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The paper describes the methods of manufacturing process optimization, using Taguchi experimental design methods with historical process data, collected during normal production.

The objectives are achieved with two separate techniques: the Retrospective Taguchi approach selects the designed experiment's data from a historical database, whilst in the Neural Network (NN) – Taguchi approach, this data is used to train a NN to estimate process response for the experimental settings. A case study illustrates both approaches, using real production data from an aerospace application.

Detailed results are presented. Both techniques identified the important factor settings to ensure the process was improved. The case study shows that these techniques can be used to gain process understanding and identify significant factors.

The most significant limitation of these techniques relates to process data availability and quality. Current databases were not designed for process improvement, resulting in potential difficulties for the Taguchi experimentation; where available data does not explain all the variability in process outcomes.

Manufacturers may use these techniques to optimise processes, without expensive and time‐consuming experimentation.

The paper describes novel approaches to data acquisition associated with Taguchi experimentation.

To highlight the application and to compare the effectiveness of the Taguchi and Shainin experimental design processes as applied to aerospace structural components.

This paper applies both the Taguchi and Shainin experimental design techniques to optimizing the design of honeycomb composite joints. The techniques are fully applied, the results analysed and their user friendliness is assessed.

This paper identifies an optimum parameter setting for composite joints gained from applying these experimental design techniques. Significant improvements in joint strength are achieved through identifying a new joint setting.

The adoption of the experimental design techniques outlined in this paper and their application to a real engineering problem will enable a company to apply the techniques and to attain improvements in terms of cost and quality.

The analysis of both the Taguchi and Shainin methodologies and the resulting conclusions as to their effectiveness for industry is the real value of this paper. This paper will be valuable for quality professionals, design engineers and manufacturing specialists in a wide range of industries.

Micro-EDM is an important process in the field of micro-machining. Especially, the μEDM is one of the technologies widely used for manufacture of micro-parts, micro-tools and micro-components, etc. The accuracy and repeatability of the μEDM process is still highly dependent on the μWEDG process. The electrode generation and regeneration is considered a key enabling technology for improving the performance of the μEDM process. Many engineers considered the Taguchi technique as engineering judgment during multiple response optimizations. This paper aims to focus on the use of micro-WEDG process to generate a micro-tool (electrode) with minimum surface roughness and higher metal removal rate (MRR).

In this research work, the Taguchi quality loss function analysis is used to examine and explain the influences of three process parameters (feed rate, capacitance and voltage) on the output responses such as MRR and surface roughness. Further, the optimized machining parameters were determined considering the multiple response objective using Taguchi multi-response signal-to-noise ratio.

Based on the experimental result, it was concluded that the Taguchi technique is suitable for the optimization of multi-response problem.

This paper presents an alternative approach using Taguchi's quality loss function. In most of the modern technological situations, more than one response variable is pertinent to the success of an industrial process. In this research work, the influence of feed rate, capacitance and voltage on the MRR and surface roughness (multiple responses) is investigated.

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.

The purpose of this paper is to propose a simple methodology in solving multi‐response optimisation problems by employing Taguchi methods and a non‐parametric statistical technique.

There is a continuous interest in developing effective and statistically sound multi‐response optimisation methods such that they will provide a firm framework in global product and process improvement. A non‐parametric approach is proposed for the first time in a five‐step methodology that exploits Taguchi's fractional factorial designs and the concept of signal‐to‐noise ratio in data consolidation. The distinct feature of this method is the transformation of each response variable to a single rank variable. The subsequent incorporation of the squared ranks for each of the investigated responses issues a single master‐rank response suitably referred to conveniently as a “Super Rank” (SR) response, thus collapsing all dependent product characteristic information into a single non‐dimensional variable. This SR variable is handled by standard non‐parametric methods such as Wilcoxon's two‐sample, rank sum test or Mann‐Whitney's test eliminating at the same time multi‐distribution effects and small‐sample complications expected for this type of experimentation.

The proposed methodology is tested on already published data pertaining a design problem in the electronic assembly technology field. The case study requires six‐factor simultaneous optimisation of three response variables. A second example is analyzed by the proposed method focusing on the optimisation of a submerged arc‐welding process problem due to a group of five factors. The Mann‐Whitney's test contrasts the effects of factor settings one‐to‐one on the SR response in order to assign statistical significance to the optimal factor settings.

The application of this methodology is tested at the same time in a real three‐response optimisation case study where each response belongs to different optimisation category.

The methodology outlined in this work eliminates the need for sophisticated multi‐response data handling. In addition, small‐sample considerations and multi‐distribution effects that may be inherent do not restrict the applicability of the method presented herein by this type of experimentation.

This investigation provides a new angle to the published methods of multi‐response optimisation by supporting Taguchi's design of experiments methods through a multi‐ranking scheme that leads to non‐parametric factor resolution.

Dr Taguchi is a Japanese engineer and an international quality consultant who has made breakthrough improvements in product and process quality through the use of statistical design of experiments (SDOE). The Taguchi method became popular in the West in the 1980s as a means to design robust products and processes. Although many companies and industries have used the method with success, the real benefits of the approach were not realised and fully understood in many cases. This lack of success could be attributed to a number of factors, but mainly because the experiments were treated in isolation and not integrated into a continuous improvement strategy. This paper briefly presents the results of the application of the Taguchi methodology in the UK industry. The paper also illustrates the application of the Taguchi method for optimising the production process of retaining a metal ring in a plastic body in a braking system.

This paper aims to report the effect of titanium oxide (TiO₂) particles on the specific wear rate (SWR) of alkaline treated bamboo and flax fiber-reinforced composites (FRCs) under dry sliding condition by using a robust statistical method.

In this research, the epoxy/bamboo and epoxy/flax composites filled with 0–8 Wt.% TiO₂ particles have been fabricated using simple hand layup techniques, and wear testing of the composite was done in accordance with the ASTM G99-05 standard. The Taguchi design of experiments (DOE) was used to conduct a statistical analysis of experimental wear results. An analysis of variance (ANOVA) was conducted to identify significant control factors affecting SWR under dry sliding conditions. Taguchi prediction model is also developed to verify the correlation between the test parameters and performance output.

The research study reveals that TiO₂ filler particles in the epoxy/bamboo and epoxy/flax composite will improve the tribological properties of the developed composites. Statistical analysis of SWR concludes that normal load is the most influencing factor, followed by sliding distance, Wt.% TiO2 filler and sliding velocity. ANOVA concludes that normal load has the maximum effect of 31.92% and 35.77% and Wt.% of TiO2 filler has the effect of 17.33% and 16.98%, respectively, on the SWR of bamboo and flax FRCs. A fairly good agreement between the Taguchi predictive model and experimental results is obtained.

This research paper attempts to include both TiO₂ filler and bamboo/flax fibers to develop a novel hybrid composite material. TiO₂ micro and nanoparticles are promising filler materials, it helps to enhance the mechanical and tribological properties of the epoxy composites. Taguchi DOE and ANOVA used for statistical analysis serve as guidelines for academicians and practitioners on how to best optimize the control variable with particular reference to natural FRCs.

The field of quality has undergone significant changes as reflected by changes in its definition, paradigms, approaches, techniques, and scope of application. This paper reviews emerging trends and issues focusing on quality engineering. Changes in customer expectation have driven the changes in the technology of design and manufacturing, which is becoming more important in satisfying individual customer expectations. This also calls for special attention to the engineering aspects of quality. Brief reviews on recent advances in the prominent quality tools such as statistical process control, quality function deployment, and design of experiment are reported. General trends in quality engineering research show the tools are being enhanced, integrated, computerized and broaden their application bases, where possible opportunities for further investigation are indicated. Among others these include contributions in multiple‐response optimization, intelligent quality systems, multivariate SPC, and practical and simple guidelines for actual implementation of various tools.

Reviews the global status of total quality management (TQM). Emphasizes continuous quality improvement as one of the main pillars of TQM. Illustrates a part of the research that was carried out to examine Taguchi′s on‐line quality control (TOLQC) methods as the means to effect continuous quality improve‐ment. Describes a case study that was carried out to study the implementation feasibilities of TOLQC methods. Highlights the inferences drawn from this case study which assert the need for managerial approach rather than mere technical computations for successful implementation. Insists on intensified training and awareness programmes on the implementation strategies of these methods to attain the ultimate goals of TQM.

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.