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1 – 10 of over 1000
Article
Publication date: 25 September 2009

Humberto Hijar‐Rivera and Victor Garcia‐Castellanos

The purpose of this paper is to present computer‐generated combined arrays as efficient alternatives to Taguchi's crossed arrays to solve robust parameter problems.

Abstract

Purpose

The purpose of this paper is to present computer‐generated combined arrays as efficient alternatives to Taguchi's crossed arrays to solve robust parameter problems.

Design/methodology/approach

The alternative combined array designs were developed for the cases including six to twelve variables where CMR designs are not smaller than Taguchi's designs. The efficiency to estimate the effects of interest was calculated and compared to the efficiency of the corresponding CMR designs.

Findings

For all the cases investigated at least one computer generated combined array design was found with the same size as the CMR design and with higher efficiency.

Practical implications

Robust parameter design identifies appropriate levels of controllable variables in a process for the manufacturing of a product. The designed experiments involve the controllable variables along with the uncontrollable or noise variables to design a product or process that will be robust to changes in these noise variables. Response surface methodology estimates the actual relationship between the response and the input variables with an empirical model based on the designed experiment. Once the empirical model is fitted, the surface described by the model can be used to describe the behavior of the response over the experimental region. The higher efficiency of the computer generated combined array designs proposed in this research produces lower variances for the parameter estimates and lower variance of prediction for the model. As a result, the response will be described in a more realistic form.

Originality/value

The paper shows that using a computer‐generated design to solve a robust parameter problem will result in a better approximation to the true response of the process. Consequently, optimizing the fitted model will produce settings for the parameters closer to the real optimal settings.

Details

Journal of Quality in Maintenance Engineering, vol. 15 no. 4
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 1 July 2004

Jiju Antony, V. Somasundarum, Craig Fergusson and Pavel Blecharz

Dr Genichi Taguchi is a Japanese engineer and quality consultant who has promoted the use of statistical design of experiments for improving process/product quality at minimal…

1572

Abstract

Dr Genichi Taguchi is a Japanese engineer and quality consultant who has promoted the use of statistical design of experiments for improving process/product quality at minimal costs. Taguchi has developed a practical and strategic approach for designing quality into products and processes at the product planning, design and development stages, which is often referred to as off‐line quality control. Although many companies in Europe and the USA have used the Taguchi approach to statistical design of experiments with success, very few applications of this method are realised in countries such as the Czech Republic. This paper reports the applications of experimental design advocated by Taguchi in two manufacturing companies in the Czech Republic. The results of the study are stimulating and will lead to wider applications of this methodology for tackling process and quality‐related problems in the Czech Republican industries in the near future.

Details

International Journal of Productivity and Performance Management, vol. 53 no. 5
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 22 May 2009

Ibrahim A. Al‐Darrab, Zahid A. Khan, Mohamed A. Zytoon and Sheikh I. Ishrat

The purpose of this paper is to demonstrate application of the Taguchi method to determine the optimum level of three important parameters (factors) related to the use of a mobile…

Abstract

Purpose

The purpose of this paper is to demonstrate application of the Taguchi method to determine the optimum level of three important parameters (factors) related to the use of a mobile phone for the text message entering task, namely illumination level, noise level and mobile angle that maximizes the performance of mobile phone users.

Design/methodology/approach

Three levels of each parameter as available in the literature, except for the mobile angle, were considered. The design of the experiment, as proposed by Genichi Taguchi, was used to conduct nine experiments. A total of 30 male subjects participated in the experimental study. The text message entry task, in the form of Arabic text, was presented to the participating subjects and their performance, measured in terms of mean number of characters entered per minute, was recorded. The signal‐to‐noise (S/N) ratio and the analysis of variance (ANOVA) were employed to investigate the users' performance. Finally, a confirmation test was conducted to verify the validity of the results.

Findings

Results showed that, at the illumination level of 475 lux, noise level of 45 dB(A), and mobile angle of 70 degrees, the subjects were quite comfortable, efficient and entered the maximum number of characters in the mobile phone per minute. The noise was found to be the dominant parameter with a contribution of 95.53 percent towards the laid down objective followed by mobile angle, 3.25 percent and illumination level, 0.66 percent.

Originality/value

To the best of the authors' knowledge no study has been conducted in the past to investigate the effect of these parameters on the performance of the mobile phone users. In addition, no attempt has yet been made to find the optimal level of these parameters from a text‐entering viewpoint. The paper represents original research and in the authors' opinion carries significantly important values as it provides new information for those involved in the design of the mobile phone environment.

Details

International Journal of Quality & Reliability Management, vol. 26 no. 5
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 1 January 2006

Jiju Antony, Daniel Perry, Chengbo Wang and Maneesh Kumar

This paper aims to illustrate an application of Taguchi method of experimental design (TMED) for the development of a new ignition coil for an automotive vehicle.

3011

Abstract

Purpose

This paper aims to illustrate an application of Taguchi method of experimental design (TMED) for the development of a new ignition coil for an automotive vehicle.

Design/methodology/approach

The application of TMED for optimisation of manufacturing processes has been widely published in the existing literature. However, the applications of TMED in the design and development of new products are not yet widely reported. This case study presents the results of a designed experiment which utilises a 16‐trial experiment to study 14 design parameters and one interaction. The case study strictly follows a systematic and disciplined methodology outlined in the paper.

Findings

The optimal settings of the critical design parameters are determined. The optimal settings have resulted in increased customer satisfaction, improved market share and low defect rate in the hands of customers.

Research limitations/implications

Although the optimal levels are determined from one large experiment, it was unable to determine the true optimal values of each design parameter.

Practical implications

Manufacturers may use TMED to optimise processes (either design or manufacturing) without expensive and time‐consuming experimentation. This case study demonstrates the true power of a well planned and designed experiment over the traditional varying one‐factor‐at‐a‐time approach to experimentation which is rather unreliable, not cost‐effective and may lead to false optimal conditions.

Originality/value

The paper provides an excellent resource for those people who are involved in the design optimisation of a new product.

Details

Assembly Automation, vol. 26 no. 1
Type: Research Article
ISSN: 0144-5154

Keywords

Article
Publication date: 7 July 2023

Vinayambika S. Bhat, Thirunavukkarasu Indiran, Shanmuga Priya Selvanathan and Shreeranga Bhat

The purpose of this paper is to propose and validate a robust industrial control system. The aim is to design a Multivariable Proportional Integral controller that accommodates…

92

Abstract

Purpose

The purpose of this paper is to propose and validate a robust industrial control system. The aim is to design a Multivariable Proportional Integral controller that accommodates multiple responses while considering the process's control and noise parameters. In addition, this paper intended to develop a multidisciplinary approach by combining computational science, control engineering and statistical methodologies to ensure a resilient process with the best use of available resources.

Design/methodology/approach

Taguchi's robust design methodology and multi-response optimisation approaches are adopted to meet the research aims. Two-Input-Two-Output transfer function model of the distillation column system is investigated. In designing the control system, the Steady State Gain Matrix and process factors such as time constant (t) and time delay (?) are also used. The unique methodology is implemented and validated using the pilot plant's distillation column. To determine the robustness of the proposed control system, a simulation study, statistical analysis and real-time experimentation are conducted. In addition, the outcomes are compared to different control algorithms.

Findings

Research indicates that integral control parameters (Ki) affect outputs substantially more than proportional control parameters (Kp). The results of this paper show that control and noise parameters must be considered to make the control system robust. In addition, Taguchi's approach, in conjunction with multi-response optimisation, ensures robust controller design with optimal use of resources. Eventually, this research shows that the best outcomes for all the performance indices are achieved when Kp11 = 1.6859, Kp12 = −2.061, Kp21 = 3.1846, Kp22 = −1.2176, Ki11 = 1.0628, Ki12 = −1.2989, Ki21 = 2.454 and Ki22 = −0.7676.

Originality/value

This paper provides a step-by-step strategy for designing and validating a multi-response control system that accommodates controllable and uncontrollable parameters (noise parameters). The methodology can be used in any industrial Multi-Input-Multi-Output system to ensure process robustness. In addition, this paper proposes a multidisciplinary approach to industrial controller design that academics and industry can refine and improve.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

Keywords

Article
Publication date: 2 November 2012

Matloub Hussain, Paul R. Drake and Dong Myung Lee

The purpose of this paper is to quantify the effect of design parameters on the bullwhip effect and dynamic responses produced by a multi‐echelon supply chain with information…

2099

Abstract

Purpose

The purpose of this paper is to quantify the effect of design parameters on the bullwhip effect and dynamic responses produced by a multi‐echelon supply chain with information sharing.

Design/methodology/approach

Taguchi design of experiments and system dynamics simulation are used to quantify the impact of a supply chain's design parameters, including degree of information sharing, on its dynamic performance, and the interactions that occur as the parameter values are varied.

Findings

Quantified relationships between supply chain design parameters and dynamic performance, including the bullwhip effect, are presented. Two parameters in particular, time to adjust inventory error and production lead time, are shown to have a particularly strong impact on the order variance compared to other parameters. However, there are several other significant findings.

Research limitations/implications

Batching and capacity constraints are common causes of the bullwhip effect, but they are not included here. Future work should quantify the impact of these.

Practical implications

This paper presents a systematic way for quantifying and understanding the impact of supply chain design parameters on the bullwhip effect and dynamic responses, and their interactions. The experimental results provide practical understanding for supply chain managers.

Originality/value

Previous studies have identified causes of the bullwhip effect but little attention has been given to quantifying their impact and interactions. This paper makes a contribution towards filling this gap, using system dynamics simulation and Taguchi design of experiments.

Details

International Journal of Physical Distribution & Logistics Management, vol. 42 no. 10
Type: Research Article
ISSN: 0960-0035

Keywords

Article
Publication date: 3 July 2007

Namwoo Kang, Junyoung Kim and Yongtae Park

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…

1777

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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

Practical implications

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.

Originality/value

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.

Details

Industrial Management & Data Systems, vol. 107 no. 6
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 24 August 2010

Amitava Ray, Bijan Sarkar and Subir Kumar Sanyal

Cost estimation based on expert's judgment is not an ideal approach, since human decisions are usually determined according to general attributes of limited and unstructured…

1993

Abstract

Purpose

Cost estimation based on expert's judgment is not an ideal approach, since human decisions are usually determined according to general attributes of limited and unstructured experience. The purpose of this paper is to develop a generic model of intelligence and cognitive science‐based method that can play an active role in process cost prediction within the shortest possible time.

Design/methodology/approach

In this paper, an intelligent system was conceived for prediction of total process cost of the product. The system is based on the concept of case‐based reasoning. It is a method for solving problems by making use of previous (source cases), similar situations and reusing information and knowledge about such situations. The source case data are generated by Taguchi technique and the cost function calculates the corresponding cost of each experiment in the economic time scale. The target case consists of the process variables whose cost needs to be determined. The cost for the source cases, consisting of the process variables of the already manufactured products are known in priori. The system calculates the similarities between the source cases and target cases and calculates the optimum cost. The fuzzy‐C‐means clustering method provides the model connecting the process parameters with total costs searched for.

Findings

The results show that the quality of predictions made by the intelligent system is comparable to the quality assured by the experienced expert. The proposed expert system is superior to traditional cost accounting system and assists inexperienced users in predicting the optimum process cost within the shortest possible time.

Research limitations/implications

The research was limited to the traditional machining process.

Practical implications

The paper can be applied to any process industry and will have immense practical value.

Originality/value

This is the first time an expert system has been developed for the process industry that can calculate the process cost within a few days or a few hours before making an offer to a buyer.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 3 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 1 February 2006

Hari Singh and Pradeep Kumar

Taguchi's technique is best suited to optimize a single performance characteristic yielding an optimal setting of process parameters. A single setting of process parameters may be…

1744

Abstract

Purpose

Taguchi's technique is best suited to optimize a single performance characteristic yielding an optimal setting of process parameters. A single setting of process parameters may be optimal for one quality characteristics but the same setting may yield detrimental results for other quality features. Thus the purpose of this paper is to describe simultaneous optimization of multi‐characteristics.

Design/methodology/approach

The multi‐machining characteristics have been optimized simultaneously using Taguchi's parameter design approach and the utility concept. The paper used a single performance index, utility value, as a combined response indicator of several responses.

Findings

A simplified model based on Taguchi's approach and utility concept is used to determine the optimal settings of the process parameters for a multi‐characteristic product. The model is used to predict optimal settings of turning process parameters to yield the optimum quality characteristics of En24 steel turned parts using TiC coated carbide inserts. The optimal values obtained using the multi‐characteristic optimization model have been validated by confirmation experiments. The model can be extended to any number of quality characteristics provided proper utility scales for the characteristics are available from the realistic data.

Practical implications

The proposed methodology can be applied to those industrial situations where a number of responses are to be optimized simultaneously.

Originality/value

The paper discusses a case study on En24 steel turned parts using titanium carbide coated tungsten carbide inserts. The material, En24 steel, has wide applications in aerospace, machine tools, automobiles, etc. The proposed algorithm is easy to apply.

Details

Journal of Manufacturing Technology Management, vol. 17 no. 2
Type: Research Article
ISSN: 1741-038X

Keywords

Article
Publication date: 16 April 2020

Alagappan K M, Vijayaraghavan S, Jenarthanan M P and Giridharan R

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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

Details

Multidiscipline Modeling in Materials and Structures, vol. 16 no. 5
Type: Research Article
ISSN: 1573-6105

Keywords

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