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The purpose of this paper is to investigate the influence of low-cost chemical vapour treatment process on geometric accuracy and surface roughness of different curved and freeform surfaces of fused deposition modelling (FDM) specimens build at different part building orientations.

Parts with different primitive and curved surfaces are designed and modelled to build at three different part orientations along X orientation (vertical position resting on side face), Y orientation (horizontal position resting on base) and Z orientation (upright position). Later, the parts are post-processed by cold vapours of acetone. Geometric accuracy and surface roughness are measured both before and after the chemical treatment to investigate the change in geometric accuracy, surface roughness of FDM parts.

The results indicate that surface roughness is reduced immensely after cold vapour treatment with minimum variation in geometric accuracy of parts. Parts build vertically over its side face (X orientation) provides the overall better surface finish and geometric accuracy.

The present study provides an approach of post-built treatment for FDM parts and observes a significant improvement in surface finish of the components. The present approach of post-built treatment can be adopted to enhance the surface quality as well as to achieve desired geometric accuracy for different primitive, freeform/curved surfaces of FDM samples suitable for functional components as well as prototypes.

Additive manufacturing (AM) studies on Inconel 718 (IN718) have focused on exploring its tensile and fatigue response. As IN718 is used in the propulsion and energy sector, the impact of shearing is also critical to ensuring the durability of these components. As such, this study aims to explore the relation between build orientation on the shear cyclic response of direct metal laser sintered (DMLS) IN718.

IN718 torsion specimens were manufactured along six build orientations: (100)-X, (010)-Y, (001)-Z, (110)-XY45, (101)-XZ45 and (011)-YZ45, using the DMLS process. Torsional fatigue testing was performed on as-built specimens, from which fracture behavior, surface roughness, softening/hardening response and monotonic/cyclic shear torsional properties were assessed.

DMLS IN718 was found to exhibit transversely isotropic behavior. In terms of shear stress range and shear modulus, Z > (X, XY45, Y) > (XZ45, YZ45). Specimens cyclically hardened to stabilization and softened to fracture. In terms of torsional fatigue fracture response, the Z, XZ45 and YZ45 specimens exhibited crack initiation and propagation from internal defects, whereas cracks were found to initiate at the surface and propagate between and through build layers for the X, Y and XY45 specimens.

This study reports the torsional cyclic response and shear moduli exhibited by as-built DMLS IN718 manufactured along varying build orientations. The findings are applicable for researchers because of the wide use of IN718 in the gas turbine industry, and the current trend to replace conventional manufacturing with AM.

Orientation determination is an essential planning task in additive manufacturing (AM) because it directly affects the part quality, build time, geometric tolerance, fabrication cost, etc. This paper aims to propose a negative feedback decision-making (NFDM) model to realize the personalized design of part orientation in AM process.

NFDM model is constructed by integrating two sub-models: proportional–integral–derivative (PID) negative feedback control model and technique for order preference by similarity to an ideal solution (TOPSIS) decision-making model. With NFDM model, a desired target is first specified by the user. Then, the TOPSIS decision model calculates the “score” for the current part orientation. TOPSIS decision model is modified for ease of control. Finally, the PID controller automatically rotates the part based on the error between the user-specified target and the calculated “score”. Part orientation adjustment is completed when the error is eliminated. Five factors are considered in NFDM model, namely, surface roughness, support structure volume, geometric tolerance, build time and fabrication cost.

The case studies of turbine fan and dragon head indicate that the TOPSIS model can be perfectly integrated with the PID controller. This work extends the proposed model to different AM processes and investigates the feasibility of combining different decision-making models with PID controller and the effects of including various evaluation criteria in the integrated model.

The proposed model innovatively takes the TOPSIS decision-making model and the PID control model as a whole. In this way, the uncontrollable TOPSIS model becomes controllable, so the proposed model can control the TOPSIS model to achieve the user-specified targets.

The purpose of this paper is to use a combination of numerical simulation and experiment to evaluate the performance of laser surface texturing (LST) in the field of gear lubrication, and to more accurately predict the lubrication characteristics of different surfaces.

The method used in this paper is developed on the basis of the deterministic solution of the three-dimensional (3D) mixed elasto-hydrodynamic lubrication (EHL) model and the model parameters are corrected by friction test. The film pressure, film thickness and friction coefficient of different micro-textured tooth surfaces are predicted on the basis of accurate 3D mixed EHL models.

The results demonstrate that the micro-texture structure of the tooth surface can increase the local film thickness and enhance the lubricating performance of the tooth surface without drastically reducing the contact fatigue life. The stress distribution and friction characteristics of the tooth surface can be optimized by adjusting the micro-texture arrangement and the size of the micro-textures.

A new evaluation method using a 3D hybrid EHL model and friction test to predict the lubrication characteristics of LST is proposed, which can effectively improve the processing economy and save time.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2020-0423

Binder jetting (BJ) process is an additive manufacturing (AM) process in which powder materials are selectively joined by binder materials. Products can be manufactured layer-by-layer directly from three-dimensional model data. The quality properties of the products fabricated by the BJ AM process are significantly affected by the process parameters. To improve the product quality, the optimal process parameters need to be identified and controlled. This research works with the 420 stainless steel powder material.

This study focuses on four key printing parameters and two end-product quality properties. Sixteen groups of orthogonal experiment designed by the Taguchi method are conducted, and then the results are converted to signal-to-noise ratios and analyzed by analysis of variance.

Five sets of optimal parameters are concluded and verified by four group confirmation tests. Finally, by taking the optimal parameters, the end-product quality properties are significantly improved.

These optimal parameters can be used as a guideline for selecting proper printing parameters in BJ to achieve the desired properties and help to improve the entire BJ process ability.

The purpose of this paper is to investigate the effects of surface texture with roughness orientation considered on tribological properties under a mixed lubrication state numerically and experimentally.

Based on the average Reynolds equation and asperity contact model, the impacts of surface texture parameters and roughness orientation on lubrication properties have been calculated using finite difference method. Tin–bronze samples with various prescribed surface texture geometric parameters and roughness orientation were fabricated by laser surface texturing technique, and the tribology performance of the textured surface was studied experimentally.

The effects of surface geometric parameters and roughness orientation parameters have been discerned. The experimental observations are in good agreement with the numerical prediction, which suggests that the numerical scheme adopted in this work is suitable in capturing the surface texture and roughness effect under mixed lubrication state.

By meticulously controlling the surface roughness and surface texture geometric characteristics based on the laser surface texturing process, samples with prescribed surface texture parameters and roughness orientation consistent with that in theoretical studies were fabricated and the theoretical model and results were verified experimentally.

This paper aims to focus on an experimental study of surface roughness, dimensional accuracy and time of fabrication of parts produced by fused deposition modelling (FDM) technique of additive manufacturing. The fabricated parts of acrylonitrile butadiene styrene (ABS) material have pyramidal and conical features. Influence of five process parameters of FDM, namely, layer thickness, wall print speed, build orientation, wall thickness and extrusion temperature is studied on response characteristics. Furthermore, regression models for responses are developed and significant process parameters are optimized.

Comprehensive experimental study is performed using response surface methodology. Analysis of variance is used to investigate the influence of process parameters on surface roughness, dimensional accuracy and time of fabrication in both outer pyramidal and inner conical regions of part. Furthermore, a multi-response optimization using desirability function is performed to minimize surface roughness, improve dimensional accuracy and minimize time of fabrication of parts.

It is found that layer thickness and build orientation are significant process parameters for surface roughness of parts. Surface roughness increases with increase in layer thickness, while it decreases initially and then increases with increase in build orientation. Layer thickness, wall print speed and build orientation are significant process parameters for dimensional accuracy of FDM parts. For the time of fabrication, layer thickness and build orientation are found as significant process parameters. Based on the analysis, statistical non-linear quadratic models are developed to predict surface roughness, dimensional accuracy and time of fabrication. Optimization of process parameters is also performed using desirability function.

The present study is restricted to the parts of ABS material with pyramidal and conical features only fabricated on FDM machine with delta configuration.

From the critical review of literature it is found that some researchers have made to study the influence of few process parameters on surface roughness, dimensional accuracy and time of fabrication of simple geometrical parts. Also, regression models and optimization of process parameters has been performed for simple parts. The present work is focussed on studying all these aspects in complicated geometrical parts with pyramidal and conical features.

This paper aims to investigate the dimensional accuracy and surface roughness of printed masked stereolithography (m-SLA) parts. The fabricated specimens of photosensitive polymer resin have complex shapes and various features. The influence of four process parameters of m-SLA, including layer height, exposure time, light-off delay and print orientation, is studied on response characteristics.

The Box–Behnken design of response surface methodology is used to examine the effect of process parameters on the shrinkage of various geometrical dimensions like diameter, length, width, and height of different features in a complex shape. Additionally, a multi-response optimization has been carried out using the desirability function to minimize the surface roughness and printing time and maximize the dimensional accuracy.

The layer height and print orientation influence the surface roughness of parts. An increase in layer height results in increased surface roughness, and the orientation parallel to the z-axis of the machine gives the highest surface roughness. The dimensional accuracy of m-SLA parts is influenced by layer height, exposure time, and print orientation. Although not significant in dimensional accuracy and surface roughness, the light-off delay can affect printing time apart from other parameters like layer height and print orientation.

The effect of layer height and print orientation on dimensional accuracy, printing time, and surface roughness is investigated by researchers using simple shapes in other vat photopolymerization techniques. The present work is focused on studying the effect of these parameters and additional parameters like light-off delay in complicated geometrical parts in m-SLA.

This paper aims to study the comparison between a response surface methodology (RSM) and artificial neural network (ANN) in the modelling and prediction of surface roughness during endmilling of glass-fibre-reinforced polymer composites.

Aiming to achieve this goal, several milling experiments were performed with polycrystalline diamond inserts at different machining parameters, namely, feed rate, cutting speed, depth of cut and fibre orientation angle. Mathematical model is created using central composite face-centred second-order in RSM and the adequacy of the model was verified using analysis of variance. ANN model is created using the back propagation algorithm.

With regard to the machining test, it was observed that feed rate is the dominant parameter that affects the surface roughness, followed by the fibre orientation. The comparison results show that models provide accurate prediction of surface roughness in which ANN performs better than RSM.

The data predicted from ANN are very nearer to experimental results compared to RSM; therefore, this ANN model can be used to determine the surface roughness for various fibre-reinforced polymer composites and also for various machining parameters.

The purpose of this paper is to develop a mathematical model for surface roughness and delamination through response surface methodology (RSM) and analyse the influences of the entire individual input machining parameters (cutting speed, fibre orientation angle, depth of cut and feed rate) on the responses in milling of glass fibre reinforced plastics (GFRP) composites with solid carbide end mill cutter coated with PCD.

Four factors, five level central composites and a rotatable design matrix in response surface methodology were employed to carry out the experimental investigation. “Design Expert 8.0” software was used for regression and graphical analysis of the data were collected. The optimum values of the selected variables were obtained by solving the regression equation and by analyzing the response surface contour plots. Analysis of variance (ANOVA) was applied to check the validity of the model and for finding the significant parameters.

The developed second order response surface model was used to calculate the surface roughness and delamination of the machined surfaces at different cutting conditions with the chosen range with 95 per cent confidence intervals. Using such a model, remarkable savings in time and cost can be obtained.

The effect of fibre orientation during milling of GFRP laminates using RSM has not been previously attempted for analysis.