Optimization of the friction-stir-welding process and tool parameters to attain a maximum tensile strength of AA7075

Abstract

High-strength, precipitation-hardening AA7075 alloy is used extensively in aircraft primary structures. The friction-stir-welding (FSW) process is an emerging solid-state joining process in which the material that is being welded does not melt and recast. The FSW process and tool parameters play a major role in deciding the joint strength. In this paper an attempt has been made to establish an empirical relationship between the FSW process and tool parameters (tool rotational speed, welding speed, axial force, shoulder diameter, pin diameter, and tool material hardness) and the tensile strength of the joint. Statistical tools such as design of experiments, analysis of variance, and regression analysis are used to develop the relationships. The developed empirical relationship can be effectively used to predict the tensile strength of FSW joints at the 95 per cent confidence level. A sensitivity analysis is also carried out and compared with the relative impact of input parameters on tensile strength in order to verify the measurement errors on the values of the uncertainty in estimated parameters.

Keywords

friction stir welding design of experiments analysis of variance response surface methodology sensitivity analysis optimization

References

Thomas

W. M.

Nicholas

E. D.

Needham

J. C.

Murch

M. G.

Temple-Smith

Dawes

C. J.

. Friction stir butt welding (The Welding Institute (TWI)). PCT World Patent Application WO 93/10935; field: 27 November 1992 (UK 9125978.8, 6 December 1991); publication: 10 June 1993.

J.-Q.

Nelson

T. W.

Mishra

R. S.

Mahoney

. Microstructural investigation of friction stir welded 7050-T651 aluminium. Acta Materialia 51 (2003): 713–729.

Grum

Slabe

J. M.

. The use of factorial design and response surface methodology for fast determination of optimal heat treatment conditions of different Ni—Co—Mo surfaced layers. J. Mater. Process Technol. 155 (2004): 2026–2032.

Gunaraj

Murugan

. Application of response surface methodology for predicting weld bead quality in submerged arc welding of pipes. J. Mater. Process Technol. 88 (1999): 266–275.

Manonmani

Murugan

Buvanasekaran

. Effect of process parameters on the weld bead geometry of laser beam welded stainless steel sheets. J. Joining Mater. 17 (4) (2005): 103–109.

Balasubramanian

Jayabalan

Balasubramanian

. Developing mathematical models to predict tensile properties of pulsed current gas tungsten arc welded Ti—6Al—4V alloy. Mater. Des. 29 (1) (2008): 92–97.

Palani

P. K.

Murugan

. Optimization of weld bead geometry for stainless steel claddings deposited by FCAW. J. Mater. Process Technol. 190 (2007): 291–299.

Karaoglua

Secgin

. Sensitivity analysis of submerged arc welding process parameters. J. Mater. Process Technol. 202 (2007): 500–507.

Kim

I. S.

Son

K. J.

Yang

Y. S.

Yaragada

P. K. D. V.

. Sensitivity analysis for process parameters in GMA welding processes using a factorial design method. J. Mach. Tools Mf. 43 (2003): 763–769.

10.

Gunaraj

Murugan

. Prediction and optimization of weld bead volume for the submerged arc process. Part 2. Weld. J. 79 (11) (2000): 331–338.

11.

Elangovan

Balasubramanian

. Influences of tool pin profile and tool shoulder diameter on the formation of friction stir processing zone in AA6061 aluminium alloy. Mater. Des. 29 (2008): 362–373.

12.

Elangovan

Balasubramanian

Babu

. Predicting tensile strength of friction stir welded AA6061 aluminium alloy joints by a mathematical model. Mater. Des. 30 (2009): 188–193.

13.

Cochran

W.G.

Cox

G.M.

. Experimental designs (London: John Wiley 1957).

14.

Kumar

Shan

H. S.

. Effect of evaporative pattern casting process parameters on the surface roughness of Al—7% Si alloy castings. J. Mater. Processing Technol. 182 (2007): 615–623.

15.

Hou

T. H.

C. H.

Liu

W. L.

. Parameter optimization of a nano-particle wet milling process using the Taguchi method, response surface method and genetic algorithm. J. Powder Technol. 173 (2007): 153–162.

16.

Johnson

N. L.

Leone

F. C.

. Statistics and experimental design in engineering and physical sciences (New York: John Wiley 1964).

17.

Box

G. E. P.

Hunter

W. H.

Hunter

J. S.

. Statistics for experimenters (New York: John Wiley 1978).

18.

Montgomery

D. C.

. Design and analysis of experiments (New York: John Wiley 2001).

19.

Sarıgu

A. S.

Secgin

A. A.

. Study on the application of the acoustic design sensitivity analysis of vibrating bodies. Appl. Acoust. 65 (2004): 1037–1056.

20.

Jayaraman

Sivasubramanian

Balasubramanian

Lakshminarayanan

A. K.

. Prediction of tensile strength of friction stir welded A356 cast aluminium alloy using response surface methodology and artificial neural network. J. Mfg Sci. Prod. Res. 9 (2008): 1–2.

21.

Lakshminarayanan

A. K.

Balasubramanian

. Comparison of RSM with ANN in predicting tensile strength of friction stir welded AA7039 aluminium alloy joints. Trans. Non-ferrous Metals Soc. China 19 (2009): 9–18.

Optimization of the friction-stir-welding process and tool parameters to attain a maximum tensile strength of AA7075–T 6 aluminium alloy

Abstract

Abstract

Keywords

References