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This paper aims to propose a global adaptive direct slicing technique of Non-Uniform Rational B-Spline (NURBS)-based sculptured surface for rapid prototyping where the NURBS representation is directly extracted from the computer-aided design (CAD) model. The imported NURBS surface is directly sliced to avoid inaccuracies due to tessellation methods used in common practice. The major objective is to globally optimize texture error function based on the available range of layer thicknesses of the utilized rapid prototyping machine. The total texture error is computed with the defined error function to verify slicing efficiency of this global adaptive slicing algorithm and to find the optimum number of slices. A variety of experiments are conducted to study the accuracy of the developed procedure, and the results are compared with previously developed algorithms.

This paper proposes a new adaptive algorithm which globally optimizes a texture error function produced by staircase effect for a user-defined number of layers. The adaptive slicing algorithm dynamically calculates optimized slicing thicknesses based on the rapid prototyping machine’s specifications to minimize the texture error function. This paper also compares the results of implementing the developed methodology with the results of previously developed algorithms and presents cost-effective optimum slicing layer thicknesses.

A new methodology for global adaptive direct slicing algorithm of CAD models, based on a texture error function for the final product and the possible layer thicknesses in rapid prototyping, has been developed and implemented. Comparing the results of implementation with the common practice for several case studies shows that the proposed approach has greater slicing efficiency. Typically, by utilizing this approach, the number of prototyping layers can be reduced by 20-50 per cent compared to the slicing with other algorithms, while maintaining or improving the accuracy of the final manufactured surfaces. Therefore, the developed slicing method provides a better solution to trade-off between the rapid prototyping time and the rapid prototyping accuracy. For the many advantages of global direct slicing, it can be seen as the future solution to the slicing process in rapid prototyping systems.

This paper presents an innovative approach in direct global adaptive slicing of the additive manufacturing parts. The novel definition of an error function which comprehensively addresses the resulting manufactured surface quality of the entire product allows presenting an objective function to solve and to find the optimum selection of all the layer thicknesses during the slicing process.

The purpose of this paper is to analyze hydromagnetic flow between two horizontal plates in a rotating system. The bottom plate is a stretching sheet and the top one is a solid porous plate. Heat transfer in an electrically conducting fluid bounded by two parallel plates is also studied in the presence of viscous dissipation.

Differential Transformation Method (DTM) is used to obtain a complete analytic solution for the velocity and temperature fields and the effects of different governing parameters on these fields are discussed through the graphs.

The obtained results showed that by adding a magnetic field to this system, transverse velocity component reduces between the two plates. Also as the Prandtl number increases, in presence of viscous dissipation, the temperature between the two plates enhances while an opposite behavior is observed when the viscous dissipation is negligible.

The equations of conservation of mass, momentum and energy are reduced to a non‐linear ordinary differential equations system. Differential Transformation Method is utilized to approximate the solution for velocity and temperature profiles.

In the last two decades with the rapid development of nonlinear science, there has appeared ever‐increasing interest of scientists and engineers in the analytical techniques for nonlinear problems. This paper considers linear and nonlinear systems that are not only regarded as general boundary value problems, but also are used as mathematical models in viscoelastic and inelastic flows. The purpose of this paper is to present the application of the homotopy‐perturbation method (HPM) and variational iteration method (VIM) to solve some boundary value problems in structural engineering and fluid mechanics.

Two new but powerful analytical methods, namely, He's VIM and HPM, are introduced to solve some boundary value problems in structural engineering and fluid mechanics.

Analytical solutions often fit under classical perturbation methods. However, as with other analytical techniques, certain limitations restrict the wide application of perturbation methods, most important of which is the dependence of these methods on the existence of a small parameter in the equation. Disappointingly, the majority of nonlinear problems have no small parameter at all. Furthermore, the approximate solutions solved by the perturbation methods are valid, in most cases, only for the small values of the parameters. In the present study, two powerful analytical methods HPM and VIM have been employed to solve the linear and nonlinear elastic beam deformation problems. The results reveal that these new methods are very effective and simple and do not require a large computer memory and can also be used for solving linear and nonlinear boundary value problems.

The results revealed that the VIM and HPM are remarkably effective for solving boundary value problems. These methods are very promoting methods which can be wildly utilized for solving mathematical and engineering problems.

This 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.

Subtractive 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.

The 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).

The 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.

The 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.

The purpose of this paper is to propose a method for simulating the profile of part edges as a result of the FDM process. Deviations from nominal edge shape are predicted as a function of the layer thickness and three characteristic angles depending on part geometry and build orientation.

Typical patterns of edge profiles were observed on sample FDM parts and interpreted as the effects of possible toolpath generation strategies. An algorithm was developed to generate edge profiles consistent with the patterns expected for any combination of input variables.

Experimental tests confirmed that the simulation procedure can correctly predict basic geometric properties of edge profiles such as frequency, amplitude and shape of periodic asperities.

The algorithm takes into account only a subset of the error causes recognized in previous studies. Additional causes could be integrated in the simulation to improve the estimation of geometric errors.

Edge simulation may help avoid process choices that result in aesthetic and functional defects on FDM parts.

Compared to the statistical estimation of geometric errors, graphical simulation allows a more detailed characterization of edge quality and a better diagnosis of error causes.

The purpose of the study is to obtain an analytical approximate solution for jamming transition problem (JTP) using Adomian decomposition method (ADM).

In this study, the jamming transition is presented as a result of spontaneous deviations of headway and velocity that is caused by the acceleration/breaking rate to be higher than the critical value. Dissipative dynamics of traffic flow can be represented within the framework of the Lorenz scheme based on the car-following model in the one-lane highway. Through this paper, an analytical approximation for the solution is calculated via ADM that leads to a solution for headway deviation as a function of time.

A highly nonlinear differential equation having no exact solution due to JTP is considered and headway deviation is obtained implementing a number of different initial conditions. The results are discussed and compared with the available data in the literature and numerical solutions obtained from a built-in numerical function of the mathematical software used in the study. The advantage of using ADM for the problem is presented in the study and discussed on the basis of the results produced by the applied method.

This is the first study to apply ADM to JTP.

Fused filament fabrication or fused deposition modeling (FFF/FDM) has as one of its main restrictions the surface quality intrinsic to the process, especially linked to the layer thickness used during manufacture. The purpose of this paper is to study the possibility of improving the surface quality of polylactic acid (PLA) parts manufactured by FFF using the shot blasting technique.

The influence of corundum blasting on 0.2 mm layer thickness FDM PLA parts treated with two sizes of abrasive, different exposure times and different incidence pressures.

As a result, improvements of almost 80% were obtained in the surface roughness of the pieces with high exposure times, and more than 50% in just 20 s.

This technique is cheap, versatile and adaptable to different part sizes and geometries. Furthermore, it is a fast and environmentally friendly technique compared to conventional machining or vapor smoothing. Despite this, no previous studies have been carried out to improve the quality of this technology.

Due to intrinsic limitations, fused deposition modelling (FDM) products suffer from the bad surface finish and inaccurate dimensional accuracies restricting its usage in many applications. Hence, there is a need for processing polymer patterns before, during and after their productions. This paper aims to highlight the importance of pre- and post-processing treatments on the FDM-based acrylonitrile butadiene styrene patterns improving its surface quality so, that it can be used in rapid investment casting process for making medical implants and other high precision components.

As a part of pre-processing treatment, the machine parameters affecting the surface quality were identified and optimised using design of experiments. The patterns developed after the first stage of optimisation were given different post-processing treatments, which included vapour smoothening, chemical treatment and sand paper polishing. The results were compared and the best ones were used for making patterns for making medical implants via rapid investment casting technique. The surface quality was checked while the dimensional changes happening during the stages of this hybrid technique were recorded using a three-dimensional optical scanner.

The surface roughness of the FDM based ABS patterns reduced from 21.63 to 14.40 µm with pre-processing treatments. Chemical treatment (post-processing treatment) turned to be the most suitable technique for reducing the surface roughness further down to 0.30 µm. Medical implants that used these pre- and post-processing treatments gave an average surface roughness of 0.68 µm. Cost and lead time comparisons showed that rapid investment casting technique can be a better method for low volume, customised and with specific requirements.

FDM parts/medical implants produced by rapid investment casting technique suffer from the inferior surface finish and inaccurate dimensional accuracies limiting its applications. A systematic approach to overcome this issue is presented in this research paper. This will directly help the end users and the manufacturers of medical implants, wherein, better surface finish and dimensionally accurate components are expected.

Fused deposition modelling (FDM) is the most economical additive manufacturing technique. The purpose of this paper is to describe a detailed review of this technique. Total 211 research papers published during the past 26 years, that is, from the year 1994 to 2019 are critically reviewed. Based on the literature review, research gaps are identified and the scope for future work is discussed.

Literature review in the domain of FDM is categorized into five sections – (i) process parameter optimization, (ii) environmental factors affecting the quality of printed parts, (iii) post-production finishing techniques to improve quality of parts, (iv) numerical simulation of process and (iv) recent advances in FDM. Summary of major research work in FDM is presented in tabular form.

Based on literature review, research gaps are identified and scope of future work in FDM along with roadmap is discussed.

In the present paper, literature related to chemical, electric and magnetic properties of FDM parts made up of various filament feedstock materials is not reviewed.

This is a comprehensive literature review in the domain of FDM focused on identifying the direction for future work to enhance the acceptability of FDM printed parts in industries.

Material extrusion is one of the most commonly used approaches within the additive manufacturing processes available. Despite its popularity and related technical advancements, process reliability and quality assurance remain only partially solved. In particular, the surface roughness caused by this process is a key concern. To solve this constraint, experimental plans have been exploited to optimize surface roughness in recent years. However, the latter empirical trial and error process is extremely time- and resource consuming. Thus, this study aims to avoid using large experimental programs to optimize surface roughness in material extrusion.

This research provides an in-depth analysis of the effect of several printing parameters: layer height, printing temperature, printing speed and wall thickness. The proposed data-driven predictive modeling approach takes advantage of Machine Learning (ML) models to automatically predict surface roughness based on the data gathered from the literature and the experimental data generated for testing.

Using ten-fold cross-validation of data gathered from the literature, the proposed ML solution attains a 0.93 correlation with a mean absolute percentage error of 13%. When testing with our own data, the correlation diminishes to 0.79 and the mean absolute percentage error reduces to 8%. Thus, the solution for predicting surface roughness in extrusion-based printing offers competitive results regarding the variability of the analyzed factors.

There are limitations in obtaining large volumes of reliable data, and the variability of the material extrusion process is relatively high.

Although ML is not a novel methodology in additive manufacturing, the use of published data from multiple sources has barely been exploited to train predictive models. As available manufacturing data continue to increase on a daily basis, the ability to learn from these large volumes of data is critical in future manufacturing and science. Specifically, the power of ML helps model surface roughness with limited experimental tests.