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The industry standard for applying the identification nomenclature to Printed Circuit Boards (PCBs) is silkscreen legend printing, using white ink. This multi‐step process has minimal flexibility for applying unique legends e.g. serialization numbers to individual boards. This paper describes a new, alternative single step direct legend printing system which uses piezoelectric inkjet technology, the leading digital imaging method for a variety of industrial applications. The advantages that this, inherently clean and efficient, drop‐on‐demand, printing process brings to legend printing include increased flexibility, shorter process times, good legend definition, accurate placement, small footprint equipment and reduced labour and material usage.

This research compared the efficacy of process outcomes leveraging lean methods versus traditional pedagogy applied to dental education dependent on emerging technology. The pedagogical objective was to improve system efficiency without compromising traditional outcomes of effectiveness (quality).

The research team tested the efficacy of a lean A3 framework to identify, remove waste and redesign a technology-dependent simulation laboratory course (CAD/CAM/IR Restorative Dentistry). Students were also sensitized to time-in-chair to introduce a stronger patient focus. Baseline data collected from a control group were statistically compared to the research group's data after the course redesign. In addition, course time allocations were measured and then compared.

The results showed the interventions significantly reduced procedure cycle times without compromising quality. Additionally, the course was more efficiently conducted as measured by course time allocations.

This research demonstrated that the use of the A3 framework enhanced learning through process documentation, reengineering and systems optimization resolving issues of inefficiency associated with the CAD/CAM/IR pedagogy. This work is significant because it demonstrates the practice of using lean interventions to redesign and improve a technology-based healthcare course to maximize benefits.

This research is the first to examine how to leverage lean methods in a healthcare simulation laboratory, dependent on innovative technology, to educate and train future practitioners. This research applied statistical rigor in a controlled experiment to maximize its applicability and generalizability.

The purpose of this paper is to present an automatic approach for mesh sizing field generation of complicated  computer-aided design (CAD) models.

In this paper, the authors present an automatic approach for mesh sizing field generation. First, a source point extraction algorithm is applied to capture curvature and proximity features of CAD models. Second, according to the distribution of feature source points, an octree background mesh is constructed for storing element size value. Third, mesh size value on each node of background mesh is calculated by interpolating the local feature size of the nearby source points, and then, an initial mesh sizing field is obtained. Finally, a theoretically guaranteed smoothing algorithm is developed to restrict the gradient of the mesh sizing field.

To achieve high performance, the proposed approach has been implemented in multithreaded parallel using OpenMP. Numerical results demonstrate that the proposed approach is remarkably efficient to construct reasonable mesh sizing field for complicated CAD models and applicable for generating geometrically adaptive triangle/tetrahedral meshes. Moreover, since the mesh sizing field is defined on an octree background mesh, high-efficiency query of local size value could be achieved in the following mesh generation procedure.

How to determine a reasonable mesh size for complicated CAD models is often a bottleneck of mesh generation. For the complicated models with thousands or even ten thousands of geometric entities, it is time-consuming to construct an appropriate mesh sizing field for generating high-quality mesh. A parallel algorithm of mesh sizing field generation with low computational complexity is presented in this paper, and its usability and efficiency have been verified.

This paper aims to use cone-beam computed tomography (CBCT) and computer-aided design/3D printing technology to design and fabricate a drill guide template for access cavity preparation of permanent molars, and conduct a preliminary evaluation of its effectiveness.

CBCT scans were performed on two permanent maxillary first molars extracted due to periodontitis. Based on the scans, guide templates of access cavities were designed. The angle of the guiding cylinders was determined based on the direction of the long axis of the tooth. A 3D resin printer with high resolution was used to print the guide templates. The printed guide templates were used by a dentist with specialized clinical experience to perform access cavity preparation in a dental simulator. Then the prepared access cavities were scanned again by CBCT, and scan data were compared to the design data.

The 3D printed drill guide template had a close fit with the extracted tooth fit. The access cavity prepared using the guide template enabled the removal of the pulp chamber roof, and formed a straight-line access. Points were selected for measurement at regularly spaced intervals of 0.5 mm along the side wall of the access cavity. The mean deviation between the actual access cavities of the two permanent maxillary first molars and the designed cavities was less than 0.1 mm, with a maximum deviation of about 0.5 mm, showing a good conformance between the actual cavity and the designed cavity.

A drill guide template was designed and fabricated by 3D printing technology, which easily guided burs to complete the access cavity preparation work forming an ideal cavity shape with satisfying accuracy, and thus may reduce the complications during pulp chamber entry.

The paper aims to evaluate the influence of thermo-chemical cycles of oral fluids on the surface attributes (roughness and microhardness) of lithium disilicate glass-ceramic (LDC) crown restorations manufactured with CAD/CAM technology.

There have been 24 LDC crowns manufactured using the CAD/CAM process for their respective preparation dies ply methyl methacrylate (PMMA) of mandibular left second premolar tooth (n = 8 each group). The standard procedure was used to glaze 16 crown samples (Groups 2 and 3).Samples of Group 3 were aged with thermal (563°C and 5563°C) and pH (2–14) cycles. All 24 samples were tested with a Profilometer and a Vicker hardness tester was used for their surface roughness and hardness measurement, respectively.

In statistical examination on SPSS Statistics 20 (IBM) software, of surface roughness values (Ra) and Vicker hardness values from different groups, Tukey HSD test was executed in one-way ANOVA (a = 0.05). The means Ra for groups were accordingly Group 3 > Group1 > Group 2 (p < 0.001). Similarly, micro-hardness was in order of Group 2 > Group 1 > Group 3 (p < 0.001).

The research work does not have any limitations.

Surrounding temperature and pH significantly impact the surface characteristics of lithium disilicate crown restoration. The study also reveals the inverse relationship between surface roughness and surface hardness parameters. The observed results and facts revealed well in agreement with the past research studies.

Most layer‐based rapid prototyping systems use polygonal models as input. In addition, the input polygonal models need to be manifold and water‐tight; otherwise the built objects may have defects or the building process may fail in some cases. This paper aims to present a regulation method of an arbitrarily complex polygonal model for rapid prototyping and manufacturing applications.

The method is based on a semi‐implicit representation of a solid model named the layered depth‐normal images (LDNI), which sparsely encodes the shape boundary of a polygonal model in three orthogonal directions. In the method, input polygonal models or parametric equations are first converted into LDNI models. A regulation operator based on the computed LDNI models is presented. A volume tiling technique is developed for very complex geometries and high accuracy requirements. From the processed LDNI model, an adaptive contouring method is presented to construct a cell representation that includes both uniform and octree cells. Finally, two‐manifold and water‐tight polygonal mesh surfaces are constructed from the cell representation.

The LDNI‐based mesh regulation operation can be robust due to its simplicity. The accuracy of the generated regulated models can be controlled by setting LDNI pixel width. Parallel computing techniques can be employed to accelerate the computation in the LDNI‐based method. Experimental results on various CAD models demonstrate the effectiveness and efficiency of our approach for complex geometries.

The input polygonal model is assumed to be closed in our method. The regulated polygonal model based on our method may have a big file size.

A novel mesh regulation method is presented in this paper. The method is suitable for rapid prototyping and manufacturing applications by achieving a balance between simplicity, robustness, accuracy, speed and scalability. This research contributes to the additive manufacturing development by providing a digital data preparation method and related tools.

Examines the process of selective laser sintering [SLS] for rapid prototyping. Begins with a brief history of [SLS] then describes the main components of the SLS system, the build materials which are used and the actually process operating cycle by which models are produced. Looks at the 3‐D CAD data preparation and factors affecting the quality of the models. Concludes that selective laser sintering is a continually developing process and in particular much effort is being spent on the development of new materials for the models.

The manufacturability of extremely fine porous structures in the SLM process has rarely been investigated, leading to unpredicted manufacturing results and preventing steady medical or industrial application. The research objective is to find out the process limitation and key processing parameters for printing fine porous structures so as to give reference for design and manufacturing planning.

In metallic AM processes, the difficulty of geometric modeling and manufacturing of structures with pore sizes less than 350 μm exists. The manufacturability of porous structures in selective laser melting (SLM) has rarely been investigated, leading to unpredicted manufacturing results and preventing steady medical or industrial application. To solve this problem, a comprehensive experimental study was conducted to benchmark the manufacturability of the SLM process for extremely fine porous structures (less than 350 um and near a limitation of 100 um) and propose a manufacturing result evaluation method. Numerous porous structure samples were printed to help collect critical datasets for manufacturability analysis.

The results show that the SLM process can achieve an extreme fine feature with a diameter of 90 μm in stable process control, and the process parameters with their control strategies as well as the printing process planning have an important impact on the printing results. A statistical analysis reveals the implicit complex relations between the porous structure geometries and the SLM process parameter settings.

It is the first time to investigate the manufacturability of extremely fine porous structures of SLM. The method for manufacturability analysis and printing parameter control of fine porous structure are discussed.

The COVID-19 pandemic emphasises the need for antiviral materials that can reduce airborne and surface-based virus transmission. This study aims to propose the use of additive manufacturing (AM) and surrogate modelling for the rapid development and deployment of novel copper-tungsten-silver (Cu-W-Ag) microporous architecture that shows strong antiviral behaviour against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

The research combines selective laser melting (SLM), in-situ alloying and surrogate modelling to conceive the antiviral Cu-W-Ag architecture. The approach is shown to be suitable for redistributed manufacturing by representing the pore morphology through a surrogate model that parametrically manipulates the SLM process parameters: hatch distance (h_d), scan speed (S_s) and laser power (L_p). The method drastically simplifies the three-dimensional (3D) printing of microporous materials by requiring only global geometrical dimensions solving current bottlenecks associated with high computed aided design data transfer required for the AM of porous materials.

The surrogate model developed in this study achieved an optimum parametric combination that resulted in microporous Cu-W-Ag with average pore sizes of 80 µm. Subsequent antiviral evaluation of the optimum architecture showed 100% viral inactivation within 5 h against a biosafe enveloped ribonucleic acid viral model of SARS-CoV-2.

The Cu-W-Ag architecture is suitable for redistributed manufacturing and can help reduce surface contamination of SARS-CoV-2. Nevertheless, further optimisation may improve the virus inactivation time.

The study was extended to demonstrate an open-source 3D printed Cu-W-Ag antiviral mask filter prototype.

The evolving nature of the COVID-19 pandemic brings new and unpredictable challenges where redistributed manufacturing of 3D printed antiviral materials can achieve rapid solutions.

The papers present for the first time a methodology to digitally conceive and print-on-demand a novel Cu-W-Ag alloy that shows high antiviral behaviour against SARS-CoV-2.