Prediction of Process Parameters of Ultrasonically Welded PC/ABS Material Using Soft-Computing Techniques

This paper presents an overview of research works on the utilizing of soft computing in the optimization of process parameters and in the prediction of thin film properties in sputtering processes. The papers from this review were obtained from relevant databases and from various scientific journals. The papers collected were published from 2008 to 2012. The focus of the review is to provide an outlook on the utilization of soft computing techniques in sputtering processes. Based on the review, the soft computing techniques which have been applied so far are ANN, GA and Fuzzy Logic. The first finding of this review is that soft computing technique is a promising and more reliable approach to optimize and predict process parameters compared to the traditional methods. The second finding is that the utilizing of soft computing techniques in sputtering processes are still limited and still in exploratory phase as they have not yet been extensively and stably applied. The techniques applied are also limited to ANN, GA and Fuzzy, whereas the exploration into other techniques is also necessary to be conducted in order to seek the most reliable technique and so as to expand the application of soft computing approach. Future research could focus on the exploration of other soft computing techniques for optimization in order to find the best optimization techniques based on the specific processes.

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Optimization of friction stir welding process parameters using soft computing techniques

Soft Computing ◽

10.1007/s00500-016-2251-6 ◽

2016 ◽

Vol 21 (23) ◽

pp. 7083-7098 ◽

Cited By ~ 6

Author(s):

Nizar Faisal Alkayem ◽

Biswajit Parida ◽

Sukhomay Pal

Keyword(s):

Friction Stir Welding ◽

Soft Computing ◽

Process Parameters ◽

Welding Process ◽

Friction Stir ◽

Friction Stir Welding Process ◽

Soft Computing Techniques

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Soft computing model for analysing the effect of friction stir processing parameters on the intergranular corrosion susceptibility of aluminium alloy AA5083

Koroze a ochrana materialu ◽

10.1515/kom-2018-0014 ◽

2018 ◽

Vol 62 (3) ◽

pp. 97-107 ◽

Cited By ~ 3

Author(s):

R. Vaira Vignesh ◽

R. Padmanaban ◽

Chinnaraj K.

Keyword(s):

Mass Loss ◽

Aluminium Alloy ◽

Soft Computing ◽

Process Parameters ◽

Friction Stir Processing ◽

Fuzzy System ◽

Intergranular Corrosion ◽

Friction Stir ◽

Soft Computing Techniques ◽

Corrosion Susceptibility

Abstract Aluminium alloy AA5083 is prone to intergranular corrosion in marine environments. In an attempt to reduce the intergranular corrosion, AA5083 was subjected to friction stir processing (FSP). The FSP experimental trials were conducted as per face-centered central composite design with three levels of variation in FSP process parameters viz. tool rotation speed (TRS), tool traverse speed (TTS) and tool shoulder diameter (SD). Intergranular corrosion susceptibility of the processed specimens was assessed by performing nitric acid mass loss test. The mass loss of the specimens was correlated with the intergranular corrosion susceptibility as per the standard ASTM G67-13. The experimental results indicate that FSP had significantly reduced the intergranular corrosion susceptibility of the AA5083 alloy. Soft computing techniques namely Artificial Neural Network, Mamdani Fuzzy system, and Sugeno Fuzzy system were used to predict the intergranular corrosion (IGC) susceptibility (mass loss) of the friction stir processed specimens. Among the developed models, Sugeno fuzzy system displayed minimum percentage error in prediction. So Sugeno fuzzy system was used to analyze the effect of friction stir processing process parameters on the IGC of the processed specimens. The results suggest that stir processing of AA5083 at a TRS of 1300 rpm, TTS of 60 mm/min and SD of 21 mm would make the alloy least susceptible to intergranular corrosion.

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