Shot-peening is a surface treatments utilized extensively in the industry to enhance the performance of metal parts against fatigue. This paper aimed to find the optimal parameters of the shotpeening process based on the finite elements model and the Taguchi method. The effects of three peening parameters (shot diameter, shot velocity, coverage percentage) are investigated on residual stress and roughness using Taguchi method. A new Taguchi technique is proposed by combining it with desirability function to optimize the shot-peening parameters that simultaneously provide two or more responses in an optimal mode. The results show that the coverage percentage has the most influence on the surface stress and maximum compressive stress whereas the velocity and diameter of the shot are the most effective parameters on the depth of compression stress. The shot velocity is the main factor of the surface roughness due to the shot peening. Through the proposed structure, optimal conditions can be obtained for surface stress and roughness simultaneously with high-coverage and low-velocity. Eventually, results reveal the effectiveness of the proposed strategy in stand point of saving time and cost.

In this study, biomass dry weight [DW (0.912 g/L)] was markedly enhanced at pH of 10 for 24 h of aeration. The maximum production of protein (14.239 mg/L) was obtained at the highest photoperiod. The highest content of PC and APC (0.129 and 0.099 mg/L, respectively) was recorded at pH of 10 for 24 h of aeration. The highest content of total chlorophyll (Ca and Cb) and carotenoids (K) (6.436, 3.421, and 2.856 mg/L) was recorded at pH of 9. The content of photosynthesis pigments (Ca, Cb, and K) was reduced by increasing pH from 9 to 10, while the high alkaline pH (10) may favor the over-production of biomass, protein, phycobiliprotein pigments (PC and APC). Moreover,  A. maxima increased the accumulation of photosynthesis pigment under strong illumination and decreased the accumulation of phycobiliprotein pigments by increasing the light irradiance time from 12 to 24 h.

In the friction stir welding process, preferred joint property is vastly reliant on the selection of optimal welding conditions. The present study aims to use the Taguchi technique to , nd the optimal process conditions for achieving superior Ultimate Tensile Strength (UTS) in friction stir welded Aluminum Matrix Composite (AMC) joints. AMCs reinforced with rutile particles which have a potential application in the aerospace, automotive, and marine industries are used in the present work. Taguchi parametric design technique was used to identify the effect of rotational speed, tool traverse speed, and tool geometry on joint strength. Taguchi approach confined the optimum level of process variables and these variables were optimized. The investigation showed that the parameters within the selected value range will seriously affect the output. The predicted value of the output response was 155. 48 MPa, which was validated by further experiments using the optimum process variables. Analysis Of Variance (ANOVA) results indicated that the UTS of the composite joint is mainly affected by the tool traverse speed followed by rotational speed, and tool geometry. The microstructural study unveiled that grain size is dependent on process variables and , finer grains offer better joint properties.

In this paper, the heat transfer to the fluid, passing through the double forward facing step (FFS) channel with square obstacle is enhanced by Taguchi’ s S/N ratio analysis. Flow through the forward facing step channel has a wide range of applications in thermal systems due to its flow separation and subsequent reattachment, which in turn enhances the heat transfer. Flow separation and reattachment mainly depends on the channel geometry, obstacle and flow parameters. Hence, in this study, step height in the channel, obstacle size, Reynold’ s number and gap between the obstacle and step are included as control paramters in the S/N ratio analysis for maximizing the heat transfer. These parameters are varied through three levels of values and L9 orthogonal array is employed. Numerical simulation technique is applied to analyze the L9 cases through computational fluid dynamics code. From the simulation, the rise in temperature at the channel exit with reference to the inlet is predicted. The best values for the identified control parameters conclude to a temperature raise of about 2. 86 C. The optimum result obtained from the S/N ratio analysis is also compared with response surface methodology technique. Finally, analysis of variance (ANOVA) is conducted and identified that step height and flow Reynold’ s number affect the heat transfer by about 79 and 19%, respectively.

In this study, the application of gray relational analysis (GRA) and Taguchi method in multi-criteria process parameters selection of turning operation has been investigated. The process responses under study are material removal rate (MRR) and surface roughness (SR); in turn, the input parameters include cutting speed, feed rate, depth of cut and nose radius of the cutting tool. The proposed approach employs GRA to convert the values of process outputs, obtained from Taguchi method, into a single objective used to determine the best set of process parameters for turning operation of AISI 202 austenitic stainless steel. Analytical results reveal that the combination of higher levels of cutting speed, depth of cut, and nose radius and lower level of feed rate is essential to achieve simultaneous maximization of material removal rate and minimization of surface roughness. Using verification test, these settings would result in more than 14% improvement over those for initial settings. The analysis of variance (ANOVA) and F-tests showed that nose radius is the major factor affecting the gray relational grade (GRG) with 41% contribution.  In general, the proposed procedure is quite efficient in determining the effects of process parameters and finding the best set of process parameters.

CNC turning is widely used as a manufacturing process through which extra unwanted material is turned to get a high degree of surface roughness. In this research article, Taguchi technique was coupled with Grey Relational Analysis (GRA) to optimize the turning variables, or turning parameters, for the simultaneous improvement of productivity, root mean square roughness (Rq), and average surface roughness (Ra). Taguchi technique L27 (34) orthogonal array was used in this experimental work. Depth of cut, feed, and speed were considered as the controllable process parameters. Root mean square roughness (Rq), average surface roughness (Ra), and material removal rate (MRR) were considered as the performance characteristics; according to TGRA results, the optimum combination in this study found A1B1C1 (Vc=400 rpm, f=0. 06 mm/rev, and DOC=0. 5 mm). The optimum values of Ra and MRR for this study were 6. 86 μ m and 20690. 31 mm3/s, respectively. Further, ANOVA was applied, and showed that depth of cut (DOC) had the most significant effect and followed in line by speed and feed for multi-response optimization. According to the results of Analysis of Variance (ANOA), the %age contribution of DOC (depth of cut), speed, and feed were 38. 71 %, 11. 89%, and 8. 466%, respectively.