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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.

There is growing evidence of a knowledge gap in the association of maintenance with production activities in bottling plants. Indeed, insights into how to jointly optimise these activities are not clear. In this paper, two optimisation models, Taguchi schemes and response surface methodology are proposed.

Borrowing from the “hard” total quality management elements in optimisation and prioritisation literature, two new models were developed based on factor, level and orthogonal array selection, signal-to-noise ratio, analysis of variance and optimal parametric settings as Taguchi–ABC and Taguchi–Pareto. An additional model of response surface methodology was created with analysis on regression, main effects, residual plots and surface plots.

The Taguchi S/N ratio table ranked planned maintenance as the highest. The Taguchi–Pareto shows the optimal parametric setting as A4B4C1 (28 h of production, 30.56 shifts and 37 h of planned maintenance). Taguchi ABC reveals that the planned maintenance and number of shifts will influence the outcome of production greatly. The surface regression table reveals that the production hours worked decrease at a value of planned maintenance with a decrease in the number of shifts.

This is the first time that joint optimisation for bottling plant will be approached using Taguchi–ABC and Taguchi–Pareto. It is also the first time that response surface will be applied to optimise a unique platform of the bottling process plant.

One of the key elements of a maintenance system is risk analysis because the risk level of an engineering system will determine the maintenance policy required. Failure Mode and Effect Analysis (FMEA) is widely applied in evaluating risk of failure of engineering systems. However, the conventional FMEA used in analyzing risk by most industries has shortcomings such as an inability to utilize imprecise and interval data in prioritizing risk. To overcome these limitations, different variants of FMEA have been reported in the literature. However, these modified approaches are computationally intensive; hence, the purpose of this paper is to develop an efficient FMEA-based methodology that is easy to analyze and implement.

The proposed technique combines the Taguchi method with FMEA in order to analyze risk of engineering systems easily and effectively. The effectiveness of the approach is demonstrated with a case study of the fuel oil system of a marine diesel engine.

The results of the integrated Taguchi method and FMEA, when compared with well-known techniques, namely, VIKOR and compromise programming, from the literature are very similar. From the comparative analysis, it was evident that the proposed method is a viable option to the more computationally intensive approaches used in the literature.

The approach proposed is novel and simple and can be implemented more easily than approaches from the literature in analyzing risk.

Friction stir welding (FSW) is considered an environmentally sound process compared to traditional fusion welding processes. It is a complex process in which various parameters influence weld strength. Therefore, it is essential to identify the best parameter settings for achieving the desired weld quality. This paper aims to investigate the multi-response optimization of process parameters of the FSWed 6061-T6 aluminum (Al) alloy.

The input process parameters related to FSW have been sorted out from a detailed literature survey. The properties of weldments such as yield strength, ultimate tensile strength, percentage elongation and microhardness have been used to evaluate weld quality. The process parameters have been optimized using the Taguchi-based grey relational analysis (GRA) methodology. Taguchi L16 orthogonal array has been considered to design the experiments. The effect of input parameters on output responses was also determined by the analysis of variance (ANOVA) method. Finally, to corroborate the results, a confirmatory experiment was carried out using the optimized parameters from the study.

The ANOVA result indicates that the tool rotation speed was the most significant parameter followed by tool pin profile and welding speed. From the confirmation test, it was observed that the optimum FSW process parameters predicted by the Taguchi method improved the grey relational grade by 13.52%. The experimental result also revealed that the Taguchi-based GRA method is feasible in finding solutions to multi-response optimization problems in the FSW process.

The present study is unique in the multi-response optimization of FSWed 6061-T6 Al alloy using the Taguchi and GRA methodology. The weld material having better mechanical properties is essential for the material industry.

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.

The aim of the paper is the fine‐tuning of proportional integral derivative (PID) controllers under model parameter uncertainties (noise).

The fine‐tuning of PID controllers achieved using the Taguchi method following the steps given: selection of the control factors of the PID with their levels; identification of the noise factors that cause undesirable variation on the quality characteristic of PID; design of the matrix experiment and definition of the data analysis procedure; analysis of the data; decision regarding optimum settings of the control parameters and predictions of the performance at optimum levels of control factors; calculation of the expected cost savings under optimum condition; and confirmation of experimental results.

An example of the proposed method is presented and demonstrates that given certain performance criteria, the Taguchi method can indeed provide sub‐optimal values for fine PID tuning in the presence of model parameter uncertainties (noise). The contribution of each factor to the variation of the mean and the variability of error is also calculated. The expected cost savings for PID under optimum condition are calculated. The confirmation experiments are conducted on a real PID controller.

As a further research it is proposed the contiguous fine‐tuning of PID controllers under a number of a variant controllable models (noise).

The enhancement of PID controllers by Taguchi method is proposed with the form of a hardware mechanism. This mechanism will be incorporated in the PID controller and automatically regulate the PID parameters reducing the noise influence.

Application of Taguchi method in the scientific field of automation control.

The purpose of this study is to investigate the impact of titanium oxide (TiO₂) filler on the abrasive wear properties of bamboo fiber reinforced epoxy composites (BFRCs) using a Taguchi approach. The study aims to enhance the abrasive wear resistance of these composites by introducing TiO₂ filler as a potential reinforcement, thus contributing to the development of sustainable and environmentally friendly materials.

This study focuses on the fabrication of epoxy/bamboo composites infused with TiO₂ particles within the Wt.% range of 0–8 Wt.% using hand layup techniques. The resulting composites were subjected to wear testing according to ASTM G99-05 standards. Statistical analysis of the wear results was carried out using the Taguchi design of experiments (DOE). Additionally, an analysis of variance (ANOVA) was used to determine the influential control factors impacting the specific wear rate (SWR) and coefficient of friction (COF).

The study illuminates how integrating TiO₂ filler enhances abrasive wear in epoxy/bamboo composites. Statistical analysis of SWR highlights abrasive grit size (grit) as the most influential factor, followed by normal load, Wt.% of TiO₂ and sliding distance. Analysis of the COF identifies normal load as the primary influential factor, followed by grit, Wt.% of TiO₂ and sliding distance. The Taguchi predictive model closely aligns with experimental results, validating its reliability. The morphological study revealed significant differences between the unfilled and TiO₂-filled composites. The inclusion of TiO₂ improved wear resistance, as evidenced by reduced surface damage and wear debris.

This research paper aims to integrate TiO₂ filler and bamboo fibers to create an innovative hybrid composite material. TiO₂ micro and nanoparticles show promise as filler materials, contributing to improved tribological properties of epoxy composites. The utilization of Taguchi’s DOE and ANOVA for statistical analysis provides valuable guidance for academic researchers and practitioners in optimizing control variables, especially in the context of natural fiber reinforced composites.

The purpose of this paper is to identify the ideal process parameters to be set for the drilling of hybrid fibre-reinforced polymer (FRP) (kenaf and banana) composite using High-Speed Steel drill bits (5, 10, 15 mm) coated with tungsten carbide by means of statistical reproduction of the delamination factor and machining force using Taguchi–Grey Relational Analysis.

The contemplated process parameters are Feed, Speed and Drill Diameter. The trials were carried out by taking advantage of the L-27 factorial design by Taguchi. Three factors, the three level Taguchi Orthogonal Array design in Grey Relational Analysis was used to carry out the trial study. Video Measuring System was used to identify the damage around the drill region. “Minitab 18” was used to examine the data collected by taking advantage of the various statistical and graphical tools available. Examination of variance is used to legitimize the model in identifying the most notable parameter.

The optimised set of input parameters were found out successfully which are as follows: Feed Rate: 450 mm/min, Cutting Speed: 3,000 rpm and Drill Diameter of 5 mm. When these values are fed in as input the optimised output is being obtained. From ANOVA analysis, it is apparent that the Speed (contribution of 92.6%) is the most influencing parameter on the delamination factor and machining force of the FRP material.

Optimization of process parameters on drilling of natural fibres reinforced in epoxy resin matrices using Taguchi–Grey Relational Analysis has not been previously explored.

In milling process the surface roughness and delamination are the most important performance characteristics, which are influenced by many factors like fibre orientation angle, helix angle, feed rate and spindle speed. The selection of these parameters at optimum level plays a vital role in getting minimum surface roughness and delamination factor. The purpose of this paper is to present multi-objective optimisation of Computer Numerical Control milling parameters using Grey-Taguchi method to get minimum surface roughness and delamination factor in machining of glass fibre reinforced plastics (GFRP) composites used in automotive, aircraft and manufacture of space ships.

The experiments are designed and conducted based on Taguchi's L₂₇ orthogonal array by taking fibre orientation angle, helix angle, feed rate and spindle speed at three levels and responses are surface roughness and delamination factor. Taguchi's signal-to-noise (S/N) ratio are determined based on their performance characteristics. A Grey relation grade is obtained by using S/N ratio. Based on Grey relational grade value, optimum levels of parameters have been identified by using response table and response graph.

Optimum levels of parameters for GFRP composites have been identified by using response table and response graph and the significant contributions of controlling parameters are estimated using analysis of variance.

The combined effect of fibre orientation angle and helix angle during milling of GFRP composites using Grey relational analysis has not been previously attempted for analysis.

The aim of the this study is to develop a new class of composites which would be more commercially viable and environmentally sustainable via reduced resource depletion, as there has been global interest in utilization of natural resources. The dry sliding wear behavior of glass-epoxy (G-E)-based composites filled with tamarind kernel powder (TKP) in different volume fractions of fillers (0 per cent, 3 per cent and 6 per cent) was studied as per standards.

In the present study, the analysis and optimization of the wear process has been studied. The Taguchi approach to experimental design was used to identify the effect of wear parameters such as applied load, sliding velocity and sliding distance. Taguchi tools such as analysis of variance and multiple linear regression models have been used to analyze, obtain the significant parameters and evaluate the optimum combination levels of wear process parameters. The results of Taguchi analysis indicate that sliding distance was found to be the prominent parameter affecting wear volume loss compared to other wear parameters.

The G-E composites with 3 and 6 vol.% of TKP had the lowest wear volume loss. Multiple linear regression models for all the tested composites’ results well match with experimental results. Confirmation tests were conducted to validate the analysis. There was a close relationship between the experimental results and the statistical model.

However, to the best of author’s knowledge, these literature reports related to natural organic filler materials are limited to analysis of polymer matrix composite. Further, the addition of TKP particle as a potential filler has not been addressed. An attempt has been made to clarify the technical viability of TKP as a potential filler for G-E composite.