Abstract

This research focused on developing a hybrid quality monitoring model through combining the data-driven and key engineering parameters to predict the friction stir blind riveting (FSBR) joint quality. The hybrid model was formulated through utilizing the in situ processing and joint property data. The in situ data involved sensor fusion (force and torque signals) and key processing parameters (spindle speed, feed rate, and stacking sequence) for data-driven modeling. The quality of the FSBR joints was defined by the tensile strength. Furthermore, the joint cross-sectional analysis and failure modes in lap shear tests were employed to confirm the efficacy of the proposed model and development of the process–structure–property relationship.

References

1.
Immarigeon
,
J. P.
,
Holt
,
R. T.
,
Koul
,
A. K.
,
Zhao
,
L.
,
Wallace
,
W.
, and
Beddoes
,
J. C.
,
1995
, “
Lightweight Materials for Aircraft Applications
,”
Mater. Charact.
,
35
(
1
), pp.
41
67
.
2.
Che
,
D.
,
Saxena
,
I.
,
Han
,
P.
,
Guo
,
P.
, and
Ehmann
,
K. F.
,
2014
, “
Machining of Carbon Fiber Reinforced Plastics/Polymers: A Literature Review
,”
ASME J. Manuf. Sci. Eng.
,
136
(
3
), p.
034001
.
3.
Khan
,
H. A.
,
Nigar
,
M.
, and
Chaudhry
,
I. A.
,
2015
, “Tensile Behavior of Unidirectional Carbon-Reinforced Composites for Aerospace Structures Under Varying Strain Rates,”
Applied Mechanics and Materials
,
D.
Hoxha
,
I.
McAndrew
, and
A.
Dung Ngo
, eds.,
Trans Tech Publications
, pp.
357
361
.
4.
Wang
,
K.
,
Li
,
Y.
,
Banu
,
M.
,
Li
,
J.
,
Guo
,
W.
, and
Khan
,
H.
,
2017
, “
Effect of Interfacial Preheating on Welded Joints During Ultrasonic Composite Welding
,”
J. Mater. Process. Technol.
,
246
, pp.
116
122
.
5.
Upadhyay
,
P.
,
Hovanski
,
Y.
,
Jana
,
S.
, and
Fifield
,
L. S.
,
2017
, “
Joining Dissimilar Materials Using Friction Stir Scribe Technique
,”
ASME J. Manuf. Sci. Eng.
,
139
(
3
), p.
034501
.
6.
Díaz
,
J.
, and
Rubio
,
L.
,
2003
, “
Developments to Manufacture Structural Aeronautical Parts in Carbon Fiber Reinforced Thermoplastic Materials
,”
J. Mater. Process. Technol.
,
143
, pp.
342
346
.
7.
Wang
,
H.
,
Yang
,
K.
, and
Liu
,
L.
,
2018
, “
The Analysis of Welding and Riveting Hybrid Bonding Joint of Aluminum Alloy and Polyether-Ether-Ketone Composites
,”
J. Manuf. Process.
,
36
, pp.
301
308
.
8.
Khan
,
H. A.
,
Li
,
J.
, and
Shao
,
C.
,
2017
, “
Analyses of Friction Stir Riveting Processes: A Review
,”
ASME J. Manuf. Sci. Eng.
,
139
(
9
), p.
090801
.
9.
Gao
,
D.
,
Ersoy
,
U.
,
Stevenson
,
R.
, and
Wang
,
P.-C.
,
2009
, “
A New One-Sided Joining Process for Aluminum Alloys: Friction Stir Blind Riveting
,”
ASME J. Manuf. Sci. Eng.
,
131
(
6
), p.
061002
.
10.
Lathabai
,
S.
,
Tyagi
,
V.
,
Ritchie
,
D.
,
Kearney
,
T.
,
Finnin
,
B.
,
Christian
,
S.
,
Sansome
,
A.
, and
White
,
G.
,
2011
, “
Friction Stir Blind Riveting: A Novel Joining Process for Automotive Light Alloys
,”
SAE Int. J. Mater. Manuf.
,
4
(
1
), pp.
589
601
.
11.
Wang
,
W.-M.
,
Ali Khan
,
H.
,
Li
,
J.
,
Miller
,
S. F.
, and
Zachary Trimble
,
A.
,
2016
, “
Classification of Failure Modes in Friction Stir Blind Riveted Lap-Shear Joints With Dissimilar Materials
,”
ASME J. Manuf. Sci. Eng.
,
139
(
2
), p.
021005
.
12.
Min
,
J.
,
Li
,
Y.
,
Li
,
J.
,
Carlson
,
B. E.
, and
Lin
,
J.
,
2015
, “
Friction Stir Blind Riveting of Carbon Fiber-Reinforced Polymer Composite and Aluminum Alloy Sheets
,”
Int. J. Adv. Manuf. Technol.
,
76
(
5
), pp.
1403
1410
.
13.
Khan
,
H. A.
,
Wang
,
W. M.
,
Wang
,
K.
,
Li
,
S.
,
Miller
,
S.
, and
Li
,
J.
,
2019
, “
Investigation of Mechanical Behavior of Dissimilar Material FSBR Joints Exposed to a Marine Environment
,”
J. Manuf. Process.
,
37
, pp.
376
385
.
14.
Wang
,
W.
,
Wang
,
K.
,
Khan
,
H. A.
,
Li
,
J.
, and
Miller
,
S.
,
2018
, “
Numerical Analysis of Magnesium to Aluminum Joints in Friction Stir Blind Riveting
,”
Procedia CIRP
,
76
, pp.
94
99
.
15.
Guo
,
W.
,
Chen
,
J.
,
Guo
,
S.
, and
Li
,
J.
,
2017
, “
Process Monitoring of Friction Stir Blind Riveting for Lightweight Materials
,”
Proceedings of the 2017 Industrial and Systems Engineering Conference
,
Pittsburgh, PA
, pp.
2165
2170
.
16.
Lu
,
H.
,
Plataniotis
,
K. N.
, and
Venetsanopoulos
,
A. N.
,
2008
, “
MPCA: Multilinear Principal Component Analysis of Tensor Objects
,”
IEEE Trans. Neural Netw.
,
19
(
1
), pp.
18
39
.
17.
Lu
,
H.
,
Plataniotis
,
K. N.
, and
Venetsanopoulos
,
A. N.
,
2009
, “
Uncorrelated Multilinear Principal Component Analysis for Unsupervised Multilinear Subspace Learning
,”
IEEE Trans. Neural Netw.
,
20
(
11
), pp.
1820
1836
.
18.
Min
,
J.
,
Li
,
J.
,
Carlson
,
B. E.
,
Li
,
Y.
,
Quinn
,
J. F.
,
Lin
,
J.
, and
Wang
,
W.
,
2015
, “
Friction Stir Blind Riveting for Joining Dissimilar Cast Mg AM60 and Al Alloy Sheets
,”
ASME J. Manuf. Sci. Eng.
,
137
(
5
), p.
051022
.
19.
Paynabar
,
K.
,
Jin
,
J. J.
, and
Pacella
,
M.
,
2013
, “
Monitoring and Diagnosis of Multichannel Nonlinear Profile Variations Using Uncorrelated Multilinear Principal Component Analysis
,”
IIE Trans.
,
45
(
11
), pp.
1235
1247
.
20.
Guo
,
W.
,
Jin
,
J.
, and
Hu
,
S. J.
,
2016
, “
Profile Monitoring and Fault Diagnosis Via Sensor Fusion for Ultrasonic Welding
,”
Proceedings of the ASME 2016 11th International Manufacturing Science and Engineering Conference. Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing
,
Blacksburg, VA
, p.
V002T04A028
.
21.
Yan
,
H.
,
Paynabar
,
K.
, and
Shi
,
J.
,
2015
, “
Image-Based Process Monitoring Using Low-Rank Tensor Decomposition
,”
IEEE Trans. Autom. Sci. Eng.
,
12
(
1
), pp.
216
227
.
22.
Cichocki
,
A.
,
Mandic
,
D.
,
De Lathauwer
,
L.
,
Zhou
,
G.
,
Zhao
,
Q.
,
Caiafa
,
C.
, and
Phan
,
H. A.
,
2015
, “
Tensor Decompositions for Signal Processing Applications: From Two-Way to Multiway Component Analysis
,”
IEEE Signal Process. Mag.
,
32
(
2
), pp.
145
163
.
23.
Bilodeau
,
M.
, and
Brenner
,
D.
,
2008
,
Theory of Multivariate Statistics
,
Springer Science & Business Media
, New York.
24.
Friedman
,
J.
,
Hastie
,
T.
, and
Tibshirani
,
R.
,
2001
,
The Elements of Statistical Learning
,
Springer Series in Statistics
,
New York
.
25.
Grasso
,
M.
,
Colosimo
,
B.
, and
Pacella
,
M.
,
2014
, “
Profile Monitoring Via Sensor Fusion: The Use of PCA Methods for Multi-Channel Data
,”
Int. J. Prod. Res.
,
52
(
20
), pp.
6110
6135
.
26.
Friedman
,
J.
,
Hastie
,
T.
, and
Tibshirani
,
R.
,
2010
, “A Note on the Group Lasso and a Sparse Group Lasso,” preprint arXiv:1001.0736.
27.
Simon
,
N.
,
Friedman
,
J.
,
Hastie
,
T.
, and
Tibshirani
,
R.
,
2013
, “
A Sparse-Group Lasso
,”
J. Comput. Graph. Stat.
,
22
(
2
), pp.
231
245
.
28.
Yuan
,
M.
, and
Lin
,
Y.
,
2006
, “
Model Selection and Estimation in Regression With Grouped Variables
,”
J. R. Stat. Soc. B: Stat. Methodol.
,
68
(
1
), pp.
49
67
.
29.
Ruta
,
D.
, and
Gabrys
,
B.
,
2000
, “
An Overview of Classifier Fusion Methods
,”
Comput. Inf. Syst.
,
7
(
1
), pp.
1
10
.
30.
Schön
,
J.
,
2004
, “
Coefficient of Friction for Aluminum in Contact With a Carbon Fiber Epoxy Composite
,”
Tribol. Int.
,
37
(
5
), pp.
395
404
.
31.
Khan
,
H. A.
,
Pei
,
S.
,
Chen
,
N.
,
Miller
,
S.
, and
Li
,
J.
,
2020
, “
Evaluation of µFSBR Joint Performance by Process-Physics Based Quality Criteria and Online Monitoring Algorithm
,”
J. Mater. Process. Technol.
,
278
, p.
116508
.
32.
Min
,
J.
,
Li
,
Y.
,
Li
,
J.
,
Carlson
,
B. E.
, and
Lin
,
J.
,
2015
, “
Mechanics in Frictional Penetration With a Blind Rivet
,”
J. Mater. Process. Technol.
,
222
, pp.
268
279
.
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