The Use of Fuzzy Logic in the Taguchi Method for the Optimisation of the Submerged Arc Welding Process

Tarng, Y.S.; Yang, Wen-Hsi; Juang, S. C.

doi:10.1007/s001700070040

Cited by 113 publications

(62 citation statements)

References 6 publications

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“…In this regard, the proper adjustment of input parameters is an unavoidable necessity in order to achieve the welding with desired geometric properties due to the vastness and variety of involved parameters. The experimental methods based on the trial and error were usually used in the past in order to determine the optimal levels of adjusting parameters, but in recent years, the theoretical approaches such as statistical methods, response levels, approaches for designing the experiments and neural network have been considered [13]. Since that compared with other methods, using the regression analysis and artificial neural network lead to the models, which generally resulted in more accurate findings, are more cost-effective and precise despite obtaining from a small number of experimental tests, predicting the weld bead geometry by the mentioned methods has become an active field for research.…”

Section: Review Of Traditional Methodsmentioning

confidence: 99%

Weld Quality Prediction Using Artificial Intelligence Technique

Ojha¹,

Yadav²,

Yadav

2014

SMSJ

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Section: Review Of Traditional Methodsmentioning

confidence: 99%

Weld Quality Prediction Using Artificial Intelligence Technique

Ojha¹,

Yadav²,

Yadav

2014

SMSJ

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“…However, conventional Taguchi method can only find the optimal parameters based on a single performance characteristic. Hence, the fuzzy logic is combined with Taguchi method in this study to optimize the parameters [29,30]. In fuzzy-based Taguchi method, several fuzzy rules will be derived based on the performance requirement of the system.…”

Section: Fuzzy-based Taguchi Methods With Mpcimentioning

confidence: 99%

“…By using orthogonal arrays (OAs), the Taguchi method can search in the parameter space with a reduced number of experiments [18,28]. Since the aim of this study is to develop an intelligent charger with short charging time, high charging efficiency and low temperature increment; therefore, the optimization can be regarded as a multiple performance characteristic index (MPCI) problem [29,30]. To solve this kind of problem, fuzzy logic is combined with Taguchi method to obtain the optimal output MF of the proposed FLC-based battery charger.…”

Section: Introductionmentioning

confidence: 99%

Optimization of a Fuzzy-Logic-Control-Based Five-Stage Battery Charger Using a Fuzzy-Based Taguchi Method

et al. 2013

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Lithium ion (Li-ion) batteries have been widely used in various kinds of applications, including consumer electronics, green energy systems and electrical vehicles. Since the charging method has a significant influence on the performance and lifetime of Li-ion batteries, an intelligent charging algorithm which can properly determine the charging current is essential. In this study, a fuzzy-logic-control-based (FLC-based) five-stage Li-ion battery charger is proposed. The proposed charger takes the temperature rise and the gradient of temperature rise of battery into account, and adjusts the charging current accordingly. To further improve the performance of the proposed FLC, the fuzzy-based Taguchi method is utilized to determine the optimal output membership functions (MFs). Comparing with the conventional constant current-constant voltage (CC-CV) method, the charging time, charging efficiency, average temperature rise and the obtained cycle life of the Li-ion battery are improved by about 58.3%, 1.65%, 26.7% and 59.3%, respectively.

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“…Tarng and Yang [17] reported on the optimization of weld bead geometry in GTAW by using the Taguchi method. Tarng et al [18] applied the modified Taguchi method to determine the process parameters for optimum weld pool geometry in TIG welding of stainless steel. Tarng et al [19] also worked on the use of grey-based Taguchi method to determine optimum process parameters for submerged arc welding (SAW) in hard facing with consideration of multiple weld qualities.…”

Section: Introductionmentioning

confidence: 99%

Parametric optimization of MIG welding on 316L austenitic stainless steel by Taguchi method

Ghosh¹,

Pal²,

Nandi³

2016

Archives of Materials Science and Engineering

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Purpose: Taguchi design has been adopted in order to identify optimal parametric combination for desired quality of weld. Design/methodology/approach: A plan of experiments based on Taguchi technique has been used. An orthogonal array, signal to noise (S/N) ratio and analysis of variance (ANOVA) are employed to study the welding characteristics of material & optimize the welding parameters. Findings: The welding investigators have always been in search for better quality of weldment. In present work, effect of current, gas flow rate and nozzle to plate distance on quality of weld in metal gas arc welding of Austenitic stainless steel AISI 316L has been studied through experiment and analyses. Butt welded joints have been made by several levels of current, gas flow rate and nozzle to plate distance. The result computed is in form of contribution from each parameter, through which optimal parameters are identified for maximum tensile strength and percentage elongation. Research limitations/implications: The main objective of the present study was to apply the Taguchi method to establish the optimal set of control parameters for the welding. The Taguchi method is employed to determine the optimal combination of design parameters, including: current, gas flow rate and nozzle to plate distance. Practical implications: Weld quality mainly depends on features of bead geometry, mechanical-metallurgical characteristics of the weld as well as on various aspects of weld chemistry and these features are expected to be greatly influenced by various input parameters like current, voltage, electrode stick-out, gas flow rate, edge preparation, position of welding, welding speed and many more in metal inert gas (MIG) welding. Moreover, the cumulative effect of the mentioned quality indices determines the extent of joint strength that should meet the functional aspects of the weld in practical field of application. Therefore, preparation of a satisfactory good quality weld seems to be a challenging job. Originality/value: The result computed is in form of contribution from each parameter, through which optimal parameters are identified for maximum tensile strength and percentage elongation. This paper presents new results of optimization using Taguchi method.

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The Use of Fuzzy Logic in the Taguchi Method for the Optimisation of the Submerged Arc Welding Process

Cited by 113 publications

References 6 publications

Weld Quality Prediction Using Artificial Intelligence Technique

Weld Quality Prediction Using Artificial Intelligence Technique

Optimization of a Fuzzy-Logic-Control-Based Five-Stage Battery Charger Using a Fuzzy-Based Taguchi Method

Parametric optimization of MIG welding on 316L austenitic stainless steel by Taguchi method

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