Optimization of process parameters of High Pressure Die Casting process for ADC12 Aluminium alloy using Taguchi method

This introduction paper is based on the paper "[Optimization of process parameters of High Pressure Die Casting process for ADC12 Aluminium alloy using Taguchi method]" published by "[International Journal of Pure and Applied Mathematics]".

1. Overview:

  • Title: Optimization of process parameters of High Pressure Die Casting process for ADC12 Aluminium alloy using Taguchi method
  • Author: Veeresh G Balikai, IG Siddlingeshwar, Mahesh Gorwar
  • Year of publication: 2018
  • Journal/academic society of publication: International Journal of Pure and Applied Mathematics
  • Keywords: Optimisation, DOE, Taguchi Method, HPDC, Process parameters, Porosity

2. Abstract:

A study has been carried out to optimize the die casting process parameters in order to achieve the improved quality of high pressure die casting (HPDC) products, which is the challenge for the small and large scale manufacturers of HPDC products. In this study the approach used is the experimental study to optimize the die casting process parameters for the ADC12 aluminum alloys. The ADC12 aluminum alloy components were chosen for the study and objective was to reduce the porosity in these components which help to obtain the good quality castings. The porosity is the most common defect frequently encountered in aluminium high pressure die castings, which increases the rejection rate and scrap rate and reduces the productivity. Porosity formation is closely related to die casting process parameters. Hence in order to minimize the porosity, this paper investigated the effect of process parameters on porosity formation in HPDC of ADC12 alloys and optimization of process parameters carried out using Taguchis parameter design approach. Experiments were conducted by varying selected process parameters with different levels as per Taguchi method. ANOVA was performed to find the significance of parameters on porosity formation in die castings. Results indicated that selected process parameters have significant effect on porosity formation. The optimum process parameters were obtained for minimum porosity in HPDC of ADC12 alloy.

3. Introduction:

High pressure die casting (HPDC) process is an efficient manufacturing process to produce complex, thin and thick wall components economically with high productivity and high dimensional accuracy for automotive, aerospace, defence and other industries [9,13]. In aluminium high pressure die casting process, molten aluminium alloy is injected into a metal mould at high speed and allowed to solidify under high holding pressure [10]. ADC12 based alloys have been widely used in the field of HPDC process to produce lightweight components with low cost, good mechanical properties and high corrosion resistance for electric, electronic and automobile and other applications [5].

In high pressure die casting of ADC12 aluminium alloys, Porosity is the most common defect caused due to entrapment of air/gas and oxides due to the turbulent flow of metal during the cavity filling [8]. This defect is classified as gas porosity (caused due to air trapped air in sleeve), shrinkage porosity (due to solidification of the metal in the gate before solidification in other areas of the casting) and flow porosity (caused due to insufficient pressure towards the end of cavity filling). The mechanical properties and pressure tightness are affected due to presence of porosity in castings. Porosity in a high pressure die casting varies both with part geometry of component and casting parameters of the process [9].

Porosity formation is determined by several independent process parameters. The focus of this research is to investigate the effects of selected process parameters on casting porosity and reduction of porosity formation in die castings of ADC12 aluminium alloy can be achieved by using Taguchis parameter design approach for the Design of experiments (DOE). The porosity formation is minimized by selecting the optimum process parameters for HPDC process.

4. Summary of the study:

Background of the research topic:

The quality improvement of high pressure die casting (HPDC) products is a significant challenge for manufacturers. Porosity is a common defect in aluminium HPDC, leading to increased rejection and scrap rates, and reduced productivity. Porosity formation is intrinsically linked to the die casting process parameters.

Status of previous research:

Previous studies have focused on the influence of process parameters on porosity formation in die castings. G.O. Verran et al (2008) investigated the optimization of injection parameters using the Taguchi method for SAE 305 alloys [3]. V. D. Tsoukalas (2003) examined the effect of die casting machine parameters on porosity in aluminium die-casting [6]. Lars Arnberg et al (2015) reviewed the impact of injection parameters on porosity and tensile properties of Al-Si alloys [8]. G.P.Syrcos (2003) also applied the Taguchi method to optimize aluminium alloy die casting [4].

Purpose of the study:

This study aims to optimize the die casting process parameters for ADC12 aluminium alloy components to minimize porosity and improve casting quality. The research utilizes the Taguchi parameter design approach to identify the optimum process parameters for HPDC.

Core study:

The core of this study is to experimentally optimize the die casting process parameters for ADC12 aluminium alloy using the Taguchi method. The investigation focuses on minimizing porosity, a critical defect in HPDC, by adjusting process parameters. ANOVA is employed to determine the significance of each parameter on porosity formation.

5. Research Methodology

Research Design:

The research employs the Taguchi parameter design approach, a Design of Experiments (DOE) technique, to systematically investigate and optimize process parameters. An orthogonal array (OA) is utilized to reduce the number of experiments required while efficiently exploring the parameter space. Specifically, an L25 orthogonal array is chosen based on the degree of freedom (DOF) for 4 parameters at 5 levels.

Data Collection and Analysis Methods:

Experiments were conducted on a high pressure die casting machine 400T HMT model. The selected process parameters are: Pouring temperature (T), Injection pressure (P), Plunger velocity 1st phase (V1), and Plunger velocity 2nd phase (V2), each with 5 levels as shown in Table 1.

Table 1: Process parameters and their ranges along with 5 levels

Sl noProcess parametersRangeLevel 1Level 2Level 3Level 4Level 5
1Pouring temperature, T (°C)660-700660670680690700
2Injection pressure, P (Kg/m³)160-200160170180190200
3plunger velocity-1st. V₁ (m/s)0.26-0.30.260.270.280.290.3
4plunger velocity-2nd, V2 (m/s)2.6-32.62.72.82.93

Casting density was measured using Archimedes' principle, and porosity was quantitatively analyzed. The S/N ratio was calculated to assess the variation of porosity. ANOVA was performed to determine the statistical significance of each process parameter on porosity. Minitab 16 software was used for Taguchi optimization and ANOVA.

Research Topics and Scope:

The research focuses on optimizing process parameters to minimize porosity in HPDC of ADC12 aluminium alloy. The scope is limited to four key process parameters: pouring temperature, injection pressure, plunger velocity (1st phase), and plunger velocity (2nd phase). The study uses an L25 orthogonal array for experimental design and ANOVA for data analysis.

6. Key Results:

Key Results:

ANOVA results (Table 4) indicate that plunger velocity (1st phase), plunger velocity (2nd phase), and pouring temperature significantly affect die casting porosity. The percentage contribution of each parameter is:

  • Plunger velocity (1st phase): 34.012%
  • Plunger velocity (2nd phase): 31.602%
  • Pouring temperature: 11.245%
  • Intensification pressure: 2.134%

Table 4: ANOVA for S/N ratios of die casting porosities

SourceDOFSeq SSAdj MSFPx100%
T44191050.6311.2453
P479200.112.1340
V1412683172.5834.012
V2411722932.2931.602
Error8439.28754.91
Total242728.23100

Optimum process parameters for minimum porosity are:

  • Pouring temperature: 660°C (1st level)
  • Intensification pressure: 190 kg/cm² (4th level)
  • Plunger velocity (1st phase): 0.3 m/s (5th level)
  • Plunger velocity (2nd phase): 3.0 m/s (5th level)

Figure Name List:

  • Fig.1. Cause and effect diagram (Ishikawa diagram) for casting porosity

7. Conclusion:

The experimental study demonstrates that variations in die casting process parameters significantly affect porosity formation in ADC12 aluminium alloy die castings. Pouring temperature, intensification pressure, plunger velocity (1st phase), and plunger velocity (2nd phase) are identified as influential parameters. The Taguchi Method parameter design approach successfully optimized process parameters in HPDC for ADC12 alloy, achieving satisfactory porosity reduction and improved casting quality. The optimized parameters for minimum porosity are Pouring temperature at 660°C, Intensification pressure at 190 kg/cm², Plunger velocity (1st phase) at 0.3 m/s, and Plunger velocity (2nd phase) at 3.0 m/s.

8. References:

  • [1] S. W. Choi, Y. C. Kim, J. I. Cho & C. S. Kang (2008), Influence of die casting process parameters on castability and properties of thin walled aluminium housings, International Journal of Cast Metals Research, 21:1-4, pp.330-333.
  • [2] Murray, M.T. (2011) High pressure die casting of aluminium and its alloys, M Murray & Associates Pty Ltd, Australia.
  • [3] G.O. Verran, R.P.K. Mendes, L.V.O. Dalla Valentina (2008), DOE applied to optimization of aluminium alloy die castings journal of materials processing technology, 200 pp.120125.
  • [4] G.P.Syrcos (2003), Die casting process optimization using Taguchi method, journal of materials processing technology, 135, pp.68-74.
  • [5] M.A. Irfan, D. Schwam, A. Karve, R. Ryder (2012), Porosity reduction and mechanical properties improvement in die cast engine blocks, Materials Science and Engineering A 535, pp.108 114.
  • [6] V. D. Tsoukalas (2003), The effect of die casting machine parameters on porosity of aluminium die castings, International Journal of Cast Metals Research, 15:6, pp.581-588.
  • [7] Guilherme Ourique Verran, Rui Patrick Konrad Mendes, Marco Aurelio Rossi, Influence of injection parameters on defects formation in die casting Al12Si1.3Cu alloy: Experimental results and numeric simulation, Journal of Materials Processing Technology, 179 (2006) pp.190195.
  • [8] Anilchandra R. Adamane, Lars Arnberg, Elena Fiorese, Giulio Timelli, Franco Bonollo, (2015), Influence of Injection parameters on the porosity and tensile properties of High pressure die cast Al-Si Alloys: A Review, International Journal of Metalcasting, Volume 9, Issue 1.
  • [9] Laihua Wang, Peter Turnley, Gary Savage (2011), Gas content in high pressure die castings, Journal of Materials Processing Technology 211, pp.15101515.
  • [10] V.D. Tsoukalas (2008), Optimization of porosity formation in AlSi9Cu3 pressure die castings using genetic algorithm analysis, Materials and Design 29, pp.20272033.
  • [11] Roy, R. K. Design of Experiments Using the Taguchi Approach: 16 Steps to Product and Process Improvement, 2001 (J. Wiley, New York).
  • [12] Taguchi, G. and Konishi, S. Orthogonal Arrays and Linear Graphs, 1987 (American Supplier Institute, Dearborn, Michigan).
  • [13] Quang-Cherng Hsu and Anh Tuan Do (2013), Minimum Porosity Formation in Pressure Die Casting by Taguchi Method, Mathematical Problems in Engineering.
  • [14] Taguchi G. Introduction to quality engineering. 1st ed. New York: Asian Productivity Organization, UNIPUB; 1986.
  • [15] Logothetis N. Total quality control. 2nd ed. UK: Prentice-Hall International Limited; 1992.
  • [16] K.Ch.Apparao and Anil Kumar Birru, Optimization of Die casting process based on Taguchi approach, Materials Today: Proceedings 4 (2017) pp.18521859.

9. Copyright:

  • This material is a paper by "Veeresh G Balikai, IG Siddlingeshwar, Mahesh Gorwar". Based on "Optimization of process parameters of High Pressure Die Casting process for ADC12 Aluminium alloy using Taguchi method".
  • Source of the paper: http://www.acadpubl.eu/hub/Special Issue

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