Abstract
Aluminum–copper alloys are widely employed in automobile and aerospace industries owing to their marvelous mechanical and physical attributes. But the major hindrance in their application is that these materials are more susceptible to casting defects such as porosity, hot tears, and shrinkage occurring during solidification. The said issues have a negative impact on the mechanical properties of the casted materials and thus limit their use. Squeeze casting is a promising choice for these materials that has an ability to manufacture near-net shape parts with superior surface finish and better mechanical properties. Although, the potential of this method is tested for a variety of materials, but its capability for casting AA2026 alloy is yet to be comprehensively explored which is the primary focus of this research. Three key parameters of squeeze casting process, namely squeeze pressure, die temperature, and pouring temperature are selected for investigating their influence on surface roughness, ultimate tensile strength, and hardness using response surface methodology. Experimental results are analyzed using analysis of variance to find the control factor’s significance and adequacy of models. It has been found that squeeze pressure is the most influencing parameter for surface roughness whereas for ultimate tensile strength and hardness, pouring temperature is the major contributing factor. SEM analysis is carried out to reveal the micro-details of the fractured samples. In addition to finding optimal ranges of control variables (using contour plot analysis) for each response individually, a multi-response optimization has also been carried out using desirability approach. Furthermore, mathematical models are also developed and validated through confirmatory tests. The results of confirmatory runs depict that the proposed models have a high degree of prediction accuracy.
Similar content being viewed by others
References
Jorstad J, Apelian D (2009) Hypereutectic al-si alloys: practical casting considerations. Int J Met 3:13–36. https://doi.org/10.1007/BF03355450
Sigworth G (2011) Understanding quality in aluminum castings. Int J Met 5:7–22. https://doi.org/10.1007/BF03355504
Pratheesh K, Kanjirathinkal A, Joseph MA, Ravi M (2017) Study on the effects of squeeze pressure on mechanical properties and wear characteristics of near-eutectic Al-Si-cu-mg-Ni piston alloy with variable Cu content. Int J Met 11:831–842. https://doi.org/10.1007/s40962-017-0132-0
Greß T, Mittler T, Schmid S, Chen H, Ben Khalifa N, Volk W (2018) Thermal analysis and production of as-cast Al 7075/6060 bilayer billets. Int J Met. https://doi.org/10.1007/s40962-018-0282-8
Vijian P, Arunachalam VP (2007) Optimization of squeeze casting process parameters using Taguchi analysis. Int J Adv Manuf Technol 33:1122–1127
Dursun T, Soutis C (2014) Recent developments in advanced aircraft aluminium alloys. Mater Des 56:862–871. https://doi.org/10.1016/j.matdes.2013.12.002
Souissi N, Souissi S, Lecompte J-P, Amar MB, Bradai C, Halouani F (2015) Improvement of ductility for squeeze cast 2017 a wrought aluminum alloy using the Taguchi method. Int J Adv Manuf Technol 78:2069–2077
Gupta KM (2014) Engineering materials: research, applications and advances. CRC Press
Raj R, Thakur DG (2016) Qualitative and quantitative assessment of microstructure in Al-B4C metal matrix composite processed by modified stir casting technique. Arch Civ Mech Eng 16:949–960. https://doi.org/10.1016/j.acme.2016.07.004
Vijian P, Arunachalam VP (2006) Optimization of squeeze cast parameters of LM6 aluminium alloy for surface roughness using Taguchi method. J Mater Process Technol 180:161–166
Li Y, Yang H, Xing Z (2017) Numerical simulation and process optimization of squeeze casting process of an automobile control arm. Int J Adv Manuf Technol 88:941–947. https://doi.org/10.1007/s00170-016-8845-4
Ghomashchi MR, Vikhrov A (2000) Squeeze casting: an overview. J Mater Process Technol 101:1–9
Fan CH, Chen ZH, He WQ, Chen JH, Chen D (2010) Effects of the casting temperature on microstructure and mechanical properties of the squeeze-cast Al–Zn–mg–cu alloy. J Alloys Compd 504:L42–L45
Patel GCM, Mathew R, Krishna P, Parappagoudar MB (2014) Investigation of squeeze cast process parameters effects on secondary dendrite arm spacing using statistical regression and artificial neural network models. Procedia Technol 14:149–156
Patel GCM, Krishna P, Parappagoudar MB (2014) Optimization of squeeze cast process parameters using Taguchi and grey relational analysis. Procedia Technol 14:157–164
Senthil P, Amirthagadeswaran KS (2012) Optimization of squeeze casting parameters for non symmetrical AC2A aluminium alloy castings through Taguchi method. J Mech Sci Technol 26:1141–1147
Souissi S, Ben Amar M, Bradai C (2013) Microstructure characterization and tensile properties of direct squeeze cast and gravity die cast 2017A wrought Al alloy. Int J Mater Form 6:249–254
Bin S, Xing S, Ning Z, Lan LI (2013) Influence of technical parameters on strength and ductility of AlSi9Cu3 alloys in squeeze casting. Trans Nonferrous Metals Soc China 23:977–982
Haider KMA, Mufti NA (2014) Mechanical and microstructural evaluation of squeeze cast Al-4% Cu alloy using a full-factorial experimental design. J Miner Met Mater Soc 66:1446–1453
Souissi N, Souissi S, Le Niniven C, Amar MB, Bradai C, Elhalouani F (2014) Optimization of squeeze casting parameters for 2017 a wrought al alloy using Taguchi method. Metals (Basel) 4:141–154
Patel M, GC PK, Parappagoudar MB (2015) Modelling of squeeze casting process using design of experiments and response surface methodology. Int J Cast Met Res 28:167–180
Gan Y, Zhang D, Zhang W, Li Y (2015) Effect of cooling rate on microstructure and mechanical properties of squeeze cast Al–Cu–Mg alloy. Int J Cast Met Res 28:50–58
Soundararajan R, Ramesh A, Sivasankaran S, Sathishkumar A (2015) Modeling and analysis of mechanical properties of aluminium alloy (A413) processed through squeeze casting route using artificial neural network model and statistical technique. Adv Mater Sci Eng 2015:1–16
Yaseen RS, Hussein HA, Jassim AH (n.d.) Study the effects of squeeze casting parameters on the corrosion behavior of Al-Si-4Cu alloy
Souissi N, Souissi S, Le Niniven C, Amar MB, Bradai C, Halouani F (2015) An experimental design and theoretical analysis of squeeze casting parameters for 2017A aluminium alloy. Int J Mater Eng Innov 6:59–73
Azhagan MT, Mohan B, Rajadurai A (2015) Experimental study of squeeze casting of aluminium alloy AA6061. Appl Mech Mater Trans Tech Publ 422–426
Guan RG, Zhao ZY, Li YD, Chen TJ, Xu SX, Qi PX (2016) Microstructure and properties of squeeze cast A356 alloy processed with a vibrating slope. J Mater Process Technol 229:514–519
Manjunath Patel GC, Krishna P, Parappagoudar MB (2016) Squeeze casting process modeling by a conventional statistical regression analysis approach. Appl Math Model 40:6869–6888
Manjunath Patel GC, Krishna P, Parappagoudar MB (2016) Modelling and multi-objective optimisation of squeeze casting process using regression analysis and genetic algorithm. Aust J Mech Eng 14:182–198
Sarfraz S, Jahanzaib M, Wasim A, Hussain S, Aziz H (2017) Investigating the effects of as-casted and in situ heat-treated squeeze casting of Al-3.5% Cu alloy. Int J Adv Manuf Technol 89:3547–3561
Montgomery DC (2017) Design and analysis of experiments. Wiley, Hoboken
Myers RH, Montgomery DC (1995) Response surface methodology: process and product optimization using designed experiments. Wiley, Hoboken
Maeng DY, Lee JH, Won CW, Cho SS, Chun BS (2000) The effects of processing parameters on the microstructure and mechanical properties of modified B390 alloy in direct squeeze casting. J Mater Process Technol 105:196–203
Mia M, Dhar NR (2016) Prediction of surface roughness in hard turning under high pressure coolant using artificial neural network. Measurement. 92:464–474
Yue TM (1997) Squeeze casting of high-strength aluminium wrought alloy AA7010. J Mater Process Technol 66:179–185
Azam M, Jahanzaib M, Wasim A, Hussain S (2015) Surface roughness modeling using RSM for HSLA steel by coated carbide tools. Int J Adv Manuf Technol 78:1031–1041
Derringer G, Suich R (1980) Simultaneous optimization of several response variables. J Qual Technol 12:214–219. https://doi.org/10.1080/00224065.1980.11980968
El-Taweel TA (2009) Multi-response optimization of EDM with Al-Cu-Si-TiC P/M composite electrode. Int J Adv Manuf Technol 44:100–113. https://doi.org/10.1007/s00170-008-1825-6
Natarajan U, Periyanan PR, Yang SH (2011) Multiple-response optimization for micro-endmilling process using response surface methodology. Int J Adv Manuf Technol 56:177–185. https://doi.org/10.1007/s00170-011-3156-2
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Ali, M.A., Ishfaq, K. & Jawad, M. Evaluation of surface quality and mechanical properties of squeeze casted AA2026 aluminum alloy using response surface methodology. Int J Adv Manuf Technol 103, 4041–4054 (2019). https://doi.org/10.1007/s00170-019-03836-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-019-03836-6