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The purpose of this paper is to demonstrate the ability to researchers of using design of experiments (DoE) as a structured and systematic approach to performing systematic literature reviews. The authors demonstrate a simple case study illustrating the application of DoE in executing a systematic literature review on two popular topics in higher education: academic leadership and Lean Six Sigma.

The methodology involves the systematic literature review of linking academic leadership with terms such as Lean, Six Sigma, Total Quality Management, Maturity Model and Continuous Improvement. The main tool used to structure the systematic literature review is a Taguchi Orthogonal Array design, specifically an L16 grid and the method is verified by conducting another review, replacing the term academic leadership with simply leadership.

The approach identified at first no research papers linking the terms; however, when academic leadership was replaced with university, 19 research papers where discovered. The verification exercise, linking just leadership with the other search string generated over 1,000 results – demonstrating that the tool can find large volumes of articles if they exist, the search was completed for a ten year time frame – 2004 to 2014.

The case study focussed on a field which is known to have little current research and the verification exercise deliberately targeted a known large body of research. The authors will continue to use the approach and refine the technique over time.

This approach would help any researcher despite of their discipline to identify opportunities and gaps in the current literature.

The paper shows how DoE can be used in an academic research-based process. No other literature review approach currently exists which uses Taguchi approach to DoE to filter the search criteria.

Through this study, four different types of woven fabric structures were created by using cotton/banana blends with a 70:30 ratio by varying the weaving specifications. This study aims to investigate the comfort and mechanical properties of these woven materials.

Taguchi L16 experimental design (5 factors and 4 levels) with response surface methodology tool was used to optimize mechanical and comfort characteristics. The yarn samples used in this study are cotton/banana with a blend ratio of 70:30. Fabric type (A), grams per square metre (GSM; B), yarn count (C), fabric thickness (D) and cloth cover factor (E) are the chosen process characteristics.

The highest tensile strength and tearing strength of the cotton/banana blended fabric samples were obtained as 326.3 N and 90.3 k.gf/cm, respectively. Similarly, the highest thermal conductivity and overall moisture management capacity values were found to be 0.6628 and 3.06 W/mK X10⁻⁴, respectively. The optimized process parameters for obtaining maximum mechanical properties were using canvas fabric structure, 182 GSM, 36^s Ne yarn count, 0.48 mm fabric thickness and 23.5 cloth cover factor. Similarly, the optimized process parameters for obtaining maximum comfort properties were achieved using a twill fabric structure, 182 GSM, 32^s Ne yarn count, 0.4 mm fabric thickness and 23 cloth cover factor.

In contrast to synthetic fabrics, banana fibre and its blended materials are significant ecological solutions for apparel and functional clothing. Products made from banana fibre are a sustainable and green alternative to conventional fabrics. Banana fibre obtained from the pseudostem of the plant has an appearance similar to ramie and bamboo fibres. Numerous studies showed that banana fibre could absorb significant moisture and be spun into yarn through ring and rotor spinning technology. On the other hand, this fibre can be easily combined with cotton, jute, wool and synthetic fibre. The present utilization of pseudostem of banana plant fibre is very minimal. This type of research improves the usability of bananas their blended fabrics as apparel and functional wear.

In this study, experimental studies were carried out using different process parameters of the soft pneumatic gripper (SPG) fabricated by the fused deposition modeling method. In the experimental studies, the surface quality of the gripper was examined by determining four different levels and factors. The experiment was designed to estimate the surface roughness of the SPG.

The methodology consists of an experimental phase in which the SPG is fabricated and the surface roughness is measured. Thermoplastic polyurethane (TPU) flex filament material was used in the fabrication of SPG. The control factors used in the Taguchi L16 vertical array experimental design and their level values were determined. Analysis of variance (ANOVA) was performed to observe the effect of printing parameters on the surface quality. Finally, regression analysis was applied to mathematically model the surface roughness values obtained from the experimental measurements.

Based on the Taguchi signal-to-noise ratio and ANOVA, layer height is the most influential parameter for surface roughness. The best surface quality value was obtained with a surface roughness value of 18.752 µm using the combination of 100 µm layer height, 2 mm wall thickness, 200 °C nozzle temperature and 120 mm/s printing speed. The developed model predicted the surface roughness of SPG with 95% confidence intervals.

It is essential to examine the surface quality of parts fabricated in additive manufacturing using different variables. In the literature, surface roughness has been examined using different factors and levels. However, the surface roughness of a soft gripper fabricated with TPU material has not been examined previously. The surface quality of parts fabricated using flexible materials is very important.

The purpose of this study is to check the reliability of a multi-pin joint to be a fail-safe joint by considering different geometric and material parameters. The pin joints are made of uni-directional fiberglass that has been impregnated with epoxy composites incorporating 3% nano-clay.

This study incorporates the analysis of multi-pin joints experimentally, numerically and statistically using the Weibull approach. During analyses, geometrical parameters edge to diameter (E:D), longitudinal pitch to diameter (F:D), side edge to diameter (S:D) and transverse pitch to diameter (P:D) were analyzed using the Taguchi method with a higher-the-better L16 orthogonal array.

This study aims to develop multi-pin laminated joints to attain higher reliability, which have been designated as fail-safe joints for the intended application and which have higher joint strength. The study reveals that to achieve 99% reliability or 1% probability of failure using the Weibull approach, 24.4% load decrement from the experimental result recorded for three-pin joint configuration at E:D = 4, F:D = 5, S:D = 4 and P:D = 5. Similarly, for the four-pin configuration at E:D = 4, F:D = 4, S:D = 4 and P:D = 5, 23.07% of load decrement observed from the experimental result implies that the expected load with a 99% reliability offers a safe load.

A reliability analysis on multi-pin joints was not conducted in structural application. Composite materials are used because of high reliability and high strength-to-weight ratio. So, in the present work, reliability of the multi-pin joint is analyzed using Weibull distribution.

Although Multi-Layer Ceramic Capacitors (MLCC) are known for its better frequency performance and voltage handling capacity, but under various environmental conditions, its reliability becomes a challenging issue. In modern era of integration, the failure of one component can degrade or shutdown the whole electronic device. The lifetime estimation of MLCC can enhance the reuse capability and furthermore, reduces the e-waste, which is a global issue.

The residual lifetime of MLCC is estimated using empirical method i.e. Military handbook MILHDBK2017F, statistical method i.e. regression analysis using Minitab18.1 as well as intelligent technique i.e. artificial neural networks (ANN) using MATLAB2017b. ANN Feed-Forward Back-Propagation learning with sigmoid transfer function [3–10–1–1] is considered using 73% of available data for training and 27% for testing and validation. The design of experiments is framed using Taguchi’s approach L16 orthogonal array.

After exploring the lifetime of MLCC, using empirical, statistical and intelligent techniques, an error analysis is conducted, which shows that regression analysis has 97.05% accuracy and ANN has 94.07% accuracy.

An intelligent method is presented for condition monitoring and health prognostics of MLCC, which warns the user about its residual lifetime so that faulty component can be replaced in time.

The purpose of this paper is to investigate the process parameters and optimise the machining input parameter of powder mixed electric discharge machining for high carbon high chromium alloy steel (D2 steel) for the industrial application. Grey relational analysis approach has been used to obtain the multiple performance output response.

In this experimental work, input parameters, namely, pulse on-time, discharge current, tool material and grit size, are selected. The design of the experiment has been constructed with the help of MINITAB 7 Software, in which L16 orthogonal array has been preferred for the experimentation. The effect of input parameters, namely, material removal rate, tool wear rate and surface roughness, is investigated. Grey relational analysis and analysis of variance are performed to optimise the input parameters and better output results.

In this experimentation, there is an increment of tool wear rate by 64.49 per cent, material removal rate by 47.14 per cent and surface roughness by 35.82 per cent.

A lot of practical applications have been found in many different material processing industries like metallurgy, machinery, electronics, transportation, military science, agricultural machinery, etc. These practical applications have brought forward definite and noticeable economic benefits.

The reader is given a general overview on the machining investigation and optimisation of processes parameters through the grey theory approach. It gives a new framework to investigate the problems where multiple input machining variable and various output responses are obtained in single optimised parameters.

Resistance spot welding (RSW) is an essential process in the automobile sector to join the components. The steel is the principal material utilized in car generation because of its high obstruction against erosion, toughness, ease of support and its recuperation potential. Due to this, it was planned to study the mechanical properties, hardness and microstructure characteristics of RSW of Stainless steel 304.

In the present research, RSW of 304 stainless steel plates with 1 mm thickness and effect of current intensity, welding time, electrode pressure and holding time on nugget diameter, tensile strength microhardness and microstructure of the joints was investigated. The specimens were prepared according to the dimensions of 30 × 100 mm with 30 mm overlaps joint through the RSW machine. The tensile test of the specimen was carried out on a universal testing machine and microhardness of specimens measured using Vickers’s hardness tester. Taguchi L16 orthogonal array was used to scrutinize the significant parameters for each output.

It has been observed that the tensile strength of the specimen is affected by the current intensity and nugget diameter, and the weld time has a significant effect on the tensile strength. Microhardness is highly influenced by electrode pressure and holding time, as the increase in both these parameters resulted in the increase of microhardness. This is due to rapid cooling, which is done by the cooling water flowing through the copper electrodes.

This study was carried out using a copper electrode with a flat face with selected parameters and response factors. The study can be useful for researchers working on optimization of welding parameters on stainless steel.

This paper presents calculation of the welding process parameters for obtaining optimal weld bead geometry in Flux Cored arc welding (FCAW) process. Bead on plate welding was carried as per L16 orthogonal array. In this paper weld bead geometry such as penetration, bead width, reinforcement and percentage of dilution of IS 2062 structural steel plates investigated. Two hybrid techniques firstly Taguchi method coupled with Grey relational analysis and secondly Taguchi method in combination with desirability function (DF) approach has been applied in this paper. Comparison made between two hybrid optimization techniques are made to analyze to choose the best method. Optimal results have been confirmed by confirmatory experiment which showed satisfactory results.

This study aims to obtain the lowest surface roughness (Ra) and drill bit adhesion values (AV) depending on the change in control factors (cutting speed-Vc, feed rate-f and drill bit-D) during drilling of the Al 5083 H116 alloy. Low roughness values increase the fatigue strength of the final part and affect tribological properties such as lubrication and friction. In the machining of ductile materials, the AV increases the Ra value and negatively affects the tool life.

Drilling tests were conducted using Taguchi L16 orthogonal array. The experimental measurement findings for Ra and AV were adjusted utilizing the Grey Relational Analysis (GRA), the Response Surface Method (RSM) and Artificial Neural Networks (ANN) to generate prediction values. SEM detected drill-tip adhesions and chip morphology and they were analyzed by EDX.

Ra and AV increased as the f increased. Vc affects AV; 86.04% f on Ra and 54.71% Vc on AV were the most effective control parameters. After optimizing Ra and AV using GRA, the f is the most effective control factor. Vc: 120 m/min, f: 0.025 mm/rev and D2 were optimal. ANN predicted with Ra 99.6% and AV 99.8% accurately. Mathematical models are obtained with RSM. The increase in f increased AV, which had a negative effect on Ra, whereas the increase in Vc decreased the adhesion tendency. With the D1 drill bit with the highest flute length, a relatively lower Ra was measured, as it facilitates chip evacuation. In addition, the high correlations of the mathematical models obtained indicate that the models can be used safely.

The novelty of this study is to determine the optimum drilling parameters with GRA and ANN for drilling the necessary holes for the assembly of ammunition wing propulsion systems, especially those produced with Al 5083 H116 alloy, with rivets and bolts.