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“V-bending” is the most commonly used bending process in which the sheet metal is pressed into a “V-shaped” die using a “V-shaped” punch to form a required angular bend. When the punch is removed after the operation, because of elastic recovery, the bent angle varies. This shape discrepancy is known as spring back which causes problems in the assembly of the component in the modern aerospace industry. Regarding the optimization of spring-back accuracy, this research will illustrate the laws of the transition area (TA) of the nondeformation area (NDA) during the 90° “V-shape” bending process.

According to the traditional “V-bending” process to optimize the spring-back accuracy, the bent sheets are divided into deformation area (DA) and NDA. For this reason, the traditional “V-bending” process may prolong error to optimize the spring-back accuracy because NDA has a certain amount of deformation, which the researcher always avoids. Firstly, bent sheets are divided into three parts in this research: DA, TA and NDA to avoid the distortion error in TA that are not considered in the NDA in traditional theory. Then, the stress and strain in the DA and TA were discussed during theoretical derivation and some hypotheses were proposed. In this research, the interval, position and distortion degree of the TA of the bending sheet are used by finite element analysis. Finally, V-shape bending tests for aluminum alloy at room temperature are used and labeled all the work pieces' TAs to realize the deformation amount in the TA.

The bending radius does not affect the range of the TA, it only changes the position of TA in the bending sheet. It is evident that the laws of TA were explored in the width direction and gradually changed from the inner layer to the outer layer based on the ratio of width and thickness of the bending plate/sheet.

In the modern aerospace industry, aircraft manufacturing technology must maintain high accuracy. This research has practical value in the 90° “V-shape” bending of metal sheets and the development of its spring-back accuracy.

This paper aims to investigate the dimensional accuracy consisting of thickness, grip section width, full length, circularity, cylindricity and surface finish of printed polyurethane dog-bone samples based on American Society for Testing and Materials D638 type V standard, which were optimally printed by fused deposition modelling (FDM).

The experimental approach focuses on determining main effects of printing parameters, including nozzle temperature, infill percentage, print speed and layer height on dimensional error and surface finish of the printed samples, followed by the confirmation tests to warrant the reproducibility of experimental results.

This study shows that layer height has the most significant impact on dimensional accuracy and surface finish of printed samples compared to other printing parameters, whereas infill density has no significant effect on all sample dimensions.

This paper presents a comprehensive study relating to various dimensional accuracies in terms of full length, grip section width, thickness, circularity, cylindricity and surface finish of dog-bone samples printed by FDM to improve the printability and processibility via additive manufacturing.

This paper aims to present a geometrical void model in conjunction with a multiscale method to evaluate the effect of interraster distance, bead (raster) width and layer height, on the voids concentration (volume) and subsequently calculate the final mechanical properties of the fused deposition modeling parts at constant infill.

A geometric model of the voids inside the representative volume element (RVE) is combined with a two-scale asymptotic homogenization method. The RVEs are subjected to periodic boundary conditions solved by finite element (FE) to calculate the effective mechanical properties of the corresponding RVEs. The results are validated with literature and experiments.

Bead width from 0.2 to 0.3 mm, reported a decrease of 25% and 24% void volume for a constant layer height (0.1 and 0.2 mm – 75% infill). It is reported that the void’s volume increased up to 14%, 32% and 36% for 75%, 50% and 25% infill by varying layer height (0.1–0.2  and 0.3 mm), respectively. For elastic modulus, 14%, 9% and 10% increase is reported when the void’s volume is decreased from 0.3 to 0.1 mm at a constant 75% infill density. The bead width and layer height have an inverse effect on voids volume.

This work brings values: a multiscale-geometric model capable of predicting the voids controllability by varying interraster distance, layer height and bead width. The idealized RVE generation slicer software and Solidworks save time and cost (<10 min, $0). The proposed model can effectively compute the mechanical properties together with the voids analysis.

The advancement of additive manufacturing technologies has resulted in producing parts of high quality and reduced manufacturing time. This paper aims to achieve a simultaneous optimal solution for build time and surface roughness as the output data and also to find the best values for the input data consisting of build orientation, extrusion width, layer thickness, infill percentage and raster angle.

For this purpose, the effects of process parameters on the response variables were investigated by the design of experiments approach to develop empirical models using response surface methodology. The experimental parts of this research were conducted using an inexpensive and locally assembled fused filament fabrication (FFF) machine. A total of 50 runs for 4 different geometries, namely, cylinder, prism, 3DBenchy and twist gear vase, were performed using the rotatable central composite design, and each process parameters were investigated in two levels to develop empirical models. Also, a novel optimization method, namely, the posterior-based method, was accomplished to find the best values for the response variables.

The results demonstrated that not only the build orientation and layer thickness have notable effects on both response variables but also build time is dependent on extrusion width and infill percentage. Low infill percentage and high extrusion width resulted in increasing build time. By reducing layer thickness and infill percentage while increasing extrusion width, parts of high-quality surface finish and reduced built time were produced. Optimum process parameters were found to be of build direction of 0°, extrusion width of 0.61 mm, layer thickness of 0.22 mm, infill percentage of 20% and raster angle of 0°.

Through the developed empirical models and by minimizing build orientation and layer thickness, and also considerations for process parameters, parts of high-quality surface finish and reduced built time could be produced on FFF machines. To compensate for increased build time because of reduction in layer thickness, extrusion width and infill percentage must have their maximum and minimum value, respectively.

The major problem that limits the widespread use of WAAM technology is the forming quality. However, most of the current research focuses on post-process detections that are time-consuming, expensive and destructive. This paper aims to achieve the on-line detection and classification of the common defects, including hump, deposition collapse, deviation, internal pore and surface slag inclusion.

This paper proposes an in-process multi-feature data fusion nondestructive testing method based on the temperature field of the WAAM process. A thermal imager is used to collect the temperature data of the deposition layer in real-time. Efficient processing methods are proposed in this paper, such as the temperature stack algorithm, width extraction algorithm and a classification model based on a residual neural network. Some features closely related to the forming quality were extracted, containing the profile image and width curve of the deposition layer and abnormal temperature features in longitudinal and cross-sections. These features are used to achieve the detection and classification of defects.

Thermal non-destructive testing is a potentially superior technology for in-process detection in the industrial field. Based on the temperature field, extracting the most relevant features of the defect information is crucial. This paper pushes current infrared (IR) monitoring methods toward real-time detection and proposes an in-process multi-feature data fusion non-destructive testing method based on the temperature field of the WAAM process.

In this paper, the single-layer and multi-layer WAAM samples are preset with various defects, such as hump, deposition collapse, deviation, pore and slag inclusion. A multi-feature nondestructive testing methodology is proposed to realize the in-process detection and classification of the defects. A temperature stack algorithm is proposed, which improves the detection accuracy of profile change and solves the problem of uneven temperature from arc striking to arc extinguishing. The combination of residual neural network greatly improves the accuracy and efficiency of detection.

The purpose of this paper is to investigate the factors governing bond strength in fused deposition modeling (FDM) compared to strength in the fiber direction.

Acrylonitrile butadiene styrene (ABS) boxes with the thickness of a single fiber were made at different platform and nozzle temperatures, print speeds, fiber widths and layer heights to produce multiple specimens for measuring the strength.

Specimens produced with the fibers oriented in the tensile direction had 95 per cent of the strength of the constitutive filament. Bond strengths ranged from 40 to 85 per cent of the filament strength dependent on the FDM processing conditions. Diffusion, wetting and intimate contact all separately affect bond strength.

This study provides processing recommendations for producing the strongest FDM parts. The needs for higher nozzle temperatures and more robust feed motors are described; these recommendations can be useful for companies producing FDM products as well as companies designing FDM printers.

This is the first study that discusses wetting and intimate contact separately in FDM, and the results suggest that a fundamental, non-empirical model for predicting FDM bond strength can be developed based on healing models. Additionally, the role of equilibration time at the start of extrusion as well as a motor torque limitation while trying to print at high speeds are described.

As known, the wire and arc additive manufacture technique can achieve stable process control, which is represented with periodic surface waviness, when using empirical methods or feedback control system. But it is usually a tedious work to further reduce it using trial and error method. The purpose of this paper is to unveil the formation mechanism of surface waviness and develop a method to diminish it.

Two forming mechanisms, wetting and spreading and remelting, are unveiled by cross-section observation. A discriminant is established to differentiate which mechanism is valid to dominate the forming process under the given process parameters.

Finally, a theoretical method is developed to optimize surface waviness, even forming a smooth surface by establishing a matching relation between heat input (line energy) and materials input (the ratio of wire feed speed to travel speed).

Formation mechanisms are revealed by observing cross-section morphology. A discriminant is established to differentiate which mechanism is valid to dominate the forming process under the given process parameters. A mathematical model is developed to optimize surface waviness, even forming a smooth surface through establishing a matching relation between heat input (line energy) and materials input (the ratio of wire feed speed to travel speed).

The purpose of this study is to propose the use of a pre-deposition heating system for fused filament fabrication (FFF) as a means to enhance interlayer bonding by elevating the substrate temperature. The effects of the heating on thermal profile at the bonding interface and the mechanical properties of three-dimensional printed parts are investigated.

A 12-W laser head is integrated to a commercial printer as the pre-deposition heating system. The laser beam heats up substate before the deposition of a fresh filament. Effects of laser powers are investigated and the thermal profile is measured with thermocouple, infrared camera and finite element model. The correlation between the temperature at the bonding interface and the bonding quality is investigated by conducting tensile testing and neck width measurement with microscope.

The pre-deposition heating system is proven to be effective in enhancing the inter-layer strength in FFF parts. Tensile testing of specimens along build direction (Z) shows an increase of around 50% in ultimate strength. A linear relationship is observed between the pre-deposition temperature at bond interface and bonding strength. It is evident that elevating the pre-deposition temperature promotes interlayer polymer diffusion as shown by the increased neck width between layers.

Thermocouples that are sandwiched between layers are used to achieve accurate measurement of the interfacial temperature. The temperature profiles under pre-deposition heating are analyzed and correlated to the interlayer bonding strengths.

Current commercial rapid prototyping systems can be used for fabricating layered models for subsequent creation of fully‐dense metal parts using investment casting. Due to increased demand for shortened product development cycles however, there exists a demand to rapidly fabricate functional fully‐dense metal parts without hard tooling. A possible solution to this problem is direct layered rapid manufacturing of such parts, for example, via laser‐beam fusion of the metal powder. The rapid manufacturing process discussed herein is based on this approach. It involves selective laser‐beam scanning of a predeposited metal‐powder layer, forming fully‐dense claddings as the basic building block of individual layers. This paper specifically addresses only one of the fundamental issues of the rapid manufacturing process under investigation at the University of Toronto, namely the fabrication of single claddings. Our theoretical investigation of the influence of the process parameters on cladding’s geometrical properties employed thermal modeling and computer process simulation. Numerous experiments, involving fabrication of single claddings, were also carried out with varying process parameters. Comparisons of the process simulations and experimental results showed good agreement in terms of overall trends.

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.