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The hygroscopic properties of 3D-printed filaments and moisture absorption itself during the process result in dimensional inaccuracy, particularly for nozzle movement along the x-axis and for micro-scale features. In view of that, this study aims to analyze in depth the dimensional errors and deviations of the fused filament fabrication (FFF)/fused deposition modeling (FDM) 3D-printed micropillars (MPs) from the reference values. A detailed analysis into the variability in printed dimensions below 1 mm in width without any deformations in the printed shape of the designed features, for challenging filaments like polymethyl methacrylate (PMMA) has been done. The study also explores whether the printed shape retains the designed structure.

A reference model for MPs of width 800 µm and height 2,000 µm is selected to generate a g-code model after pre-processing of slicing and meshing parameters for 3D printing of micro-scale structure with defined boundaries. Three SETs, SET-A, SET-B and SET-C, for nozzle diameter of 0.2 mm, 0.25 mm and 0.3 mm, respectively, have been prepared. The SETs containing the MPs were fabricated with the spacing (S) of 2,000 µm, 3,200 µm and 4,000 µm along the print head x-axis. The MPs were measured by taking three consecutive measurements (top, bottom and middle) for the width and one for the height.

The prominent highlight of this study is the successful FFF/FDM 3D printing of thin features (<1mm) without any deformation. The mathematical analysis of the variance of the optical microscopy measurements concluded that printed dimensions for micropillar widths did not vary significantly, retaining more than 65% of the recording within the first standard deviation (SD) (±1 s). The minimum value of SD is obtained from the samples of SET-B, that is, 31.96 µm and 35.865 µm, for height and width, respectively. The %RE for SET-B samples is 5.09% for S = 2,000µm, 3.86% for S = 3,200µm and 1.09% for S = 4,000µm. The error percentage is so small that it could be easily compensated by redesigning.

The study does not cover other 3D printing techniques of additive manufacturing like stereolithography, digital light processing and material jetting.

The presented study can be potentially implemented for the rapid prototyping of microfluidics mixer, bioseparator and lab-on-chip devices, both for membrane-free bioseparation based on microfiltration, plasma extraction from whole blood, size-selection trapping of unwanted blood cells, and also for membrane-based plasma extraction that requires supporting microstructures. Our developed process may prove to be far more economical than the other existing techniques for such applications.

For the first time, this work presents a comprehensive analysis of the fabrication of micropillars using FDM/FFF 3D printing and PMMA in filament form. The primary focus of the study is to minimize the dimensional inaccuracies in the 3D printed devices containing thin features, especially in the area of biomedical engineering, by delivering benefits from the choice of the parameters. Thus, on the basis of errors and deviations, a thorough comparison of the three SETs of the fabricated micropillars has been done.

Additive manufacturing also known as 3D printing is an evolving advanced manufacturing technology critical for the new era of complex machinery and operating systems. Manufacturing systems are increasingly faced with risk of attacks not only by traditional malicious actors such as hackers and cyber-criminals but also by some competitors and organizations engaged in corporate espionage. This paper aims to elaborate a plausible risk practice of designing and demonstrate a case study for the compromised-based malicious for polymer 3D printing system.

This study assumes conditions when a machine was compromised and evaluates the effect of post compromised attack by studying its effects on tensile dog bone specimens as the printed object. The designed algorithm removed predetermined specific number of layers from the tensile samples. The samples were visually identical in terms of external physical dimensions even after removal of the layers. Samples were examined nondestructively for density. Additionally, destructive uniaxial tensile tests were carried out on the modified samples and compared to the unmodified sample as a control for various mechanical properties. It is worth noting that the current approach was adapted for illustrating the impact of cyber altercations on properties of additively produced parts in a quantitative manner. It concurrently pointed towards the vulnerabilities of advanced manufacturing systems and a need for designing robust mitigation/defense mechanism against the cyber altercations.

Density, Young’s modulus and maximum strength steadily decreased with an increase in the number of missing layers, whereas a no clear trend was observed in the case of % elongation. Post tensile test observations of the sample cross-sections confirmed the successful removal of the layers from the samples by the designed method. As a result, the current work presented a cyber-attack model and its quantitative implications on the mechanical properties of 3D printed objects.

To the best of the authors’ knowledge, this is the original work from the team. It is currently not under consideration for publication in any other avenue. The paper provides quantitative approach of realizing impact of cyber intrusions on deteriorated performance of additively manufactured products. It also enlists important intrusion mechanisms relevant to additive manufacturing.

The purpose of this study is asking for a methodologically representable relation between different relative velocity approaches, counter surfaces and the tribological behavior of the radial shaft seal (RSS).

The tribological behavior between the seal and the counterpart is examined experimentally to submit significant measured values. The correlations among seal elements, relative velocity approaches and counter surfaces with more aspects are searched.

A basis for future research regarding optimization options for service life extension of the RSS under different operation environments has been set. New insights for the performance of 3D-printed counter surface are gained as well as the application possibility of that is searched.

The applied measuring procedure in investigation part especially the usage of different approaches in relative velocity approaches is designed with originality. In particularly, the usage of a 3D-printed counter surface comes for the first time in a scientific work.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2022-0325/

This study aims to model the important flow response quantities over a shrinking wedge with the help of response surface methodology (RSM) and an artificial neural network (ANN). An ANN simulation for optimal thermal transport of incompressible viscous fluid under the impact of the magnetic effect (MHD) over a shrinking wedge with sensitivity analysis and optimization with RSM has yet not been investigated. This effort is devoted to filling the gap in existing literature.

A statistical experimental design is a setup with RSM using a central composite design (CCD). This setup involves the combination of values of input parameters such as porosity, shrinking and magnetic effect. The responses of skin friction coefficient and Nusselt number are required against each parameter combination of the experimental design, which is computed by solving the simplified form of the governing equations using bvp4c (a built-in technique in MATLAB). An empirical model for Cf_x and Nu_x using RSM and ANN adopting the Levenberg–Marquardt algorithm based on trained neural networks (LMA-TNN) is attained. The empirical model for skin friction coefficient and Nusselt number using RSM has 99.96% and 99.99% coefficients of determination, respectively.

The values of these matrices show the goodness of fit for these quantities. The authors compared the results obtained from bvp4c, RSM and ANN and found them all to be in good agreement. A sensitivity analysis is performed, which shows that Cf_x as well as Nu_x are most affected by porosity. However, they are least affected by magnetic parameters.

This study aims to simulate ANN and sensitivity analysis for optimal thermal transport of magnetic viscous fluid over shrinking wedge.

Following the recent rise in generative artificial intelligence (GenAI) tools, fundamental questions about their wider impacts have started to reverberate around various disciplines. This study aims to track the unfolding landscape of general issues surrounding GenAI tools and to elucidate the specific opportunities and limitations of these tools as part of the technology-assisted enhancement of mechanical engineering education and professional practices.

As part of the investigation, the authors conduct and present a brief scientometric analysis of recently published studies to unravel the emerging trend on the subject matter. Furthermore, experimentation was done with selected GenAI tools (Bard, ChatGPT, DALL.E and 3DGPT) for mechanical engineering-related tasks.

The study identified several pedagogical and professional opportunities and guidelines for deploying GenAI tools in mechanical engineering. Besides, the study highlights some pitfalls of GenAI tools for analytical reasoning tasks (e.g., subtle errors in computation involving unit conversions) and sketching/image generation tasks (e.g., poor demonstration of symmetry).

To the best of the authors’ knowledge, this study presents the first thorough assessment of the potential of GenAI from the lens of the mechanical engineering field. Combining scientometric analysis, experimentation and pedagogical insights, the study provides a unique focus on the implications of GenAI tools for material selection/discovery in product design, manufacturing troubleshooting, technical documentation and product positioning, among others.

This study aims to explore the potential benefits favoring the adaptation of structural optimization techniques in the additive manufacturing (AM) of medical utilities to meet the repetitive demand for functionally precise customized orthoses. Irregularities encountered during the conventional treatment of tendon injuries can be eschewed using advanced structural simulation in design and innovative splint fabrication using 3D printing.

A customized mallet finger splint designed from 3D scans was subjected to ANSYS topological simulation comprising multi-level weight reduction to retain optimal mass (100%, 90%, 80%, 70% and 60%). A batch of the four typical 3D printing materials was chosen to conduct a comparative mechanical and thermal stress analysis, facilitating the selection of the optimal one for fabricating functionally adaptive splints. Assurance of structural safety was accomplished through the experimental validation of simulation results against the testing data set of ASTM D695 and ASTM D638 Type-1 specimens over a universal testing machine (UTM). Fused deposition modeling (FDM) 3D printing processed the optimized splint fabrication to assist evaluation of weight reduction percentage, fitting aesthetics, appearance, comfort, practicality and ventilation ease at the user end.

AM efficacy can efficiently execute the design complexity involved in the topology optimization (TO) results and introduces rehabilitation practicality into the application. Topologically optimized splint provided with favorable comfort, stiffness and strengthening features, offers ventilation ease and structural stability for customized appliances, with 30.52% lighter weight and 121.37% faster heat dissipation than unoptimized one.

The state of art multidisciplinary optimization featured with structural and material optimization attributes can deliberately meet medical necessity for performance-oriented orthotic devices.

In recent years, increased use of all-aspect infrared (IR)-guided missiles based on the long-wave infrared (LWIR; 8–12 µm) band has lowered the probability of aircraft survival in warfare. The lock-on of these highly sensitive missiles is difficult to break, especially from the front. Aerodynamically heated swept-back leading edges (SBLE), because of their high temperature and large area, serve as a prominent LWIR source for aircraft detection from the front. This study aims to report the influence of sweep-back angle (Λ, based on the Mach number [M_∞]) on aerodynamic heating and the LWIR signature of SBLE.

The temperature along SBLE is obtained numerically as radiation equilibrium temperature (T_w) by discretizing the SBLE length into “n” number of segments, and for each segment, emission based on T_w is evaluated. IR radiance due to reflected external sources (sky-shine and Earthshine) and radiance due to T_w are collectively used to determine the IR contrast between SBLE and its replaced background in the LWIR band (i_{cont-SBLE,LWIR}).

The results are obtained for low subsonic turboprop aircraft (Λ = 3°, M_∞ = 0.44); high subsonic strategic bombers (Λ = 35°, M_∞ = 0.8); fifth-generation stealth aircraft (Λ = 40°, M_∞ = 1.6); and aircraft with supercruise/supersonic capability (Λ = 50°, M_∞ = 2.5). The aircraft with supersonic capability (Λ = 50°, M_∞ = 2.5) reports the maximum LWIR signatures and hence the highest visibility from the front. The results obtained are compared with values at Λ = 0° for all cases, which shows that increasing Λ significantly reduces aerodynamic heating and LWIR signatures.

The novelty of this study comes from its report on the influence of Λ on the LWIR signatures of aircraft SBLE in the frontal aspect for the first time.

The export competitiveness has only calculated on only two aspects either comparatively advantageous or comparatively disadvantageous products for India or China. There is not any thorough study that has been undertaken for Indian manufacturing sector at a segregated level along with that of China. So, in the light of these shortcomings, the purpose of this study is to analyse the dynamics of export competitiveness of indian manufacturing sector vis-à-vis its emerging counterpart, china in the global market.

A modified revealed comparative advantage index has been used in two different phases of 2001–08 and 2010–18 to find the dynamic pattern of manufacturing exports of India and China in the world market.

The study revealed that India has shown a positive response in increasing its competitive positioned products from low-technology to medium-technology products during the study period. There has been a decline in the competitive positioned products of China and simultaneously China’s threatened product lines have shown an immense increment over the years. Moreover, Indian exports are concentrated to few low-technology and resource-intensive products, that share more than 50% of total exported value for its manufacturing in the global market, whereas, China is much diversified and the exported value is more scattered over its manufactured items.

The study does not include the factors that impacted the export competitiveness of the sample economies and thus adds a limitation to this study.

As there is very limited research on dynamics of export competitiveness of Indian manufacturing exports at harmonised system 6-digit level with China, this study fulfils the gap.