Mixture analysis of organic solvents using nonselective and nonlinear Taguchi gas sensors with artificial neural networks
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In the manufacturing industry, to produce the best quality product, it is important to define several levels of inputs. The Taguchi method is proposed for the solution of this problem and is widely used. In this study, a steady-state genetic algorithm (GA), called Genmak, is developed for the solution of the experimental design problems. In order to compare the performance of the suggested algorithm with that of the Taguchi method, 3 sets with different characteristics are carefully designed. Each set has 1000 test problems. Each of these test problems is an experimental design problem having 4 factors with 3 levels. Significant effects and optimum solution are determinated by statistical methods for every problem generated. Two methods are applied to the problems and the number of problems in which the optimum solution is reached is recorded. Then, the methods are compared with respect to these records. The results show that the performance of the GA is as high as that of the Taguchi method. Another important result is that the performance of the methods decreases as the amount of interaction in a problem increases. Overall, it is concluded that GAs are suitable for finding the optimum solution to this kind of problem and can be used as an alternative to the Taguchi method.
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Taguchi method is a technique widely used in industries to attain a reliable quality even under existence of various noise variables. Basically, it relies on the interactions between the controllable and the noise factors. Under insignificant interactions between the design parameters and noises, the effectiveness of Taguchi methodology will be doubtful. Furthermore, existence of strong interactions among controllable factors may undermine the power of Taguchi approach. An abundant crop may be expected by a well planned Taguchi approach. A well designed set of experiments is one of the important prerequisites for its successful result. For this, we must have a clear understanding on strengths and weaknesses of Taguchi methodology together with a sound knowledge on the applicable system. This study provides some insights on Taguchi approach based on two case examples of one successful and the other unsuccessful. Eventually, this research aims to facilitate deeper understanding and right application of Taguchi methodology in industries.
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This paper presents the implementation of the Taguchi method for a retrofit design of a line-start permanent magnet motor. To evaluate the viability of the method, the optimum designs obtained from both the Taguchi and a traditional optimization methods are compared. This outlines the respective advantages and disadvantages of both methods. It shows that the Taguchi method is an efficient and robust design approach and possesses some unique advantages compared to conventional design methods. A design sensitivity investigation regarding the variances of certain parameters, due to manufacturing tolerances and material properties discrepancies, is also presented using the Taguchi method. From this investigation insight into the contribution of each parameter towards machine performance is gained for the steady-state performance of an embedded radial flux line-start permanent magnet motor.
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In this paper, the bursting strength of knitted fabrics was optimised using the Taguchi experiment design technique, which is a recently famous approach. In the evaluations, analyses of variance (ANOVA) and the signal to noise ratio were used. 9 experiments were performed with respect to the L9 orthogonal design for the Taguchi approach. The results show a considerable improvement in the S/N ratio as compared to the initial condition. With the Taguchi processes, we can easily determine optimum conditions for maximising the bursting strength of knitted fabrics with simple experiments.
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Taguchi defined a good quality as ‘A correspondence of product characteristic’s expected value to the objective value satisfying the minimum variance condition.’ For his good quality, he suggested Taguchi Method which is called Robust design which is irrelevant to the effect of these noise factors. Taguchi Method which has many success examples and which is used by many manufacturing industry. But Opti-mal solution of Taguchi Method is one among the experiments which is not optimal area of experiment point.On the other hand, Response Surface Method (RSM) which has advantage to find optimal solution area experiments points by approximate polynomial regression. But Optimal of RSM is depended on initial point and RSM can not use many factors because of a great many experiment. In this paper, we combine the Taguchi Method and the Response Surface Method with each advantage which is called Taguchi-RSM. Taguchi-RSM has two step, first step to find first solution by Taguchi Method, second step to find optimal solution by RSM with initial point as first step solution. We give example using catapults.
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Abstract The methods of Taguchi have received considerable attention in recent years. Part of the attention is due to the success of Genichi Taguchi and his colleagues and part of the attention is due to the mystique and controversy surrounding these methods. In this paper we discuss two separate aspects of the Taguchi method: the strategy of Taguchi and the tactics of Taguchi. The Taguchi tactics involve the specific methods and techniques recommended by Taguchi such as the use of signal-to-noise ratios and the so-called Taguchi designs. We discuss the parameter design strategy of Taguchi for designing and improving products and processes from a statistical point of view. We point out that although there are some apparent flaws in Taguchi's tactics, the basic strategy is a sound one.
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This article provides a brief explanation of the method developed by Genichi Taguchi and used by the Japanese to manufacture superior products. Taguchi's definition of quality and several concepts characteristic of his method are presented. A detailed explanation of Taguchi's experimental design process and an example of such an experiment are included.
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Бұл зерттеужұмысындaКaно моделітурaлы жәнеоғaн қaтыстытолықмәліметберілгенжәнеуниверситетстуденттерінебaғыттaлғaн қолдaнбaлы (кейстік)зерттеужүргізілген.АхметЯссaуи университетініңстуденттеріүшін Кaно моделіқолдaнылғaн, олaрдың жоғaры білімберусaпaсынa қоятынмaңыздытaлaптaры, яғнисaпaлық қaжеттіліктері,олaрдың мaңыздылығытурaлы жәнесaпaлық қaжеттіліктерінеқaтыстыөз университетінқaлaй бaғaлaйтындығытурaлы сұрaқтaр қойылғaн. Осы зерттеудіңмaқсaты АхметЯсaуи университетіндетуризмменеджментіжәнеқaржы бaкaлaвриaт бaғдaрлaмaлaрыныңсaпaсынa қaтыстыстуденттердіңқaжеттіліктерінaнықтaу, студенттердіңқaнaғaттaну, қaнaғaттaнбaу дәрежелерінбелгілеу,білімберусaпaсын aнықтaу мен жетілдіружолдaрын тaлдaу болыптaбылaды. Осы мaқсaтқaжетуүшін, ең aлдыменКaно сaуaлнaмaсы түзіліп,116 студенткеқолдaнылдыжәнебілімберугежәнеоның сaпaсынa қaтыстыстуденттердіңтaлaптaры мен қaжеттіліктерітоптықжұмыстaрaрқылыaнықтaлды. Екіншіден,бұл aнықтaлғaн тaлaптaр мен қaжеттіліктерКaно бaғaлaу кестесіменжіктелді.Осылaйшa, сaпa тaлaптaры төрт сaнaтқa бөлінді:болуытиіс, бір өлшемді,тaртымдыжәнебейтaрaп.Соңындa,қaнaғaттaну мен қaнaғaттaнбaудың мәндеріесептелдіжәнестуденттердіңқaнaғaттaну мен қaнaғaттaнбaу деңгейлерінжоғaрылaту мен төмендетудеосытaлaптaр мен қaжеттіліктердіңрөліaйқын aнықтaлды.Түйінсөздер:сaпa, сaпaлық қaжеттіліктер,білімберусaпaсы, Кaно моделі.
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