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The purpose of this paper is to describe, review, classify and analyze the current challenges in three-dimensional printing processes for combined electrochemical and microfluidic fabrication areas, which include printing devices and sensors in specified areas.

A systematic review of the literature focusing on existing challenges is carried out. Focused toward sensors and devices in electrochemical and microfluidic areas, the challenges are oriented for a discussion exploring the suitability of printing varied geometries in an accurate manner. Classifications on challenges are based on four key categories such as process, material, size and application as the printer designs are mostly based on these parameters.

A key three-dimensional printing process methodologies have their unique advantages compared to conventional printing methods, still having the challenges to be addressed, in terms of parameters such as cost, performance, speed, quality, accuracy and resolution. Three-dimensional printing is yet to be applied for consumer usable products, which will boost the manufacturing sector. To be specific, the resolution of printing in desktop printers needs improvement. Printing scientific products are halted with prototyping stages. Challenges in three-dimensional printing sensors and devices have to be addressed by forming integrated processes.

The research is underway to define an integrated process-based on three-dimensional Printing. The detailed technical details are not shared for scientific output. The literature is focused to define the challenges.

The research can provide ideas to business on innovative designs. Research studies have scope for improvement ideas.

Review is focused on to have an integrated three-dimensional printer combining processes. This is a cost-oriented approach saving much of space reducing complexity.

To date, no other publication reviews the varied three-dimensional printing challenges by classifying according to process, material, size and application aspects. Study on resolution based data is performed and analyzed for improvements. Addressing the challenges will be the solution to identify an integrated process methodology with a cost-effective approach for printing macro/micro/nano objects and devices.

The purpose of this study is to demonstrate the potential of three-dimensional printing technology for the remanufacturing of end-of-life (EoL) composites. This technology will enable the rapid fabrication of environmentally sustainable structures with complex shapes and good mechanical properties. These three-dimensional printed objects will have several application fields, such as street furniture and urban renewal, thus promoting a circular economy model.

For this purpose, a low-cost liquid deposition modeling technology was used to extrude photo-curable and thermally curable composite inks, composed of an acrylate-based resin loaded with different amounts of mechanically recycled glass fiber reinforced composites (GFRCs). Rheological properties of the extruded inks and their printability window and the conversion of cured composites after an ultraviolet light (UV) assisted extrusion were investigated. In addition, tensile properties of composites remanufactured by this UV-assisted technology were studied.

A printability window was found for the three-dimensional printable GFRCs inks. The formulation of the composite printable inks was optimized to obtain high quality printed objects with a high content of recycled GFRCs. Tensile tests also showed promising mechanical properties for printed GFRCs obtained with this approach.

The novelty of this paper consists in the remanufacturing of GFRCs by the three-dimensional printing technology to promote the implementation of a circular economy. This study shows the feasibility of this approach, using mechanically recycled EoL GFRCs, composed of a thermoset polymer matrix, which cannot be melted as in case of thermoplastic-based composites. Objects with complex shapes were three-dimensional printed and presented here as a proof-of-concept.

This work aims to investigate the interaction effects of printing process parameters of acrylonitrile butadiene styrene (ABS) parts fabricated by fused deposition modeling (FDM) technology on both the dimensional accuracy and the compressive yield stress. Another purpose is to determine the optimum process parameters to achieve the maximum compressive yield stress and dimensional accuracy at the same time.

The standard cylindrical specimens which produced from ABS by using an FDM 3D printer were measured dimensions and tested compressive yield stresses. The effects of six process parameters on the dimensional accuracy and compressive yield stress were investigated by separating the printing orientations into horizontal and vertical orientations before controlling five factors: nozzle temperature, bed temperature, number of shells, layer height and printing speed. After that, the optimum process parameters were determined to accomplish the maximum compressive yield stress and dimensional accuracy simultaneously.

The maximum compressive properties were achieved when layer height, printing speed and number of shells were maintained at the lowest possible values. The bed temperature should be maintained 109°C and 120°C above the glass transition temperature for horizontal and vertical orientations, respectively.

The optimum process parameters should result in better FDM parts with the higher dimensional accuracy and compressive yield stress, as well as minimal post-processing and finishing techniques.

The important process parameters were prioritized as follows: printing orientation, layer height, printing speed, nozzle temperature and bed temperature. However, the number of shells was insignificant to the compressive property and dimensional accuracy. Nozzle temperature, bed temperature and number of shells were three significant process parameters effects on the dimensional accuracy, while layer height, printing speed and nozzle temperature were three important process parameters influencing compressive yield stress. The specimen fabricated in horizontal orientation supported higher compressive yield stress with wide processing ranges of nozzle and bed temperatures comparing to the vertical orientation with limited ranges.

In this paper, the effects of the adhesive and curing agent contents on the tensile strength, bending strength, gas evolution and gas permeability of three-dimensional printed sand molds are studied. A strength model of the three-dimensional printed sand molds is proposed. The multi-material composite sand mold forming test is carried out. In addition, the mesostructure of the sand mold is studied.

The performances of three-dimensional printed sand mold such as tensile strength, bending strength, gas evolution and gas permeability are studied using the standard test methods. The mesostructure of the sand mold is studied by digital core technology.

A sand mold strength model based on the resin adhesive content, curing agent content and sand mold compactness are obtained. Two types of multi-material composite three-dimensional printed sand molds are proposed. An increase in the curing agent content in the sand mold widens the mesoscopic characteristic size distribution of the sand mold, and large-sized mesostructures appear, resulting in a decrease in the sand mold bearing capacity.

Process parameters that affect the performance of three-dimensional printed sand mold are revealed. The sand mold bearing curve provides a reference for the ultimate design of three-dimensional printed sand mold.

The paper deals with experimental work on the performance and mesostructure of multi-material composite three-dimensional printed sand mold with different contents of adhesive and curing agent. That gives a perspective on future designs of sand mold based on these principles.

This paper aims to investigate the effect of printing temperature on the thermal and the mechanical behaviour of polylactic acid (PLA)-polyhydroxyalkanoate (PHA) blend printed using fused deposition modelling (FDM).

Because of the use of an infra-red camera, thermal cycling during the laying down is quantified. In addition, X-ray micro-tomography is considered to reveal the microstructural arrangement within the three-dimensional printed material. Tensile loading conditions are used to derive Young’s modulus, tensile strength and fracture toughness, and relate these to the printing temperature. Finite element computation based on three-dimensional microstructure information is used to predict the role of defects on the tensile performance.

The results show a remarkable cohesive structure of PLA-PHA, particularly at 240°C. This cohesive structure is explained by the ability to ensure heat accumulation during laying down as evidenced by the nature of thermal cycling. The printing temperature is found to be a key factor for tuning the ductility of the printed PLA-PHA allowing full restoration of tensile strength at high printing temperature.

This study reports new results related to the thermo-mechanical behaviour of PLA-PHA that did not receive much attention in three-dimensional printing despite its potential as a candidate for pharmacological and medical applications. This study concludes by a wide range of possible printing temperatures for PLA-PHA and a remarkable low porosity generated by FDM.

Fabrication of customized products in low volume through conventional manufacturing incurs a high cost, longer processing time and huge material waste. Hence, the concept of additive manufacturing (AM) comes into existence and fused deposition modelling (FDM), is at the forefront of researches related to polymer-based additive manufacturing. The purpose of this paper is to summarize the research works carried on the applications of FDM.

In the present paper, an extensive review has been performed related to major application areas (such as a sensor, shielding, scaffolding, drug delivery devices, microfluidic devices, rapid tooling, four-dimensional printing, automotive and aerospace, prosthetics and orthosis, fashion and architecture) where FDM has been tested. Finally, a roadmap for future research work in the FDM application has been discussed. As an example for future research scope, a case study on the usage of FDM printed ABS-carbon black composite for solvent sensing is demonstrated.

The printability of composite filament through FDM enhanced its application range. Sensors developed using FDM incurs a low cost and produces a result comparable to those conventional techniques. EMI shielding manufactured by FDM is light and non-oxidative. Biodegradable and biocompatible scaffolds of complex shapes are possible to manufacture by FDM. Further, FDM enables the fabrication of on-demand and customized prosthetics and orthosis. Tooling time and cost involved in the manufacturing of low volume customized products are reduced by FDM based rapid tooling technique. Results of the solvent sensing case study indicate that three-dimensional printed conductive polymer composites can sense different solvents. The sensors with a lower thickness (0.6 mm) exhibit better sensitivity.

This paper outlines the capabilities of FDM and provides information to the user about the different applications possible with FDM.

Masked stereolithography (MSLA) or resin three-dimensional (3D) printing is one of the most extensively used high-resolution additive manufacturing technologies. Even though, the quality of 3D printing is determined by several factors, including the equipment, materials and slicer. Besides, the layer height, print orientation and exposure time are important processing parameters in determining the quality of the 3D printed green state specimen. The purpose of the paper is to optimize the printing parameters of the Masked Stereolithography apparatus for its dimensional correctness of 3D printed parts using the Taguchi method.

The acrylate-based photopolymer resin is used to produce the parts using liquid crystal display (LCD)-type resin 3D printer. This study is mainly focused on optimizing the processing parameters by using Taguchi analysis, L-9 orthogonal array in Minitab software. Analysis of variance (ANOVA) was performed to determine the most influencing factors, and a regression equation was built to predict the best potential outcomes for the given set of parameters and levels. The signal-to-noise ratios were calculated by using the smaller the better characteristic as the deviations from the nominal value should be minimum. The optimal levels for each factor were determined with the help of mean plots.

Based on the findings of ANOVA, it was observed that exposure time plays an important role in most of the output measures. The model’s goodness was tested using a confirmation test and the findings were found to be within the confidence limit. Also, a similar specimen was printed using the fused filament fabrication (FFF) technique; it was compared with the quality and features of MSLA 3D printing technology.

The study presents the statistical analysis of experimental results of MSLA and made a comparison with FFF in terms of dimensional accuracy and print quality.

Many previous studies reported the results based on earlier 3D printing technology such as stereolithography but LCD-based MSLA is not yet reported for its dimensional accuracy and part quality. The presented paper proposes the use of statistical models to optimize the printing parameters to get dimensional accuracy and the good quality of the 3D printed green part.

This paper aims to report on the findings of an investigation to compare three different three-dimensional printing (3DP) or additive manufacturing technologies [i.e. fused deposition modeling (FDM), stereolithography (SLA) and material jetting (MJ)] and four different equipment (FDM, SLA, MJP 2600 and Object 260) in terms of their dimensional process capability (dimensional accuracy and surface roughness). It provides a comprehensive and comparative understanding about the level of attainable dimensional accuracy, repeatability and surface roughness of commonly used 3DP technologies. It is expected that these findings will help other researchers and industrialists in choosing the right technology and equipment for a given 3DP application.

A benchmark model of 5 × 5 cm with several common and challenging features, such as around protrusion and hole, flat surface, micro-scale ribs and micro-scale long channels was designed and printed repeatedly using four different equipment of three different 3DP technologies. The dimensional accuracy of the printed models was measured using non-contact digital measurement methods. The surface roughness was evaluated using a digital profilometer. Finally, the surface quality and edge sharpness were evaluated under a reflected light ZEISS microscope with a 50× magnification objective.

The results show that FDM technology with the used equipment results in a rough surface and loose dimensional accuracy. The SLA printer produced a smoother surface, but resulted in the distortion of thin features (<1 mm). MJ printers, on the other hand, produced comparable surface roughness and dimensional accuracy. However, ProJet MJP 3600 produced sharper edges when compared to the Objet 260 that produced round edges.

This paper, for the first time, provides a comprehensive comparison of three different commonly used 3DP technologies in terms of their dimensional capability and surface roughness without farther post-processing. Thus, it offers a reliable guideline for design consideration and printer selection based on the target application.

Additive manufacturing (AM) technologies are gaining immense popularity in the manufacturing sector because of their undisputed ability to construct geometrically complex prototypes and functional parts. However, the reliability of AM processes in providing high-quality products remains an open and challenging task, as it necessitates a deep understanding of the impact of process-related parameters on certain characteristics of the manufactured part. The purpose of this study is to develop a novel method for process parameter selection in order to improve the dimensional accuracy of manufactured specimens via the fused deposition modeling (FDM) process and ensure the efficiency of the procedure.

The introduced methodology uses regression-based machine learning algorithms to predict the dimensional deviations between the nominal computer aided design (CAD) model and the produced physical part. To achieve this, a database with measurements of three-dimensional (3D) printed parts possessing primitive geometry was created for the formulation of the predictive models. Additionally, adjustments on the dimensions of the 3D model are also considered to compensate for the overall shape deviations and further improve the accuracy of the process.

The validity of the suggested strategy is evaluated in a real-life manufacturing scenario with a complex benchmark model and a freeform shape manufactured in different scaling factors, where various sets of printing conditions have been applied. The experimental results exhibited that the developed regressive models can be effectively used for printing conditions recommendation and compensation of the errors as well.

The present research paper is the first to apply machine learning-based regression models and compensation strategies to assess the quality of the FDM process.

The extrusion-based additive manufacturing method followed by debinding and sintering steps can produce metal parts efficiently at a relatively low cost and material wastage. In this study, 316L stainless-steel metal filled filaments were used to print metal parts using the extrusion-based fused filament fabrication (FFF) approach. The purpose of this study is to assess the effects of common FFF printing parameters on the geometric and mechanical performance of FFF manufactured 316L stainless-steel components.

The microstructural characteristics of the metal filled filament, three-dimensional (3D) printed green parts and final sintered parts were analysed. In addition, the dimensional accuracy of the green parts was evaluated, as well as the hardness, tensile properties, relative density, part shrinkage and the porosity of the sintered samples. Moreover, surface quality in terms of surface roughness after sintering was assessed. Predictive models based on artificial neural networks (ANNs) were used for characterizing dimensional accuracy, shrinkage, surface roughness and density. Additionally, the response surface method based on ANNs was applied to represent the behaviour of these parameters and to identify the optimum 3D printing conditions.

The effects of the FFF process parameters such as build orientation and nozzle diameter were significant. The pore distribution was strongly linked to the build orientation and printing strategy. Furthermore, porosity decreased with increased nozzle diameter, which increased mechanical performance. In contrast, lower nozzle diameters achieved lower roughness values and average deviations. Thus, it should be noted that the modification of process parameters to achieve greater geometrical accuracy weakened mechanical performance.

Near-dense 316L austenitic stainless-steel components using FFF technology were successfully manufactured. This study provides print guidelines and further information regarding the impact of FFF process parameters on the mechanical, microstructural and geometric performance of 3D printed 316L components.