Analysis and Optimization of Dimensional Accuracy and Porosity of High Impact Polystyrene Material Printed by FDM Process: PSO, JAYA, Rao, and Bald Eagle Search Algorithms

High impact polystyrene (HIPS) material is widely used for low-strength structural applications. To ensure proper function, dimensional accuracy and porosity are at the forefront of industrial relevance. The dimensional accuracy cylindricity error (CE) and porosity of printed parts are influenced mainly by the control variables (layer thickness, shell thickness, infill density, print speed of the fused deposition modeling (FDM) process). In this study, a central composite design (CCD) matrix was used to perform experiments and analyze the complete insight information of the process (control variables influence on CE and porosity of FDM parts). Shell thickness for CE and infill density for porosity were identified as the most significant factors. Layer thickness interaction with shell thickness, infill density (except for CE), and print speed were found to be significant for both outputs. The interaction factors, i.e., shell thickness and infill density, were insignificant (negligible effect) for both outputs. The models developed produced a better fit for regression with an R2 equal to 94.56% for CE, and 99.10% for porosity, respectively. Four algorithms (bald eagle search optimization (BES), particle swarm optimization (PSO), RAO-3, and JAYA) were applied to determine optimal FDM conditions while examining six case studies (sets of weights assigned for porosity and CE) focused on minimizing both CE and porosity. BES and RAO-3 algorithms determined optimal conditions (layer thickness: 0.22 mm; shell thickness: 2 mm; infill density: 100%; print speed: 30 mm/s) at a reduced computation time equal to 0.007 s, differing from JAYA and PSO, which resulted in an experimental CE of 0.1215 mm and 2.5% of porosity in printed parts. Consequently, BES and RAO-3 algorithms are efficient tools for the optimization of FDM parts.

Hole geometry and surface integrity assessment in drilling of inconel 718 using laser texture filled solid lubricant tools

Purpose Inconel 718 is used in gas turbine engines for aerospace applications due to high creep resistance but generating a hole with good surface integrity is challenging because the γ′′ interface is very strong so that slip is difficult in the grain boundary. So, the purpose of this work is to enhance the performance of drilling using a micro texture drill tool filled with solid lubricant. Design/methodology/approach Three different micro textures such as star shaped with 6-sharp apex, rectangular slots parallel and perpendicular to drill axis are created using laser on the drill tool. Deep cryogenic treatment is done on the textured tool to improve the strength and wear resistance before it is filled with solid lubricant. A detailed experimental investigation is performed to analyse the hole geometry and surface integrity of the drilled hole. Findings The accuracy of the drilled holes is enhanced in the star shaped texture drill tool over other textured and non-textured tools. A significant improvement in surface finish and hardness are observed and moreover cylindricity error, burr height of the hole is less for the above condition. It is also inferred that, at lower feed rate and higher speed produce hole with an accuracy of 96%. Originality/value Aerospace industry is focussing on improving the hole geometry and surface in Inconel 718. This work demonstrates the novel technique to improve drilling of Inconel 718 using laser textured tool filled by the solid lubricant.

Evaluation of the Surface Defects and Dimensional Tolerances in Multi-Hole Drilling of AA5083, AA6061, and AA2024

Drilling is one of the most performed machining operations for riveting and assembly operations in many industrial sectors. The accuracy of the drilled holes and their surface finish play a vital role in the longevity and performance of the machined components, which, in turn, increase productivity. Therefore, this study investigated the effect of the multi-spindle drilling process on dimensional hole tolerances, such as hole size, circularity, cylindricity, and perpendicularity. In addition, the surface defects formed in the holes were examined using scanning electron microscopy. Three aluminium alloys, AA2024, AA6061, and AA5083, which are commonly used in the aerospace, automotive, and marine sectors, were chosen as the study materials. The results showed that the holes drilled in AA2024 gave less circularity error, cylindricity error, and perpendicularity error. In the case of hole size, the holes drilled in AA6061 were less deviated from the nominal size following holes drilled in AA2024 and AA5083 alloys. Surface damage in the form of metal debris adhesion, smeared material, side flow, and feed marks was found on the inner hole surface. Holes drilled in AA5083 alloy had the worst surface finish and were the most oversized, which was associated with noticeable damage and deformations in their inner surface. The ANOVA results revealed that the spindle speed was more influential than feed and mainly affected the hole size and cylindricity errors. However, in the case of circularity error and perpendicularity error, drilling parameters were found to be insignificant.

Experimental estimation and numerical optimization of ‘cylindricity’ error in flow forming of H30 aluminium alloy tubes

The present article analyses the influence of flow forming input parameters on the development of “cylindricity error” in H30 aluminum alloy seamless tubes fabricated by a single pass reverse flow forming process. Measurement and control of geometrical precision in terms of cylindricity encompassing straightness and roundness are critical for the success of component manufacturing by flow forming. The experimental trials with a predefined range of input parameters conforming to the full factorial design of experiments approach have been performed, and corresponding cylindricity data have been recorded as the outcome. An empirical relation has been established between the input parameters and the cylindricity. It has been established that cylindricity value increases sharply with an increase in axial stagger contributing 39% to the outcome, whereas the percentage contributions of in-feed and feed-speed ratio are found to be less than 1%. The adequacy of the proposed model has further been analyzed and validated through the confirmation tests. In order to obtain better control over the overall process towards achieving higher productivity and accuracy, 2 meta-heuristic optimization algorithms namely, teaching and learning-based algorithm and genetic algorithm have been utilized for optimization of input process parameters to minimize cylindricity error. Both the algorithms predict that a combination of higher feed rate and lower value of axial stagger and in-feed parameters is essential to achieve the lowest cylindricity error in H30 Al alloy. Confirmatory experimental trials have been carried out to validate both the regression model and optimization, and have been found to agree well with the model predictions described herein.

Detection and Visualization of Manufacturing Errors of Internal Cavity Structural Parts

Aiming at the difficulty of manufacturing error detection of internal cavity structural parts, a detection method of common manufacturing error based on industrial CT images was proposed. Firstly, the image sequence of part scanned by an industrial CT machine is converted into a three-dimensional measurement model; Then, the registration of the three-dimensional measurement model with the original design model is completed; The surface information of the part is obtained by segmenting surfaces of the three-dimensional measurement model; Next, the datum surface is selected, the error value of the test surface is calculated after selecting datum surface; Finally, the detection result is obtained by comparing the error value with the tolerance value, analyzing the result and the areas that do not meet the tolerance requirements is visualized in the developed software system. The common manufacturing errors of complex inner cavity parts can be detected by the method, such as dimension error of length, planeness error, cylindricity error, parallelism and perpendicularity error of face-to-face, at the same time, it can intuitively show the area whose manufacturing errors in the cavity structure of the parts are not satisfied, which provides a basis for judging the quality of manufacturing and processing of parts.