The use of automation technology in the small-scale beverage industry requires development. Over time, packaged drinks are produced among large, medium and small industries. Especially small industries that are still doing manual cap laying. The production process requires precision in the process of selecting and arranging bottle caps automatically. This study aims to make a tool for selecting and arranging beverage bottle caps with Programmable Logic Controller (PLC). This research method uses an Automatic Tool design method using a Programmable Logic Controller (PLC) based control system. The PLC (Programmable Logic Controller) used is Omron, with type CP1E-E20 SDR-A programmed by CX-Programmer in the form of a ladder diagram. This tool consists of input and output. The input used consists of a Photoelectric Sensor and a Push Button. And the main output is an Electromagnet (Vibrator) 220 Vac. In the process this tool will work when the Push button is pressed for electromagnetic vibrations, electromagnetic vibrations will give vibrations to the bowl, the vibration will cause the bottle cap to move to the surface of the bowl and sort out automatically. When the bottle cap is detected by the Photoelectric Sensor, the Electromagnet will turn off automatically. Photoelectric sensor voltage source and vibrator are supplied from the DC Converter. The results of this study through photoelectric sensor testing which shows the sensor works well at a distance of 0-30 cm. From the test results, it can also be said that the Push button (PB), Photoelectric Sensor and Programmable Logic Controller (PLC) system designed can provide appropriate/synchronous commands in programming.

Topics
DC/DC converter, Sensors, Programmable logic controller, Magnetic materials, Industry
1.
M.
Xu
,
Y.
Ma
, and
S.
Chen
, “
Research on real-time quality inspection of PET bottle caps
,” in
2017 IEEE International Conference on Information and Automation (ICIA)
,
1023
–
1026
(
2017
), doi:
https://doi.org/10.1109/ICInfA.2017.8079052
.
Google Scholar
 
2.
X.
Ren
,
J.
Wen
,
Y.
Lan
,
T.
Li
, and
X.
Wang
, “
Design of Bottle Cap Detection System Based on Image Processing
,” in
2020 Chinese Control And Decision Conference (CCDC)
4880
–
4885
(
2020
).
https://doi.org/10.1109/CCDC49329.2020.9164640
Google Scholar
 
3.
A.
Gupta
,
Int. J. Res. Appl. Sci. Eng. Technol
,
7
(
12
),
248
–
253
(
2019
), doi:
https://doi.org/10.22214/ijraset.2019.12043
.
Google Scholar
Crossref
Search ADS
 
4.
R.
Ružarovský
,
R.
Holubek
,
D. R. D.
Sobrino
, and
M.
Janíček
,
Adv. Sci. Technol. Res. J
12
(
4
) (
2018
).
https://doi.org/10.12913/22998624/100349
Google Scholar
 
5.
M.
Abhijit
 and
S. S.
Priya
, “
Detecting faulty bottle caps using CNN model
,” in
2021 2nd International Conference on Smart Electronics and Communication (ICOSEC)
,
1446
–
1452
(
2021
).
https://doi.org/10.1109/ICOSEC51865.2021.9591780
Google Scholar
 
6.
S.
Sitjongsataporn
,
K.
Moolpho
, and
S.
Prongnuch
,
Adv. Sci. Technol. Eng. Syst. J
6
(
2
),
1065
–
1073
(
2021
), doi:
https://doi.org/10.25046/aj0602121
.
Google Scholar
Crossref
Search ADS
 
7.
M.
Kazmi
,
B.
Hafeez
,
H. R.
Khan
, and
S. A.
Qazi
, “
Machine-Vision-Based Plastic Bottle Inspection for Quality Assurance
,”
9
(
2022
), doi:
https://doi.org/10.3390/engproc2022020009
.
Google Scholar
 
8.
S.
Supramono
,
Internet Things Artif. Intell. J
1
(
3
),
159
–
175
(
2021
).
https://doi.org/10.31763/iota.v1i3.498
Google Scholar
Crossref
Search ADS
 
9.
G. R.
Wicaksono
 and
R. D.
Puriyanto
,
Bul. Ilm. Sarj. Tek. Elektro
3
(
1
),
1
–
9
(
2021
).
https://doi.org/10.12928/biste.v3i1.1109
Google Scholar
Crossref
Search ADS
 
10.
M. G.
Hudedmani
,
R. M.
Umayal
,
S. K.
Kabberalli
, and
R.
Hittalamani
,
Adv. J. Grad. Res
2
(
1
),
37
–
45
(
2017
), doi:
https://doi.org/10.21467/ajgr.2.1.37-45
.
Google Scholar
Crossref
Search ADS
 
11.
I. D.
Pranowo
 and
D.
Artanto
,
Int. J. Electr. Comput. Eng
11
(
4
),
3003
–
3012
(
2021
), doi:
https://doi.org/10.11591/ijece.v11i4.pp3003-3012
.
Google Scholar
Crossref
Search ADS
 
12.
I. D.
Pranowo
,
Y. B. T.
Bagastama
, and
T. A. F.
Wibisono
,
Telkomnika (Telecommunication Comput. Electron. Control
18
(
3
),
1491
–
1498
(
2020
), doi:
https://doi.org/10.12928/TELKOMNIKA.v18i3.14757
.
Google Scholar
Crossref
Search ADS
 
13.
G.
Sudarto
 and
M. T.
Santoso
, “
Development of the Omron CP1E PLC to Support PLC Practicum Activities in the Control System Engineering
,”
209
(
1
),
153
–
156
(
2021
).
Google Scholar
 
14.
F. I.
Pasaribu
,
N.
Evalina
, and
P.
Harahap
,
J. Electr. Technol. UMY
5
(
1
),
1
–
6
(
2021
), doi:
https://doi.org/10.18196/jet.v5i1.12096
.
Google Scholar
Crossref
Search ADS
 
15.
V. C.
Raju
 and
O.
Ray
, “
Development of DC-DC Power Electronics Converter Emulation kit for Educational Use
,” in
2021 National Power Electronics Conference (NPEC)
,
1
–
6
(
2021
).
Google Scholar
Crossref
Search ADS
 
16.
C.
Zhu
,
Y.
Peng
,
Y.
Yu
, and
P.
Ju
, “
Research on voltage fluctuation of power system considering wind power connection
,” in
2020 12th IEEE PES Asia-Pacific Power and Energy Engineering Conference
(
APPEEC
),
1
–
5
(
2020
).
Google Scholar
Crossref
Search ADS
 
17.
D. A.
Roy
,
R.
Rekos
,
C.
Brideau
,
T.
Lawry
, and
C.
Corrado
, “
A marine vibrator to meet the Joint Industry Project specification
,”
2018 SEG International Exposition and Annual Meeting.
Paper Number. SEG–2018–2997347 (
2018
), doi:
https://doi.org/10.1190/segam2018-2997347.1
.
Google Scholar
 
18.
O.
Orji
 et al., “
Marine vibrator source: Modular projector system
,”
SEG International Exposition and Annual Meeting.
Paper Number. D033S032R001, (
2019
), doi:
https://doi.org/10.1190/segam2019-3215325.1
.
Google Scholar
 
19.
J.
Xin
,
Z.
Kaixuan
,
J.
Jiangtao
,
D.
Xinwu
,
M.
Hao
, and
Q.
Zhaomei
,
Futur. Gener. Comput. Syst.
,
88
,
127
–
139
(
2018
), doi:
https://doi.org/10.1016/j.future.2018.05.034
.
Google Scholar
Crossref
Search ADS
 
20.
Pamela G.
Barboza
,
Cindy O.
Gamba
,
Jean J.
Schuster
,
Cristiano
Schuster
, and
Wilmar A.
Pineda
., “
Construção e Automação de um Protótipo de Esteira utilizando PLC em uma Rede ModBus
,”
Procedings do XV Simpósio Bras. Automação Intel.
,
1623
–
1628
(
2021
), doi:
https://doi.org/10.20906/sbai.v1i1.2784
.
Google Scholar
 
21.
P.
Horputra
,
R.
Phrajonthong
, and
P.
Kaewprapha
, “
Deep Learning-Based Bottle Caps Inspection in Beverage Manufacturing and Packaging Process
,” in
2021 9th International Electrical Engineering Congress (iEECON)
,
499
–
502
(
2021
).
https://doi.org/10.1109/iEECON51072.2021.9440326
Google Scholar
 
22.
X.
Liang
,
L.
Dong
, and
Y.
Wu
, “
Research on Surface Defect Detection Algorithm of Tube-Type Bottle Based on Machine Vision
,” in
2017 10th International Conference on Intelligent Computation Technology and Automation (ICICTA)
,
114
–
117
(
2017
), doi:
https://doi.org/10.1109/ICICTA.2017.32
.
Google Scholar
Crossref
Search ADS
 
23.
S. C.
Athukorala
,
H. M. A. L.
Hennayaka
,
S. M. L. P.
Rathnayake
,
M.
Hariluxman
,
J. R.
Gamage
, and
R. A. R. C.
Gopura
, “A Reverse Vending Machine for Sorting Yoghurt Cups and PET Bottles,” in
2021 Moratuwa Engineering Research Conference (MERCon)
,
333
–
338
(
2021
), doi:
https://doi.org/10.1109/MERCon52712.2021.9525682
.
Google Scholar
 
24.
C. P.
Testbed
 and
K.
Stouffer
, “
NIST-IR 8089 An Industrial Control System NISTIR 8089 An Industrial Control System Cybersecurity Performance Testbed
,” (
2016
), doi:
https://doi.org/10.6028/NIST.IR.8089
.
Google Scholar
 
25.
S. H.
Suryo
,
ROTASI
;
23
(
4
), (
2021
), doi:
https://doi.org/10.14710/rotasi.23.4.1-7
.
Google Scholar
 
This content is only available via PDF.
© 2024 Author(s). Published under an exclusive license by AIP Publishing.
2024
Author(s)
You do not currently have access to this content.