Performance optimisation of the turning process along with multi-surface heating process

Sathish Kumar, D; Thanigaivelan, R; Natarajan, N

Performance optimisation of the turning process along with multi-surface heating process

Materials Science-Poland

Volume 40 (2022): Issue 4 (December 2022)

By:

D Sathish Kumar, R Thanigaivelan and N Natarajan

Open Access

|Mar 2023

Figures & Tables

Experimental setup: (A) IR-assisted machining; (B) UV-assisted machining; and (C) HA-assisted machining.HA, hot air; IR, infrared; UV, ultraviolet

SEM image of tool edges machined with (A) IR-assisted heating, (B) UV-assisted heating, (C) HA-assisted heating and (D) normal conditions.HA, hot air; IR, infrared; SEM, scanning electron microscopy; UV, ultraviolet

Effect of input parameters on different parameters

SEM image of chip microstructure under (A) IR-assisted machining, (B) UV-assisted machining, (C) HA-assisted machining and (D) normal machining.HA, hot air; IR, infrared; SEM, scanning electron microscopy; UV, ultraviolet

Effect of input parameters on surface roughness

SEM images of machined surface obtained under (A) IR-assisted machining, (B) UV-assisted machining, (C) HA-assisted machining and (D) normal machining.HA, hot air; IR, infrared; SEM, scanning electron microscopy; UV, ultraviolet

GRC and GRG values

Experiment no.	GRC		GRC	Rank
Experiment no.	y0* y_0^*	yi* y_i^*	GRC	Rank
1	1.0000	0.5517	0.6839	13
2	0.8438	0.6344	0.6853	12
3	0.7714	0.5000	0.7127	10
4	0.9643	0.6000	0.7328	9
5	0.7297	0.9000	0.7599	5
6	0.6429	0.6000	0.6619	16
7	0.7105	0.6344	0.6650	15
8	0.6750	0.8136	0.6806	14
9	0.5870	0.7956	0.7085	11
10	0.5745	0.8471	0.7534	6
11	0.6000	0.9172	0.7338	8
12	0.6279	0.9000	0.7642	4
13	0.5192	0.8944	0.7922	3
14	0.5000	0.9600	0.7343	7
15	0.5400	0.9290	0.8230	1
16	0.5625	1.0000	0.8097	2

L16 orthogonal array and outcome of machining

Run	A	B	C	D	Cutting force (N)	Surface roughness (μm)
1	Normal	0.1	0.1	50	89	3.18
2	Normal	0.125	0.2	100	84	2.84
3	Normal	0.15	0.3	150	81	3.45
4	Normal	0.175	0.4	200	88	2.97
5	IR	0.1	0.2	150	79	2.17
6	IR	0.125	0.1	200	74	2.97
7	IR	0.15	0.4	50	78	2.84
8	IR	0.175	0.3	100	76	2.34
9	UV	0.1	0.3	200	70	2.38
10	UV	0.125	0.4	150	69	2.27
11	UV	0.15	0.1	100	71	2.14
12	UV	0.175	0.2	50	73	2.17
13	HA	0.1	0.4	100	64	2.18
14	HA	0.125	0.3	50	62	2.07
15	HA	0.15	0.2	200	66	2.12
16	HA	0.175	0.1	150	68	2.01

ANOVA for GRG

Machining parameter	Degree of freedom	Sum of the squares	Mean square	F-value	% Contribution
A	3	0.618799	0.2063	0.842	16.84
B	3	0.835593	0.2785	1.137	22.73
C	3	0.933500	0.3112	1.270	25.40
D	3	0.943359	0.3145	1.283	25.67
Error	3	0.344308	0.1148	0.468	9.37
Total	15	3.6756	0.2450		100

Machining parameters and ranges

Code	Description	Level 1	Level 2	Level 3	Level 4
A	Heating method	Normal	IR	UV	HA
B	Feed rate, mm/rev	0.1	0.125	0.15	0.175
C	Depth of cut, mm	0.1	0.2	0.3	0.4
D	Cutting speed, m/min	50	100	150	200

TOPSIS ranking

Experiment no.	Vi+ V_i^+	Vi− V_i^-	J_i (preference) value)	Rank
1	0.0584	0.0313	0.3489	16
2	0.0425	0.0337	0.4425	15
3	0.0485	0.0429	0.4695	13
4	0.0404	0.0378	0.4833	11
5	0.0267	0.0503	0.6528	6
6	0.0387	0.0354	0.4779	12
7	0.0381	0.0336	0.4687	14
8	0.0399	0.0404	0.5032	10
9	0.0287	0.0462	0.6166	8
10	0.0253	0.0531	0.6775	4
11	0.0289	0.0500	0.6342	7
12	0.0230	0.0533	0.6986	3
13	0.0284	0.0594	0.6766	5
14	0.0337	0.0536	0.6136	9
15	0.0258	0.0621	0.7063	2
16	0.0243	0.0605	0.7132	1

ANOVA for TOPSIS

Machining parameter	Degree of freedom	Sum of the squares	Mean square	F-value	% Contribution
A	3	0.076439	0.0255	1.308	26.16
B	3	0.048701	0.0162	0.833	16.67
C	3	0.064954	0.0217	1.112	22.23
D	3	0.088611	0.0295	1.517	30.33
Error	3	0.013443	0.0045	0.230	4.60
Total	15	0.2921	0.0195		100

DOI: https://doi.org/10.2478/msp-2022-0041 | Journal eISSN: 2083-134X | Journal ISSN: 2083-1331

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Language: English

Page range: 1 - 13

Submitted on: Dec 14, 2022

Accepted on: Jan 8, 2023

Published on: Mar 3, 2023

Published by: Sciendo

In partnership with: Paradigm Publishing Services

Publication frequency: 4 times per year

Keywords:

hot air,

turning,

Related subjects:

Materials sciences, other,

Nanomaterials,

Functional and smart materials,

Materials characterization and properties

© 2023 D Sathish Kumar, R Thanigaivelan, N Natarajan, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 40 (2022): Issue 4 (December 2022)Next article

Performance optimisation of the turning process along with multi-surface heating process

Figures & Tables

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

GRC and GRG values

L16 orthogonal array and outcome of machining

ANOVA for GRG

Machining parameters and ranges

TOPSIS ranking

ANOVA for TOPSIS

Paradigm

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