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This paper aims to present an experimental investigation and optimization of a low-temperature thermoelectric module to examine the influence of the main operating conditions.

In this work, a comparison was made by varying the various operating parameters such as heat source temperature, the flow rate of the cold fluid and the external load resistance. A Taguchi method was applied to optimize the parameters of the system. Three factors, including the external load resistance, mass flow rate of water (at the heat sink side) and heater temperature (at the heat source side) along with different levels were taken into account. Analysis of variance was used to determine the significance and percentage contribution of each parameter.

The experimental results show that the maximum power output 8.22W and the maximum conversion efficiency 1.11 per cent were obtained at the heater temperature of 240°C, the cold fluid mass flow rate of 0.017 kg/s, module temperature difference of 45°C and the load resistance of 5 O. It was observed that the optimum parameter levels for maximum power output determined as 5 O external load resistance, 0.17 kg/s mass flow rate of water and 240°C heater temperature (A1B3C3). It reflects that these parameters influence on the optimum conditions. The heater temperature is the most significant parameter on the power output of the thermoelectric module.

It is clear from the confirmation test that experimental values and the predicted values are in good agreement.

Reflow soldering is one of the most significant factors in determining solder joint defect rate. This study aims to introduce an innovative approach for optimizing the multiple performances of the reflow soldering process.

This study aims to minimize the solder joint defect rate of a ball grid array (BGA) package by using the grey‐based Taguchi method. The entropy measurement method was employed together with the grey‐based Taguchi method to compute for the weights of each quality characteristic. The Taguchi L18 orthogonal array was performed, and the optimal parameter settings were determined. Various factors, such as slope, temperature, and reflow profile time, as well as two extreme noise factors, were considered. The thermal stress, peak temperature, reflow time, board‐ and package‐level temperature uniformity were selected as the quality characteristics. These quality characteristics were determined using the numerical method. The numerical method comprises the internal computational flow that models the reflow oven coupled with the structural heating and cooling models of the BGA assembly. The Multi‐physics Code Coupling Interface was used as the coupling software.

The analysis of variance results reveals that the cooling slope was the most influential factor among the multiple quality characteristics, followed by the soaking temperature and the peak temperature. Experimental confirmation test results show that the performance characteristics improved significantly during the reflow soldering process.

The proposed approach greatly reduces solder joint defects and enhances solutions to lead‐free reliability issues in the electronics manufacturing industry.

The findings provide new guidelines to the optimization method which are very useful for the accurate control of the solder joint defect rate within components and printed circuit board (PCB) which is one of the major requirements to achieve high reliability of electronic assemblies.

The purpose of this paper is to propose a new method of robust parameter design for dynamic multi‐response system. The objectives are to resolve the correlations among multiple responses and the uncertainty of system with incomplete information.

First, desirability function is used to measure dynamic system sensitivity and system variation, and principal component analyses on the two indices are conducted. Second, the grey relational grade (GRD) between principal component sequences of the two indices and their respective ideal sequences, gained by grey relational analysis, is converted to an integrated GRD (IGRD) index by means of TOPSIS method, and then the optimal level combination of controllable factors is identified based on the IGRD index.

It was found that the optimal factor level combination obtained by the proposed method is nearest the ideal solution and farthest from the negative ideal solution. The validity and superiority of the proposed method are confirmed through two illustrative examples.

It should be noted that the proposed method fails to consider the interaction effects between controllable factors and noise factors.

The method proposed in the paper effectively integrates several common methods to optimize a dynamic multiple responses system based on Taguchi's robust parameter design. These methods do not involve complicated mathematical theory, and are therefore easy for practitioners to use in engineering practice.

Glass fibre reinforced plastics (GFRP) contain two phases of materials with drastically distinguished mechanical and thermal properties, which brings in complicated interactions between the matrix and the reinforcement during machining. Surface quality and dimensional precision will greatly affect parts during their useful life especially in cases where the components will be in contact with other elements or materials during their useful life. The purpose of this paper is to discuss the application of the Taguchi method with fuzzy logic to optimise the machining parameters for machining of GFRP composites with multiple characteristics.

The machining tests were performed on a CNC milling machine using solid carbide (K10) End mill cutting tool with three different helix angles. Experiments were planned using Taguchi’s orthogonal array with the cutting conditions prefixed.

The machining parameters, namely, helix angle of the end mill cutter, spindle speed, feed rate, depth of cut, and work piece fibre orientation (specially applied to the GFRP composites) were optimised with considerations of multiple response characteristics, including machining force, material removal rate, and delamination. The results from confirmation runs indicated that the determined optimal combination of machining parameters improved the performance of the machining process.

Multi-response optimisation of machinability behaviour of GFRP composites using fuzzy logic has not been attempted previously.

There are process uncertainties and material property variations during laminated steel sheet forming, and those fluctuations may result in non-reliable forming quality issues such as fracture and delamination. Additionally, the optimization of sheet forming process is a typical multi-objective optimization problem. The target is to find a multi-objective design optimization and improve the process design reliability for laminated sheet metal forming. The paper aims to discuss these issues.

Desirability function approach is adopted to conduct deterministic multi-objective optimization, and response surface is used as meta-model. Reliability analysis is conducted to evaluate the robustness of the multi-objective design optimization. The proposed method is implemented in a step-bottom square cup drawing process. First, forming process parameters and three noise factors are assumed as probability variables to conduct reliability assessment of the laminated steel sheet forming process using Monte Carlo simulation. Next, only two forming process parameters, blank holding force and frictional coefficient, are considered as probability variables to investigate the influence of the forming parameter deviation on the variance of the response using the first-order second-moment method.

The results indicate that multi-objective design optimization using desirability function method has high efficiency, and an optimized robust design can be obtained after reliability assessment.

The proposed design procedure has potential as a simple and practical approach in the laminated steel sheet forming process.

The purpose of this study is to manufacture test boards for re-enacting plant or field situations where vacuum chamber for expelling gas bubbles and autoclave equipment would not be accessible. This research focuses on the examination and enhancement of tensile strength for the nanocomposites consisting of uniaxial glass fiber mats, nanoclay (NC) and epoxy.

The parameters considered are the weight content of Cloisite 15A NC, the volume of glass fiber (V_gf) and the direction of glass fibers (θ). The composites are made by hand lay-up technique and tested according to ASTM D 638 standard. Taguchi L9 orthogonal array is used to design the experiments.

The results imply that the orientation of fibers exhibited high significance with a p-value of 0.001 for the upgrade of strength. NC percentage and the volume of fiber have a low effect as the p-values obtained were 0.375 and 0.294. Confirmation tests were performed at the optimal levels of parameters and the outcomes were in the permissible range of the anticipated values of S/N ratio and mean tensile strength. The negligible effect of nanoclay is due to the lack of infusion of resin into the d-spacing of clay layers due to the low configuration settings of mixing conditions which was confirmed by XRD studies. The negligible effect of glass fiber volume is due to the void content and lack of stress transfer between fibers uniformly due to the void content and improper mixing of nanoclay.

The limitation of this study is that a low-speed mechanical stirrer was used to mix NC in the epoxy and the mixture was not subjected to vacuum and ultrasonication for degassing and deagglomeration.

These composites can be used as substitute materials in place of metallic parts in the aerospace and automobile sector. These composites can be used in civil structures instead of steel and concrete, which have low strength-to-weight ratio and where the requirement of strength is in the range of 60 to 390 MPa.

The composites can be used in a variety of applications, for example, structural works, automotive panels and low-cost housing.

This research gives an idea about the combined contribution of NC, V_gf and “θ” to the improvement of tensile strength of the glass-epoxy composite.

The purpose of this paper is to develop a mathematical model for metal removal rate and surface roughness through Taguchi method and analyse the influence of the individual input machining parameters (cutting speed, feed rate, helix angle, depth of cut and wt% on the responses in milling of aluminium-titanium diboride metal matrix composite (MMC) with solid carbide end mill cutter coated with nano-crystals.

Taguchi OA is used to optimise the material removal rate (MRR) and Surface Roughness by developing a mathematical model. End Milling is used to create slots by combining various input parameters. Five factors, three-level Taguchi method is employed to carry out the experimental investigation. Fuzzy logic is used to find the optimal cutting factors for surface roughness (Ra) and MRR. The factors considered were weight percentage of TiB₂, cutting speed, depth of cut and feed rate. The plan for the experiments and analysis was based on the Taguchi L27 orthogonal array with five factors and three levels. MINITAB 17 software is used for regression, S/N ratio and analysis of variance. MATLAB 7.10.0 is used to perform the fuzzy logics systems.

Using fuzzy logics, multi-response performance index is generated, with which the authors can identify the correct combination of input parameters to get higher MRR and lower surface roughness value with the chosen range with 95 per cent confidence intervals. Using such a model, remarkable savings in time and cost can be obtained.

Machinability characteristics in Al-TiB₂ MMC based on the Taguchi method with fuzzy logic has not been analysed previously.

This research aims to study the stencil printing process of the quad flat package (QFP) component with a pin pitch of 0.4 mm. After the optimization of the printing process, the desired inspection specification is determined to reduce the expected total process loss.

Static Taguchi parametric design is applied while considering the noise factors possibly affecting the printing quality in the production environment. The Taguchi quality loss function model is then proposed to evaluate the two types of inspection strategies.

The optimal parameter-level treatment for the solder paste printing process includes a squeegee pressure of 11 kg, a stencil snap-off of 0.14 mm, a cleaning frequency of the stencil once per printing and using an air gun after stencil wiping. The optimal upper and lower specification limits are 119.8 µm and 110.3 µm, respectively.

Noise factors in the production environment are considered to determine the optimal printing process. For specific components, the specification is established as a basis for subsequent processes or reworks.