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This paper aims to propose a new framework on prioritizing and deployment of design for additive manufacturing (DfAM) strategies to an industrial component using Fuzzy TOPSIS multiple criteria decision-making (MCDM) techniques. The proposed framework is then applied to an automotive component, and the results are discussed and compared with existing design.

Eight DfAM design alternatives associated with eight design criteria have been identified for framing new DfAM strategies. The prioritization order of the design alternatives is identified by Fuzzy TOPSIS MCDM technique through its closeness coefficient. Based on Fuzzy TOPSIS MCDM output, each of the design alternatives is applied sequentially to an automobile component as a case study. Redesign is carried out at each stage of DfAM implementation without affecting the functionality.

On successful implementation of proposed framework to an automotive component, the mass is reduced by 43.84%, from 0.429 kg to 0.241 kg. The redesign is validated by finite element analysis, where von Mises stress is less than the yield stress of the material.

The proposed DfAM framework and strategies will be useful to designers, R&D engineers, industrial practitioners, experts and consultants for implementing DfAM strategies on any industrial component without impacting its functionality.

To the best of the authors’ knowledge, the idea of prioritization and implementation of DfAM strategies to an automotive component is the original contribution.

This paper aims to optimize the process parameters of the fused deposition modelling (FDM) process using the Grey-based Taguchi method and the results to be verified based on a technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) calculation.

The optimization of process parameters is gaining a potential role to develop robust products. In this context, this paper presents the parametric optimization of the FDM process using Grey-based Taguchi, TOPSIS and AHP method. The effect of slice height (SH), part fill style (PFS) and build orientation (BO) are investigated with the response parameters machining time, surface roughness and hardness (HD). Multiple objective optimizations were performed with weights of w1 = 60%, w2 = 20% and w3 = 20%. The significance of the process parameters over response parameters is identified through analysis of variance (ANOVA). Comparisons are made in terms of rank order with respect to grey relation grade (GRG), relative closeness and AHP index values. Response table, percentage contributions of process parameters for both GRG and TOPSIS evaluation are done.

The optimum factor levels are identified using GRG via the Grey Taguchi method and TOPSIS via relative closeness values. The optimized factor levels are SH (0.013 in), PFS (solid) and BO (45°) using GRG and SH (0.013 in), PFS (sparse-low density) and BO (45°) using TOPSIS relative closeness value. SH has higher significance in both Grey relational analysis and TOPSIS which were analysed using ANOVA.

In this research, the multiple objective optimizations were done on an automotive component using GRG, TOPSIS and AHP which showed a 27% similarity in their ranking order among the experiments. In the future, other advanced optimization techniques will be applied to further improve the similarity in ranking order.

The study presents the case of an automotive component, which illustrates practical relevance.

In several research studies, optimization was done on the standard test specimens but not on a real-time component. Here, the multiple objective optimizations were applied to a case automotive component using Grey-based Taguchi and verified with TOPSIS. Hence, an effort has been taken to find optimum process parameters on FDM, for achieving smooth, hardened automotive components with enhanced printing time. The component can be explored as a replacement for the existing product.

This study aims to investigate the effects of five different printing parameters, namely, printing speed (PS), printing temperature/nozzle temperature/extrusion temperature, heated-bed temperature, raster angle (RA) and layer height (LT), on mechanical properties.

American Society for Testing and Materials (ASTM) standards were used for the specimen design. Then, the Taguchi method was used for the design of the experiment and an L16 orthogonal array was preferred. Tensile, Shore D and surface roughness tests were conducted on polylactic acid test specimens. The test results were analyzed using the signal-to-noise ratio and analysis of variance (ANOVA).

As a result of the study, it was seen that RA is the most important parameter for the tensile strength, PS is for the hardness and LT is for the surface roughness. According to the ANOVA results, the effects of the RA, PS and LT on the maximum tensile strength, hardness and surface roughness were 41.59%, 69.51% and 44.6%, respectively.

To the best of the authors’ knowledge, this study is one of the most comprehensive parameter optimization studies for additive manufacturing in the literature because it includes five different printing parameters and three mechanical test procedures.

The essential properties of active sports fabrics are moisture management, quick-drying, body heat management and thermal regulations. Fibre type, blending nature, yarn and fabric structure and the finishing treatment are the key parameters that influenced the performance of the clothing meant for sportswear. This study aims to investigate the effect of fibre blending and structural tightness factors on bi-layer sport fabric's dimensional, moisture management and thermal properties.

In this study, 12 different bi-layer inter-lock fabrics were produced. Polyester filament (120 Denier) yarn was fed to form the backside of the fabric, and the face side was varied with cotton, modal, wool and soya spun yarns of 30sNe. Three different types of structural tightness factors were considered, such as low, medium and high were taken for sample development. The assessment towards dimensional, moisture management and thermal properties was carried out on all the samples.

The polyester-modal blend with a high tightness factor has shown maximum overall moisture management capability (OMMC) values of 0.73 and air permeability of 205.3 cm³/cm²/s. The same sample has shown comparatively higher thermal conductivity of 61.72 × 10^–3 W m^-1 °C^-1(Under compression state) and 58.45 × 10^–3 W m^-1 °C^-1 (under recovery state). In the case of surface roughness is concerned, polyester-modal blends have shown the lowest surface roughness, surface roughness amplitude and surface friction co-efficient. Among the selected fibre combinations, the overall comfort level of polyester-modal bi-layer knitted structure with a higher tightness factor is appreciable. Polyester-modal is more suitable for active sportswear among the four fiber blend combinations.

The outcome of this study will help to gain a better understanding of fibre blends, structural tightness factor and other process specifications for the development of bi-layer fabric for active sportswear applications. The dynamic functional testing methods (Moisture management and Thermal properties) were carried out to simulate the actual wearing environment of the sports clothing. This study will create a new scope of research opportunities in the field of bi-layer sports textiles.

This study was conducted to explore the influence of fibre blend and structural tightness factor on the comfort level of sportswear and to find the suitable fibre blend for active sportswear clothing.

Super 304HCu super austenitic stainless steel tubes containing 2.3 to 3 (Wt.%) of copper (Cu) is used in superheaters and reheater tubings of nuclear power plants. In general, austenitic stainless steels welded by conventional constant current gas tungsten arc welding (CC-GTAW) produce coarse columnar grains, alloy segregation and may result in inferior mechanical properties. Pulsed current gas tungsten arc welding (PC-GTAW) can control the solidification structure by altering the prevailing thermal gradients in the weld pool.

Super 304HCu tubes of Ø 57.1 mm and the wall thickness of 3.5 mm were autogenously welded using CC and PC-GTAW processes. Joints are characterized using optical microscopy, electron microscopy, energy dispersive spectroscopy and electron backscatter diffraction (EBSD) techniques. Hot tensile properties of the weld joints were evaluated and correlated with their microstructural features.

Current pulsing in GTAW has resulted in minimal eutectic film segregation, lower volume % of delta ferrite and appreciable improvement in tensile properties than CC-GTAW joints.

The EBSD boundary map and inverse pole orientation map of Super 304HCu weld joints evidence the grain refinement and much frequent high angle grain boundaries achieved using weld current pulsing.

The purpose of this paper is to determine the optimum level of geometrical parameters such as helix angle, nose radius, rake angle and machining parameters such as cutting speed, feed rate and depth of cut to arrive minimum surface roughness and tool wear during end milling of Al 356/SiC metal matrix composites (MMCs) using high speed steel end mill cutter.

L27 Taguchi orthogonal design with six factors and three levels is employed for conducting experiments. Analysis of variance (ANOVA) is carried out using Minitab16 software to find the influence of each input parameter on output performance measure. Grey-fuzzy logic multi optimisation algorithm is used to find the optimum level of the input parameters for minimum surface roughness and tool wear simultaneously.

It is found that optimal combination of helix angle 40°, nose radius 0.8 mm, rake angle 12°, cutting speed 90 m/min, feed rate 0.04 mm/rev and depth of cut 1.5 mm have generated minimum surface roughness of 0.4063 µm and tool wear of 0.0375 mm. From ANOVA analysis, it is found that cutting speed influence is more on output performance followed by helix angle and rake angle compared with other machining and geometrical parameters.

The influence of tool geometry during end milling of MMC using Grey-fuzzy logic algorithm has not been explored previously.