were embedded in Inconel 718 tensile coupons printed using laser powder bed fusion AM. On-axis (fiber runs through the coupon's center of axis) and off-axis (fiber is at 5° and 10° to the coupon's center of axis) sensors were buried in epoxy resin inside narrow channels that run through the coupons. FBGs' spectral evolutions during embedment in the coupons were examined and cyclic loading experiments were conducted to analyze and evaluate the sensor integration process, complex strain loading, process flaws, and sensing performance. This study also demonstrates that the AM process-born deficiencies such as poor surface finish and staircase effects can be detrimental to the embedded sensors and their sensing performance.

Surface Finish Optimization of Vapor Smoothened PLA Fabricated Parts with Microstructural Analysis

Additive Manufacturing (AM) is a product creation method done layer-by-layer. This process tends to create an unwanted feature known as staircase effect. Vapor smoothing is considered a viable solution for polymer-based AM products to minimized surface roughness. Research literature concerning vapor smoothing of polylactic acid (PLA) parts generally limited unlike its ABS counterpart. This research aims to identify optimum level for both chamber temperature and exposure time of the AM product. Two methods were used to compare their outputs with one another. The two methods are surface roughness tester and optical microscopy. The results provided an impressive 50.88 and 62.72% improvement based on the two test methods. Lastly, a contour-plot was generated to provide future users a guideline if they want to conduct research similar study.

Continuous 3D printing of metal structures using ultrafast mask video projection initiated vat photopolymerization

Additive manufacturing (AM) has recently emerged as the go-to technology for producing high-quality metal components to address cutting-edge research and industrial challenges. However, existing metal AM technologies operate on a layer-by-layer basis, giving rise to undesirable "staircasing effects" that result in the anisotropic behavior. Additionally, conventional metal printing methods are constrained by printing times, expensive hardware, and limited resolution control. In response to these limitations, this work is dedicated to the development of a cost-effective, ultra-fast layerless metal AM process for crafting intricate 3D metal structures. Low viscous resin was developed to enable continuous printing of metal precursors via mask video projection-based vat photopolymerization, which enable tunable physical properties and superior surface quality. Based on experimental findings, high-density meso- and microscale metallic parts can be printed at speeds orders of magnitude faster than commercial metal AM technologies. Furthermore, printed metallic components display a uniform morphology and microstructure with consistent grain size distribution. A comparative analysis of the surface quality between layer-based and layer-less printed metal structures were conducted. This work has the potential to revolutionize not only the field of AM but also various industries reliant on high-quality metal components, such as aerospace, automotive, and medical devices.

Volumetric Additive Manufacturing of SiOC by Xolography.

Additive manufacturing (AM) of ceramics has significantly contributed to advancements in ceramic fabrication, solving some of the difficulties of conventional ceramic processing and providing additional possibilities for the structure and function of components. However, defects induced by the layer-by-layer approach on which traditional AM techniques are based still constitute a challenge to address. This study presents the volumetric AM of a SiOC ceramic from a preceramic polymer using xolography, a linear volumetric AM process that allows to avoid the staircase effect typical of other vat photopolymerization techniques. Besides optimizing the trade-off between preceramic polymer content and transmittance, a pore generator is introduced to create transient channels for gas release before decomposition of the organic constituents and moieties, resulting in crack-free solid ceramic structures even at low ceramic yield. Formulation optimization alleviated sinking of printed parts during printing and prevented shape distortion. Complexsolid and porous ceramic structures with a smooth surface and sharp features are fabricated under the optimized parameters. This work provides a new method for the AM of ceramics at µm/mm scale with high surface quality and large geometry variety in an efficient way, opening the possibility for applications in fields such as micromechanical systems and microelectronic components.

Chemical treatment in 3D dental model production for clear aligners via additive manufacturing: a comprehensive evaluation

PurposeStereolithography (SLA) additive manufacturing (AM) technique has enabled the production of inconspicuous and aesthetically pleasing orthodontics that are also hygienic. However, the staircase effect poses a challenge to the application of invisible orthodontics in the dental industry. The purpose of this study is to implement chemical postprocessing technique by using isopropyl alcohol as a solvent to overcome this challenge.Design/methodology/approachFifteen experiments were conducted using a D-optimal design to investigate the effect of different concentrations and postprocessing times on the surface roughness, material removal rate (MRR), hardness and cost of SLA dental parts required for creating a clear customized aligner, and a container was constructed for chemical treatment of these parts made from photocurable resin.FindingsThe study revealed that the chemical postprocessing technique can significantly improve the surface roughness of dental SLA parts, but improper selection of concentration and time can lead to poor surface roughness. The optimal surface roughness was achieved with a concentration of 90 and a time of 37.5. Moreover, the dental part with the lowest concentration and time (60% and 15 min, respectively) had the lowest MRR and the highest hardness. The part with the highest concentration and time required the greatest budget allocation. Finally, the results of the multiobjective optimization analysis aligned with the experimental data.Originality/valueThis paper sheds light on a previously underestimated aspect, which is the pivotal role of chemical postprocessing in mitigating the adverse impact of stair case effect. This nuanced perspective contributes to the broader discourse on AM methodologies, establishing a novel pathway for advancing the capabilities of SLA in dental application.

A Mathematical Algorithm for Improving the Medical Image

In this paper, we present a hybrid model based on total generalized variation (TGV) and shearlet with non-quadratic fidelity data terms for blurred images corrupted by impulsive and Poisson noises. Numerical experiments demonstrate that the proposed can reduce the staircase effect while preserving edges and outperform classical TV-based models in the peak signal-to-noise ratio (PSNR).

A novel improved total variation algorithm for the elimination of scratch-type defects in high-voltage cable cross-sections.

In the quality inspection process of high-voltage cables, several commonly used indicators include cable length, insulation thickness, and the number of conductors within the core. Among these factors, the count of conductors holds particular significance as a key determinant of cable quality. Machine vision technology has found extensive application in automatically detecting the number of conductors in cross-sectional images of high-voltage cables. However, the presence of scratch-type defects in cut high-voltage cable cross-sections can significantly compromise the precision of conductor count detection. To address this problem, this paper introduces a novel improved total variation (TV) algorithm, marking the first-ever application of the TV algorithm in this domain. Considering the staircase effect, the direct use of the TV algorithm is prone to cause serious loss of image edge information. The proposed algorithm firstly introduces multimodal features to effectively mitigate the staircase effect. While eliminating scratch-type defects, the algorithm endeavors to preserve the original image's edge information, consequently yielding a noteworthy enhancement in detection accuracy. Furthermore, a dataset was curated, comprising images of cross-sections of high-voltage cables of varying sizes, each displaying an assortment of scratch-type defects. Experimental findings conclusively demonstrate the algorithm's exceptional efficiency in eradicating diverse scratch-type defects within high-voltage cable cross-sections. The average scratch elimination rate surpasses 90%, with an impressive 96.15% achieved on cable sample 4. A series of conducted ablation experiments in this paper substantiate a significant enhancement in cable image quality. Notably, the Edge Preservation Index (EPI) exhibits an improvement of approximately 20%, resulting in a substantial boost to conductor count detection accuracy, thus effectively enhancing the quality of high-voltage cable production.

A multi-directional fractional-order variation with luminance term for infrared and visible image fusion

Infrared and visible image fusion strives to effectively combine the advantageous information from input images to achieve a fused result. In this paper, we propose a novel multi-directional fractional-order variation to fuse infrared-visible images. First, each fidelity term of each source image is modeled straightforwardly by Euclidean norm, ensuring robust optimization. Then, the detail regularization term is formulated based on fractional variation in two, four, and eight directions instead of integral variation, which enables the capture of more comprehensive detail while avoiding the undesirable staircase effect. Furthermore, the fused image is enhanced by transferring the highest level of brightness from the source images in the luminance regularization. Finally, based on the extensive experiments, the proposed method exhibits superior performance in both subjective and objective evaluations compared to existing others. Moreover, our method is further expanded to the multi-modal medical image fusion, achieving promising performance preliminarily.

An adaptive fractional-order regularization primal-dual image denoising algorithm based on non-convex function

In this paper, a novel non-convex fractional-order image denoising model is proposed to suppress the staircase effect produced by the TV model while maintaining a neat contour. The model combines ℓq(0<q<1) quasi-norm and fractional-order regularization, and employs a diffusion coefficient with a faster convergence rate to preserve more image edges and details. Additionally, an adaptive regularization parameter is designed to adjust the denoising performance of the algorithm. To obtain the optimal approximate solution of the model, an enhanced primal-dual algorithm is adopted and the complexity and convergence of the algorithm are theoretically analyzed. Finally, the effectiveness of the proposed method is demonstrated through numerical experiments.

Surface texture characterisation of longitudinal and latitudinal external and internal surfaces of laser powder bed fusion processed bespoke ball artefact

This research aims to study the diverse surface topographical features that emerge on both longitudinal and latitudinal facets' external and internal surfaces of a bespoke ball artefact. The focus variation measurement technique is employed to visually inspect the surface quality derived from a plethora of surface topographical defects and asperities namely balling, staircase effect, spatters, and un-melted/partially melted particles. These diverse defects, asperities and associated surface quality are characterised and correlated with an array of suitable areal surface texture height and hybrid parameters, and quantified with newly developed feature-based particle analysis mentioned in ISO 25178-2. The longitudinal facet external surfaces measurement range is selected from 15° to 135°, while internal surfaces measurement is performed between 15° to 165°. Similarly, the latitudinal facet external and internal surfaces are examined by full-turn at the equator. A comprehensive statistical analysis of variance (ANOVA) is employed to examine the statistical significance of inclinations angles, build orientations, and types of surfaces. The experimental results and ANOVA analysis showed that a strong interrelationship exists between the different build inclination angles and the distinct surface topographical features that emerge on longitudinal facet external and internal surfaces, while the latitudinal facet external and internal surfaces presented minimal difference in surface quality.