Effect of novel grain refiner and Ni alloying additions on microstructure and mechanical properties of Al-Si9.8-Cu3.4 HPDC castings – optimization using Multi Criteria Decision making approach

Apparao, K. Ch; Bannaravuri, Praveen Kumar; Pulisheru, Kumar Swamy; Francis, E. D.; Alfred Sunny, Kalakanda; Babu Rao, Gadudasu; Daniel, P Freedon; Birru, Anil Kumar

Effect of novel grain refiner and Ni alloying additions on microstructure and mechanical properties of Al-Si9.8-Cu3.4 HPDC castings – optimization using Multi Criteria Decision making approach

Volume 40 (2022): Issue 1 (March 2022)

By:

K. Ch Apparao, Praveen Kumar Bannaravuri, Kumar Swamy Pulisheru, E. D. Francis, Kalakanda Alfred Sunny, Gadudasu Babu Rao, P Freedon Daniel and Anil Kumar Birru

Open Access

|May 2022

Figures & Tables

Sample specimen of HPDC casting (A) Final castings with their dimensions (B) Tensile specimens with their dimensions used for the experimentations. HPDC, High pressure die casting

(A) XRD results of the Al-3.5FeNb-1.5C master alloy; (B) SEM microstructure of dispersed intermetallic particles extracted from Al-3.5FeNb-1.5C master alloy. XRD, X-ray diffraction

Optical microscopic images of experimental castings at 720°C, 750°C, and 780°C: (A–C) without grain refiner, (D–F) 0.1 wt% of Al-3.5FeNb-1.5C, (G–I) 1.0 wt% of Al-3.5FeNb-1.5C

(A) Tensile strength values (B) Brinell hardness and microhardness values obtained from experimental runs. (C) and (D) show the optical microscope images of (C) R5 and (D) R25 experimental castings, which have the highest and lowest mechanical properties, respectively. (E) and (F) show the SEM and EDS images of R5, respectively

Effect of process parameters on GRG. GRA, grey relational analysis

Effect of process parameters on CC. CC, closeness coefficient

GRG and CC value of each experimental run. CC, closeness coefficient; GRG, Grey relational grade

SEM images of Al-Si9.8-Cu3.4 alloy: Experimental runs of (A) R5 at 0.1 wt.% of Al3.5FeNb-1.5C and 0.5 wt.% of Al-6Ni with base alloy and (B) R25 at 1.0 wt.% of Al3.5FeNb-1.5C with base alloy; EDX pattern of (C) Experimental run R5 and (D) Experimental run R25

SEM images of fracture pattern of experimental runs of (A) R5 at 0.1 wt.% of Al3.5FeNb-1.5C and 0.5 wt.% of Al-6Ni with base alloy and (B) R25 at 1.0 wt.% of Al3.5FeNb-1.5C with base alloy

Composition of Al-Si9_8-Cu3_4 alloy (wt_%) considered for this study

Al%	Si%	Cu%	Fe%	Ti%	Mg%	Ni%	Zn%	Pb%	Sn%	Mn%
86.18	9.839	3.474	0.189	0.184	0.041	0.008	0.008	0.043	0.013	0.007

Input parameters and experimental values of output characteristics along with average porosity values for L27 orthogonal array

Expt. runs	Input factors					Output responses			Average porosity values
Expt. runs	A (°C)	B (wt.%)	C (wt.%)	D (°C)	E (MPa)	Tensile strength	Brinell hardness	Microhardness	Average porosity values
1	720	0	0	230	12	218.39	85	113	0.88
2	720	0	0.5	260	18	223.76	85	116	0.53
3	720	0	5	290	24	245.50	88	119	0.36
4	720	0.1	0	260	18	239.88	90	136	0.26
5	720	0.1	0.5	290	24	249.09	91	135	0.25
6	720	0.1	5	230	12	237.31	85	136	0.47
7	720	1	0	290	24	220.53	83	112	0.85
8	720	1	0.5	230	12	214.67	83	114	0.71
9	720	1	5	260	18	208.63	86	118	0.75
10	750	0	0	260	24	217.87	85	114	0.95
11	750	0	0.5	290	12	210.73	85	116	0.77
12	750	0	5	230	18	230.46	89	116	0.49
13	750	0.1	0	290	12	230.19	86	118	0.63
14	750	0.1	0.5	230	18	237.29	88	130	0.44
15	750	0.1	5	260	24	212.70	85	120	0.62
16	750	1	0	230	18	208.26	80	106	1.01
17	750	1	0.5	260	24	218.83	85	113	0.88
18	750	1	5	290	12	201.05	80	108	0.97
19	780	0	0	290	18	219.96	85	115	0.89
20	780	0	0.5	230	24	224.58	88	125	0.33
21	780	0	5	260	12	240.50	87	118	0.49
22	780	0.1	0	230	24	238.37	88	127	0.46
23	780	0.1	0.5	260	12	240.04	90	132	0.48
24	780	0.1	5	290	18	232.57	85	114	0.46
25	780	1	0	260	12	200.27	80	107	0.99
26	780	1	0.5	290	18	199.68	85	119	0.49
27	780	1	5	230	24	224.74	84	114	0.53

Process factors and their levels used in the experiments

Parameter destination	Input parameters	Parameter range	Level 1	Level 2	Level 3
A	Molten metal temperature (°C)	720–780	720	750	780
B	Al-3.5FeNb-1.5C (wt%)	0.0–0.1–1.0	0.0	0.1	1.0
C	Al-6Ni (wt%)	0.0–0.5–5.0	0.0	0.5	5.0
D	Die temperature (°C)	230–290	230	260	290
E	Injection pressure (MPa)	12–24	12	18	24

Mean values of GRG at different levels and their main effects

Parameter destination	Input parameters	Level 1	Level 2	Level 3	Max/min
A	Molten metal temperature (°C)	0.601	0.470	0.530	0.131
B	Al-3.5FeNb-1.5C (wt%)	0.516	0.683	0.403	0.280
C	Al-6Ni (wt%)	0.496	0.578	0.527	0.082
D	Die temperature (°C)	0.539	0.537	0.525	0.015
E	Injection pressure (MPa)	0.508	0.528	0.565	0.056

Response table of average values of CC for TOPSIS

Parameter destination	Input parameters	Level 1	Level 2	Level 3	Max/min
A	Molten metal temperature (°C)	0.550	0.371	0.478	0.179
B	Al-3.5FeNb-1.5C (wt%)	0.454	0.704	0.240	0.464
C	Al-6Ni (wt%)	0.399	0.540	0.460	0.141
D	Die temperature (°C)	0.499	0.463	0.435	0.036
E	Injection pressure (MPa)	0.4147	0.465	0.519	0.104

TOPSIS results

Expt. runs	Normalization			Weighted normalization			Separation		CC
Expt. runs	Tensile strength	Brinell hardness	Vickers hardness	Tensile	Brinell	Vickers	S⁻	S⁺	CC
1	0.187	0.191	0.183	0.062	0.064	0.061	0.016	0.008	0.324
2	0.192	0.191	0.188	0.064	0.064	0.063	0.014	0.010	0.416
3	0.211	0.198	0.192	0.070	0.066	0.064	0.010	0.016	0.628
4	0.206	0.202	0.220	0.069	0.067	0.073	0.003	0.021	0.886
5	0.214	0.204	0.218	0.071	0.068	0.073	0.001	0.023	0.972
6	0.204	0.191	0.220	0.068	0.064	0.073	0.005	0.020	0.786
7	0.189	0.187	0.181	0.063	0.062	0.060	0.016	0.007	0.306
8	0.184	0.187	0.184	0.061	0.062	0.061	0.017	0.007	0.283
9	0.179	0.193	0.191	0.060	0.064	0.064	0.016	0.008	0.350
10	0.187	0.191	0.184	0.062	0.064	0.061	0.016	0.008	0.333
11	0.181	0.191	0.188	0.060	0.064	0.063	0.016	0.008	0.321
12	0.198	0.200	0.188	0.066	0.067	0.063	0.012	0.013	0.511
13	0.197	0.193	0.191	0.066	0.064	0.064	0.012	0.012	0.500
14	0.204	0.198	0.210	0.068	0.066	0.070	0.005	0.018	0.779
15	0.182	0.191	0.194	0.061	0.064	0.065	0.014	0.009	0.391
16	0.179	0.180	0.171	0.060	0.060	0.057	0.022	0.003	0.110
17	0.188	0.191	0.183	0.063	0.064	0.061	0.016	0.008	0.334
18	0.172	0.180	0.175	0.057	0.060	0.058	0.022	0.001	0.059
19	0.189	0.191	0.186	0.063	0.064	0.062	0.015	0.009	0.370
20	0.193	0.198	0.202	0.064	0.066	0.067	0.009	0.014	0.598
21	0.206	0.196	0.191	0.069	0.065	0.064	0.010	0.014	0.582
22	0.204	0.198	0.205	0.068	0.066	0.068	0.006	0.017	0.727
23	0.206	0.202	0.213	0.069	0.067	0.071	0.004	0.020	0.845
24	0.200	0.191	0.184	0.067	0.064	0.061	0.014	0.011	0.452
25	0.172	0.180	0.173	0.057	0.060	0.058	0.022	0.001	0.032
26	0.171	0.191	0.192	0.057	0.064	0.064	0.018	0.008	0.309
27	0.193	0.189	0.184	0.064	0.063	0.061	0.015	0.009	0.380

Normalized data and deviation sequence values of the following characteristics

Run	Deviation Tensile strength	Sequences Brinell hardness	(Δ_0i) Microhardness	GRC Tensile strength	Brinell hardness	Microhardness	GRG	Rank
1	0.62	0.55	0.77	0.45	0.48	0.39	0.44	20
2	0.47	0.55	0.67	0.49	0.48	0.43	0.47	13
3	0.07	0.27	0.57	0.87	0.65	0.47	0.66	6
4	0.19	0.09	0.00	0.73	0.85	1.00	0.86	2
5	0.00	0.00	0.03	1.00	1.00	0.94	0.98	1
6	0.24	0.55	0.00	0.68	0.48	1.00	0.72	4
7	0.58	0.73	0.80	0.46	0.41	0.38	0.42	23
8	0.69	0.73	0.73	0.42	0.41	0.41	0.41	24
9	0.82	0.45	0.60	0.38	0.52	0.45	0.45	15
10	0.63	0.55	0.73	0.44	0.48	0.41	0.44	18
11	0.51	0.55	0.67	0.39	0.48	0.43	0.43	21
12	0.38	0.18	0.67	0.57	0.73	0.43	0.58	9
13	0.38	0.45	0.60	0.57	0.52	0.45	0.52	11
14	0.24	0.27	0.20	0.68	0.65	0.71	0.68	5
15	0.74	0.55	0.53	0.40	0.48	0.48	0.46	14
16	0.83	1.00	1.00	0.38	0.33	0.33	0.35	25
17	0.61	0.55	0.77	0.45	0.48	0.39	0.44	19
18	0.97	1.00	0.93	0.34	0.33	0.35	0.34	26
19	0.59	0.55	0.70	0.46	0.48	0.42	0.45	16
20	0.49	0.27	0.37	0.50	0.65	0.58	0.58	10
21	0.17	0.36	0.60	0.74	0.58	0.45	0.59	8
22	0.22	0.27	0.30	0.70	0.65	0.63	0.66	7
23	0.18	0.09	0.13	0.73	0.85	0.79	0.79	3
24	0.33	0.55	0.73	0.60	0.48	0.41	0.49	12
25	0.99	1.00	0.97	0.34	0.33	0.34	0.34	27
26	1.00	0.55	0.57	0.33	0.48	0.47	0.43	22
27	0.49	0.64	0.73	0.50	0.44	0.41	0.45	17

Results’ comparison at initial and optimal levels by GRA and TOPSIS methods

S. No	Parameter	Initial value	Predicted value	Experimental value

		A₂, B₁, C₁, D₂, E₃	A₁, B₂, C₂, D₁, E₃	A₁, B₂, C₂, D₁, E₃
1	Tensile strength	218.388	–	249.085
2	Brinell hardness	85	–	91
3	Vickers microhardness	113	–	135
4	Grey relational grade	0.4396	0.8087	0.9792
5	Closeness coefficient	0.3242	0.9481	0.9715
6	Improvement of GRG	–	0.5396	–
7	Improvement of CC	-	0.6473	–

DOI: https://doi.org/10.2478/msp-2022-0005 | Journal eISSN: 2083-134X | Journal ISSN: 2083-1331

Journal RSS Feed

Language: English

Page range: 9 - 24

Submitted on: Oct 28, 2021

Accepted on: May 30, 2022

Published on: May 25, 2022

Published by: Wroclaw University of Science and Technology

In partnership with: Paradigm Publishing Services

Publication frequency: 4 times per year

Keywords:

die casting, Al–Si alloy,

Al-3.5FeNb-1.5C grain refiner,

Al-6Ni master alloy,

GRA,

TOPSIS,

ultimate tensile strength and hardness

Related subjects:

Materials sciences,

Materials sciences, other,

Nanomaterials,

Functional and smart materials,

Materials characterization and properties

© 2022 K. Ch Apparao, Praveen Kumar Bannaravuri, Kumar Swamy Pulisheru, E. D. Francis, Kalakanda Alfred Sunny, Gadudasu Babu Rao, P Freedon Daniel, Anil Kumar Birru, published by Wroclaw University of Science and Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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Effect of novel grain refiner and Ni alloying additions on microstructure and mechanical properties of Al-Si9.8-Cu3.4 HPDC castings – optimization using Multi Criteria Decision making approach

Figures & Tables

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Composition of Al-Si9_8-Cu3_4 alloy (wt_%) considered for this study

Input parameters and experimental values of output characteristics along with average porosity values for L27 orthogonal array

Process factors and their levels used in the experiments

Mean values of GRG at different levels and their main effects

Response table of average values of CC for TOPSIS

TOPSIS results

Normalized data and deviation sequence values of the following characteristics

Results’ comparison at initial and optimal levels by GRA and TOPSIS methods

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