SUGISAKAMASANORI

Journal of Robotics, Networking and Artificial Life
Vol. 10(3); December (2023), pp. 220–225
ISSN (Online): 2352-6386; ISSN (Print): 2405-9021
https://alife-robotics.org/jrnal.html

Research Article

Investigate Automation Production Processing Based on
LabVIEW
Bo-Jung Yang1, Chun-Chi Lai2, Chia-Nan Ko3

Graduate School of Engineering Science and Technology, National Yunlin University of Science and Technology, Taiwan
Department of Electrical Engineering, National Yunlin University of Science and Technology, Taiwan
3
Department of Automation Engineering, Nan Kai University of Technology, Taiwan
1
2

ARTICLE INFO
Article History
Received 20 November 2022
Accepted 01 March 2024
Keywords
Similar production mechanism
Intelligent automation
MyRIO
Image recognition
LabVIEW

ABSTRACT

Industry 4.0 smart automation has been actively developing recently. Enterprises actively
researched and developed intelligent automation mechanisms to promote the efficiency of
production lines. Various innovative production mechanisms must be continuously developed.
The purpose of this article is to develop a similar production mechanism based on myRIO throughpractical functional solutions to improve production efficiency and production line stability. In
this study, we used FPGA to change the pin position function by ourselves, integrated smart
technology and multiple practical experiments, and used LabVIEW software to design anautomation platform based on myRIO controller. The efficiency of developing similar production
mechanisms validates the product identification system and platform.
© 2022 The Author. Published by Sugisaka Masanori at ALife Robotics Corporation Ltd.
This is an open access article distributed under the CC BY-NC 4.0 license(http://creativecommons.org/licenses/by-nc/4.0/).

electronics automation and academic theories is a highly
cross-field discipline. An overall hardware description with
software designed for autonomous investigation will beurgent research topics.

1. INTRODUCTION
Recently, the development of automation production
processing has gradually been valued and promoted in thevarious industry fields. The intelligent automation
technology is growing gradually, and it is also testing the
new simulation methods [1]. Due to the development ofIndustry 4.0, the industry researched intelligent automatedproduction modes, mass production and warehousemanagement can replace some human resources throughartificial intelligence. In order to improve production
efficiency, improve product yield, and reduce operating
costs, people have adopted smart automated production
models [2]. High technology is gradually popularizing
various production fields, and practical technologies andapplications have become the technologies that people are
eager to find [3].
MyRIO is vastly used in industry and education, recently.
The NI myRIO platform has been listed as the main core
controller of intelligent automation platform in various
world competitions [4]. Intelligent automation technology
integrating
precisionmachinery,information
communication, image processing, FPGA, electrical

2. METHODS
A. myRIO Controller
In this study, the myRIO controller with Tetrix robot andMatrix base metal kit was selected. It has Real-Timefunction and FPGA function, allowing users to change theinput and output pins and view the required data in real time,making it easy for users to use. In [5], myRIO controller
based mobile robots are adopted for autonomous robot
systems and competitions. Therefore, myRIO as the maincore of the controller, we design the smart automation
product line. NI LabVIEW software programming canliberate users from the complexity of traditional generalpurpose programming, making it easier for users to findprogram errors [6], [7]. LabVIEW easily integrates
programming,
visualdevelopment,
algorithmic
measurement tools, communication models, and image
processing to develop innovative technologies [8], [9], [10].

Corresponding author E-mail: t105@nkut.edu.tw

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LabVIEW has programming and interface design
functions, and can independently design human-machineinterfaces, design programs and realize the functions ofautomation mechanisms. Overall, graphic drag-and-drop
design is easier for beginners and requires no programming.
When the software enters the LabVIEW window, it isshown in Fig. 1.

to present identification results and identification efficiency
in real time, improving the efficiency of each production
line [11], [12].
C. Motor
RC motor and DC motor have different functions. RC
servo motor is usually used to do high torque low speed,which usually is used to do the work for gripping objects.
RC servo motor is divided into angle type and continuous
type. DC motor is used to do low torque high speed use.
Servo control is a method of controlling many types of
RC servos by sending the servo a PWM (pulse-widthmodulation) signal, a series of repeating pulses of variablewidth where either the width of the pulse (most common
modern hobby servos) or the duty cycle of a pulse train (lesscommon today) determines the position to be achieved by
the servo. RC servo motor is to use PWM pulse width toadjust the angle and control the direction of rotation andspeed.
The main part of DC motor control is the encoder(reading, pulse width modulation, PWM control, P ID
control, Velocity Control). Among them, the encoder
reading and pulse width modulation, and PWM control arethrough myRIO Toolkits and composed of operations andthe operation is composed of, and the PID control is tocalculate the value of the Encoder and the value of the target,
and the final result is sent to the PWM control for control.
The top speed control is to control the seconds used in thecontrol. The signal is converted into a value controlled by
PID. Through PID, the motor can rotate stably from 0 to100, and each rotation error can be controlled within therange.

Fig. 1 LabVIEW2019 window

myRIO can provide a variety of interfaces such as DC
motors, servo motors, sensors, cameras, and power supplies.
The myRIO controller can quickly connect to various
controllers and is very convenient to use.
B. Image Recognition
Through Logitech C310 network camera and Microsoft
LifeCam network camera, the recognition function canrealize RGB and HSL color recognition, Barcode
recognition, and automatic mechanism to distinguishsimilar graphics. It can develop a human-machine interface

Fig. 2 System FPGA

D. FPGA221

FPGA internal logic can be changed at any time
according to user needs. Because the parallel processing
capability of FPGA is better than Real-Time, we use FPGA
to control the input and output of signals and some simpler
operations, which can speed up our data processing andreduce the load on the Real-Time side. By writing FPGA,
we can also use I/O more flexibly Fig. 2.
E. Sensors
Infrared IR sensors use triangulation methods. The
detection distance can be converted through voltage and is
not easily affected by the reflectivity of various objects.
Infrared IR sensors can also be used as proximity sensors to
observe numerical changes in the human-machine interface
Fig. 3 [13].
The computer connects with myRIO and uses the project
to find myRIO hardware by writing ultrasonic program in
LabVIEW interface. After the writing is completed, we cantest the ultrasound, and you can view the values on thehuman-machine interface to observe whether there is anerror with the actual distance Fig. 4 [14].

Fig. 3 Distance sensors values

3. EXPERIMENTS
In this study, several experiments were conducted toverify the usability of the production line mechanism.
Lifting, barcode and color recognition experiments werecarried out separately to ensure the efficiency of the
production line mechanism by the experimental results.
In Fig. 5, the Vision Assistant is used to edit the items
required for images. To find the respective ranges of thecorresponding colors, HSL (hue, saturation, lightness) has
been used to find the respective ranges of the correspondingcolors. Finally, press the selection control again to display
the input and output adjustment page, select the desired
input and output, and press Finish, which is done. In Fig. 6,
we open a new VI and write a shape recognition program in
the terminal. First, obtain the target through visualcollection and convert the image into black and white,which can greatly improve the processing speed. Afterbinarization and shape appearance training, the shapeappearance and area data are obtained. The shape name isobtained through the index array, and then the training
results and recognition results are used for comparison.
After the comparison is completed, the corresponding
shape photos and shapes will be found.
Similarly, the target is photographed by Vision
Acquisition, edited by Vision Assistant, the total area valueof the Add Array Elements. Finally, the result is judged by
Array as shown in Fig. 7. As the same, first, use Vision
Acquisition to turn on the camera to get the image, the
Vision Assistant reads Barcodes, and then separates thedata showing the text and Bollinger signal to obtain
Barcodes Recognition as shown in Fig. 8.

Fig. 4 Ultrasound values

Fig. 5 Vision AssistantFig. 6 Pattern Recognition Program

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Fig. 8 Barcodes Recognition Program

Fig. 7 Colors Recognition Program

Fig. 9 Production line-like experimental structure

Fig. 10 Step 1 program block flow of LabVIEW

Fig. 11 Step 2 program block flow of LabVIEW

Fig. 12 Step 3 program block flow of LabVIEW

Fig. 13 Step 4 program block flow of LabVIEW

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Fig. 14 Step 5 program block flow of LabVIEW

Similar Production Line Steps
The experimental structure of the similar production line
is shown in Fig. 9.

process and completing step 5. The program block diagram
flow of this step of LabVIEW is shown in Fig. 14.
In order to ensure the stability of the implementation of
the production line mechanism, 15 practical experiments
were carried out, and each implementation was carried out
to identify the object. In 15 implementations, the barcode
recognition can be correctly recognized, and the color
recognition has one error. The color recognition may becaused by the influence of ambient light. The performanceof the production line mechanism can be verified from15
experiments.
Experiment results were carried out on the stability of
the whole mechanism. The completion of this mechanism
can provide an intelligent automated production moduleand promote the production line automation technology.

A similar production line step is as follows:
Step1
After the start button is pressed, the robot arm and theload platform return to their initial positions, and the object
is placed on the load platform. When the infrared sensor
senses the object, the load platform starts to move. Whenthe slide rail contacts the micro switch, the slide rail stops
moving. Complete step 1 program block flow LabVIEW
program as shown in the Fig. 10.
Step 2
When the infrared sensor senses an object, the roboticarm descends to grab the object. The sliding rail movement
robot arm rises and stops when it encounters the limit
switch. The turntable rotates to the target position, therobot arm descends, the clamp opens, and the object isplaced on the load platform. Then, the slider moves therobot arm upward and stops when it encounters the limit
switch to complete step 2. The program block diagram of
LabVIEW step 2 is shown in Fig. 11.

4. RESULTS and DISCUSSION
This article takes the myRIO controller as the main core,and uses Matrix to build and develop an automatedproduction structure through research on practical functions
similar to the production mechanism. Combining
theoretical methods and practical experiments, anautomation structure including an electromechanicalsystem and a smart automation program based on
LabVIEW2019 was constructed, and FPGA was used to reestablish pins and WIFI modules for remote monitoring.
The efficiency of the designed automated production line
verifies the usability of the designed automation
mechanism from experiment results. Then, the designed
automated production mechanism can be applied inindustry to improve the production capacity, stability, andyield of the production line and fully achieve Industry 4.0.

Step 3Once an object is placed on the load platform, theinfrared sensor senses the object. The linear slide rail starts
to move the load platform, and the lens recognizes theobject barcode and color. After the recognition iscompleted, when the load platform slide rail contacts the
micro switch, the load platform stops moving to complete
step 3. Step 3 The LabVIEW program block diagram isshown in Fig. 12.

5. CONCLUSION
To research and design similar production processing,the myRIO controller has been adopted as the main
controller. This implement of automation mechanism willcomplete teaching materials, which can provide basic
teaching materials for intelligent automation applications
and cultivate technical talents in cross-field intelligent
automated production.
The completion of similar production line materials inthis scheme can popularize intelligent automation
education. Laboratory teaching materials continue to be
developed and disseminated. In the future, the applicationof various image recognition can be extended to automatedproduction technology and cultivate cross-field technicaltalents.

Step 4
When the infrared sensor senses an object on the load
platform, the robotic arm lowers to grab the object. The
linear slide moves to lift the robotic arm. The turntablerotation causes the robotic arm to rotate to the target
position. The robotic arm moves down the load platform,
placing the object on the storage platform, and then returns
to the original position to complete step 4. The program
block diagram of LabVIEW step 4 is shown in Fig. 13.
Step 5
When the infrared sensor senses that there is an object on
the load platform, the load platform is started, the slider
touches the micro switch, and the load platform stops
moving. When the ultrasonic sensor on the side of the load
platform cannot sense the object, it means that the object
has been taken away. The load platform will move to theinitial position and stand by, ending the production line

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Authors Introduction
Mr. Bo-Jun Yang

Dr. Chia-Nan Ko

He received the Ph.D. degree inelectrical engineering from National
Chung Cheng University, Taiwan, in
2014. He is currently an AssistantProfessor of National Yunlin
University of Science andTechnology in Taiwan. His researchinterests include multi-sensor fusion
and intelligent robotics.

He is currently a doctoral student at
the Institute of Engineering Scienceand Technology, Douliu Yunlin
Universityof
ScienceandTechnology, Taiwan. His researchinterests include mobile robot, PID
control, production line, Slam,
image processing.

Dr. Chun-Chi Lai

He received the Ph.D. degree inelectrical engineering from National
Chung Cheng University, Taiwan, in
2014. He is currently an AssistantProfessor of National Yunlin
Universityof
ScienceandTechnology in Taiwan. His researchinterests include multi-sensor fusion
and intelligent robotics

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