Optimisation of Water Absorption Parameters of Dual-Filler Filled Composites Using Taguchi and Moderated Taguchi Techniques

Abstract

This work contributes two novel modified Taguchi techniques to the optimal parametric setting for minimum water absorption in epoxy composites. Taguchi method, using ASTM standards was applied with factors (initial weight, final weight, length, sample thickness and time of immersion) and four levels in the experimental design. The analysis of variance (ANOVA) evaluates the significance and individual contributions of the parameters. The optimal parametric setting was A1B4C3D4E1 (initial weight, 2.61 g; final weight, 2.69 g; length, 62.73 mm; thickness, 3.88 mm; time, 15.65 hrs). The ANOVA identifies time and length as dominant parameters (98.98 and 1.02 % contributions, respectively). Taguchi-Pareto analysis found only factor-level from the time and length parameters economical to optimality. The Taguchi-ABC analysis revealed the individual weights and contributions of the factor-level irrespective of its initial groupings. The new Taguchi techniques highlighted the importance of time and length of sample in obtaining minimum water absorption of composites.

Taguchi Optimisation of Cast Geometries for A356/Organic Particulate Aluminium Alloy Composites Using a Two-Phase Casting Process

“…Signal factors present the average operation of the method, while noise factors are factors that are complex and hard to operate. Taguchi method has three designs, which are system design which allows the selection of suitable operational levels that defines the states of the parameters in the experiment, the parametric design that facilitates in the identification of factor levels that produce the ideal operation of the process and then the tolerance design which is employed to lower the tolerance of factors that produce meaningful impact to the system [22]. The parametric design is employed in this work to get the ideal set of parameters.…”

“…For this experiment, "smaller-the-best" is selected to the quality characteristics. The objective function is expressed corresponding to the smaller-the-best quality characteristics in Equation (1) [22,[34][35][36].…”

“…Analysis of variance is a statistical method that is employed to calculate the singular influence of the governable factors on the quality characteristics [22]. The analysis of variance for the A356 alloy cast is shown in Table 7.…”

“…This implies that it is a good and promising initiative to reinforce A356 with abori wood and other organic particulates. In this paper, we offer the findings of an optimisation study using newly developed Taguchi modified models, primarily Taguchi-Pareto and Taguchi-ABC, built-up recently by Ajibade et al [22] and then compare the findings with the classical Taguchi method. The problem solved is the challenge of attaining accurate measurements to optimise the process parameters during the changes in one casting process to another.…”

Optimisation of bottling process using “hard” total quality management elements

“…According to Fotopoulos et al (2009), hard TQM elements entail several tools, including Pareto analysis, design of experiments, flow charts, quality function deployment, relations diagram and more. Few studies have also been conducted in several contests, including Indian, Turkish, Irish and Greece contexts and they have proved But Taguchi methods and the response surface methodology, which are "hard" elements of total quality management (TQM) could radically transform such performance (Ajibade et al, 2019;Raji and Oke, 2019). This work has two-fold rationalization.…”