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Scatter in the outcome of repeated experiments is unavoidable due to measurement errors in addition to the non-linear nature of the output responses with unknown influential input parameters. It is a standard practice to select an orthogonal array in the Taguchi approach for tracing optimum input parameters by conducting a few number of experiments and confirm them through additional experimentation (if necessary). The purpose of this paper is to present a simple methodology and its validation with existing test results in finding the expected range of the output response by suggesting modifications in the Taguchi method.

The modified Taguchi approach is proposed to find the optimum process parameters and the expected range of the output response.

This paper presents a simple methodology and its validation with existing test results in finding the expected range of the output response by suggesting modifications in the Taguchi method.

Adequacy of this methodology should be examined by considering the test data on different materials and structures.

The introduction of Chauvenet’s criterion and opposing the signal-to-noise ratio transformation on repeated experiments of each test run will provide fruitful results and less computation burden.

The purpose of this paper is to find out the optimum machining parameters using Taguchi technique with principal component analysis (PCA) during end milling of GFRP composites.

In multi-objective optimization, weight criteria of each objective are important for producing better and accurate solutions. This method has been employed for simultaneous minimization of surface roughness, cutting force and delamination factor. Experiments were planned using Taguchi’s orthogonal array with the machining parameters, namely, helix angle of the end mill cutter, spindle speed, feed rate and depth of cut were optimized with considerations of multiple response characteristics, including machining force, surface roughness and delamination as the responses. PCA is adopted to find the weight factors involved for all objectives. Finally analysis of variance concept is employed on multi-SN ratio to find out the relative significance of machining parameter in terms of their percentage contribution.

The multi-SN ratio is achieved by the product of weight factor and SN ratio to the performance characteristics in the utility concept. The results show that a combination of machining parameters for the optimized results has helix angle of 35°, machining speed of 4,000 m/min, feed rate of 750 mm/rev and depth of cut of 2.0 mm.

Effect of milling of GFRP composites on delamination factor, surface roughness and machining force with various helix angle solid carbide end mill has not been analysed yet using PCA techniques.

Diagnostic tests are widely used in many areas of modern technological society, but they are of particular importance in medicine, where early and accurate diagnosis can decrease morbidity and mortality rates of disease. How the quality of diagnostic information and decisions should be measured in a meaningful way has become increasingly important in recent years as an abundance of new diagnostic tests have been introduced. A number of seemingly independent indices are studied for evaluating diagnostic performance such as the receiver operating characteristic curves and signal‐to‐noise ratios. Designing robustness into diagnostic tests can only be achieved by minimizing the variation in the total number of false diagnosis. This article has undertaken a comparison of signal‐to‐noise ratios developed by Taguchi in quality engineering and system performance in manufacturing industry. A hybrid is also computed and its relevance to physicians as an efficient assessment method is proposed and strongly encouraged.

The purpose of this paper is to optimize the gas metal arc welding (GMAW) process input parameters simultaneously considering the multiple output variables (bead width (BW), bead height (BH) and depth of penetration (DP)).

Grey‐based Taguchi approach was used for designing the experiment, L27 orthogonal array was used which composed of three levels and 27 rows, which means that 27 experiments were carried out. Design of experiments was selected based on a four welding parameters with three levels each. The selected welding parameters for this paper are gas flow rate, voltage, travel speed and wire feed rate. The bead‐on‐plate welding trials are carried out on AISI 904L super austenitic stainless steel (SASS) sheets and evaluate the shape of the fusion zone depends upon a number of input parameters.

Bead‐on‐plate welding of 904L SASS sheet is successfully performed (without any cracks and discontinuity) by GMAW process and the bead profiles are measured. The predicted bead profiles have the better DP and lower BH and BW. It is found that the optimized setting values are improving the response values by 10 per cent.

The optimal welding conditions are identified in order to increase the productivity and minimize the total operating cost. The process input parameters effect is determined under the optimal welding combinations.

The aim of this article is to show how Taguchi methods can be applied to health care.

The quadratic loss function is at the heart of Taguchi methods. It is a powerful motivator for a quality strategy and can be used to adequately model the loss to society in health care. It also establishes a relationship between cost and variability. Therefore, it can be integrated with the performance and parameters of the design of medical applications. Signal‐to‐noise ratios give a sense of how close is the performance to the ideal. By maximizing the signal‐to‐noise ratio, quality‐engineering activities can be aimed at identifying near‐optimum levels of factors and making quality equal to zero.

This article shows that, when the patients' requirements are consistently met, lower losses can provide an impetus to improve patient satisfaction.

The article outlines areas in health care where Taguchi methods can easily be applied.

This paper examines the suitability of the discretizing approach of Roy and Dasgupta, based on the discrete concentration method of Roy, for determination of reliability of complex systems under Weibull set‐up. A system is said to be complex if its distribution is intractable and analytical evaluation of probability is not available. Numerical analyses on a hollow cylinder, solid shaft, hollow rectangular tube, and the power dissipated by a resistor have been worked out to examine the closeness between the discretized reliability estimators and the simulated values based on Monte Carlo method. Also, it may be observed that the proposed approach has superior performance in comparison to the discretizing approach of English et al., based on the moment equalization method of Taguchi. The mean absolute deviation under the discrete concentration approach is much less than the same under the moment equalization approach for the Weibull set‐up.

The purpose of this study is to optimize the process parameters (wire feed rate (F), voltage (V), welding speed (S) and torch angle (A)) in order to obtain the optimum bead geometry (bead width (W), reinforcement (R) and depth of penetration (P)), considering the ranges of the process parameters using evolutionary algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm.

The modeling of welding parameters in flux cored arc welding process using a set of experimental data and regression analysis, and optimization using GA and SA algorithm.

The adequate mathematical model was developed. The multiple objectives were optimized satisfactorily by the GA and SA algorithms. The feasible solution results are very closer to the optimized results and the percentage error was found to be negligibly small.

The optimal welding parameters were identified in order to increase the productivity. The welding input parameters effect was found.

To solve the trade‐offs between marketing and R&D domains and to minimize information loss in new product development (NPD), this study proposes an integrated design process as a new solution to the interface system between the two domains.

House of Quality integrated with multivariate statistical analysis is used for determining important design features. These design features are used as parameters for conjoint analysis and Taguchi method, and then the results of analyses are compared. Sequential application of conjoint analysis and Taguchi method, depending on the differences in utilities and signal to noise ratios, is applied for the integrated design process. An automotive interior design is illustrated for the validation of the integrated design process.

The integrated design process determines a point of compromise between the optimums of conjoint analysis and Taguchi method. Sequential application of two methods ensures full utilization of both methods and no loss of information.

More illustrations on NPD are needed to verify the proposed process.

The design process suggested in this study can be used for process innovation in six sigma approach and be integrated with value chain intelligently. This study proposes the strategic guideline of the integrated design process for enterprises.

The integrated design process suggests the solution for the trade‐offs between marketing domain that pursues the utility of product and R&D domain that emphasizes robustness of product quality. This integrated design process will give enterprises competitive advantages in NPD.

Proposing an improved model for evaluating criticality of non-value added (waste) in operation is necessary for realizing sustainable manufacturing practices. The purpose of this paper is concerning on improvement of the decision support model for evaluating risk criticality lean waste occurrence by considering the weight of modified FMEA indices and the influence of waste-worsening factors causing the escalation of waste risk magnitude.

Integration of entropy and Taguchi loss function into decision support model of modified FMEA is presented to rectify the limitation of previous risk reprioritization models in modified FMEA studies. The weight of the probability components and loss components are quantified using entropy. A case study from industry is used to test the applicability of the integration model in practical situation.

The proposed model enables to overcome the limitations of using subjective determination on the weight of modified FMEA indices. The inclusion of the waste-worsening factors and Taguchi loss functions enables the FMEA team to articulate the severity level of waste consequences appropriately over the use of ordinal scale in ranking the risk of lean waste in modified FMEA references.

When appraising the risk of lean waste criticality, ignorance on weighting of FMEA indices may be inappropriate for an accurate risk-based decision-making. This paper provides insights to scholars and practitioners and others concerned with the lean operation to understand the significance of considering the impact of FMEA indices and waste-worsening factors in evaluating criticality of lean waste risks.

The method adopted is for quantifying the criticality of lean waste and inclusion of weighting of FMEA indices in modified FMEA provides insight and exemplar on tackling the risk of lean waste and determining the most critical waste affecting performability of company operations.

Integration of the entropy and Taguchi loss function for appraising the criticality of lean waste in modified FMEA is the first in the lean management discipline. These findings will be highly useful for professionals wishing to implement the lean waste reduction strategy.

Importance performance analysis (IPA) is a technique widely used to assist organisations in developing marketing strategies and improving products or service quality. Many scholars have revised IPA to augment its effectiveness. However, this involves some unknown problems that could lead organisations to make wrong decisions. This paper aims to look at this issue.

As a solution, this paper introduces Taguchi's signal‐to‐noise (S/N) ratio approach to treat ordered categorical data in analysing customer satisfaction and integrates it with gap analysis (GA) through S/N ratio to develop a modified IPA model. A Taiwan air‐conditioning manufacturer maintenance and repair service is illustrated to demonstrate the method.

According to the test case, the modified IPA model obtained more reliable results than the traditional IPA method, considering the central tendency and variance from different customer perceptions. The proposed method can determine exact marketing strategies and improvement directions for product or service quality attributes, reduce variance and (or) move performance to the target value.

This model overcomes the limitations of the traditional IPA model while retaining the merits of the traditional model. Using the modified IPA model an organisation can define its marketing strategies and take action to establish quality improvement activities. In other words, the organisation can avoid making wrong decisions when using the modified IPA model.