Automatic-Controlled Intelligent Production Line for Shoe Soles
Rui Yang
1
, Ruihan Hu
2,*
, Lin Gan
1,*
, Hualin Ke
1,*
and Yanyin Xie
3,*
1
Guangdong Institute of Intelligent Manufacturing, Guangdong Key Laboratory of Modern Control Technology,
Guangzhou 510070, China
2
Faculty of Computing, National Pilot School of Software, Harbin Institute of Technology, Harbin 150000, China
3
Guangdong HEGII Sanitary Wares Co., Ltd, Chaozhou 528000, China
Keywords: Visual Localization, Unmanned, Intelligent Production.
Abstract: In order to protect the health of workers from the damage caused by their contact with toxic chemicals such
as xylene and acetone during manual production of shoe soles, this thesis presents the realization of automatic
and intelligent processes of production of shoe soles, such as automatic glue spraying, automatic hot printing,
automatic film pressing, and automatic abrasive spraying, with the application of technologies, such as visual
positioning, automatic spraying, automatic drying, automatic printing and automatic cleaning, and the
intelligent production procedures, such as automatic glue spraying, automatic hot printing, automatic film
pressing, and automatic abrasive spraying. The processes of the presented production line include automatic
glue spraying, automatic hot printing, automatic film pressing, automatic shoe sole cleaning and automatic
wear-resistant spraying. This thesis is conducive to the establishment of a typical model of intelligent
production for the industry of shoe soles.
1 INTRODUCTION
With the development of modern manufacturing
technology and the improvement of people's quality
of life, the markets for clothing and footwear
accessories are growing constantly with an
continuously increasing market demand for the
output of related industries. As the basic component
of footwear that is essential to people’s shoe-wearing
and travelling experience, shoe soles also witness a
growing demand in the market. As the cost of
personnel and factory land continues to increase,
shoe processing factories are experiencing fierce
competition. It is therefore imperative for these
factories to find a method of shoe sole production
with higher efficiency and lower cost. (Chen, 2022;
Luo, 2022; Fülöp Melinda Timea, 2022; He, 2022;
Stockinger Christopher, 2021; Tian, 2020) The
prevailing processing technologies of shoe sole
production can be generally categorized into two
qualitative methods: direct injection molding and
reprocessing after molding. Direct injection molding
relies on special formulas of agents with wear-
resistant, anti-skid, and other properties, by mixing
*
Corresponding author
these additives into the injection molding materials
of a shoe sole, so that the injected shoe sole directly
becomes wear-resistant, anti-skid, portable and
comfortable. (Eversheim, 1982; H. Sasaoka, 1987;
Layek, 1988; Ferrarini, 1997; G.W Zhang, 2002;
Hidehiko, 2007; Gheorghe, 2014; Yin, 2013) On the
one hand, this method has the advantages of
convenient processing and low equipment cost, but
the high cost of special additives and the method’s
application limited to the upper and lower sides of
shoe soles make the material cost of shoe soles still
remain high. (Peter, 2013; Morosan, 2013; Fatih
Mehmet Özel, 2013; H N Nagendra, 2019) In
addition, the appearance of shoe soles needs to be
molded at one time, so if a special appearance is
required, the wear-resistant and anti-skid effects of
its printing will be reduced. On the other hand, shoe
soles can be molded by hot melt materials, or
processed by leather and other materials before
surface treatment such as spraying and printing,
which can maximize material cost savings. (Indri
Marina, 2019; Pierluigi Petrali, 2018; Alexandru
Nitu, 2018; Chen, 2018) However, the existing sole
processing procedures are cumbersome and require a
Yang, R., Hu, R., Gan, L., Ke, H. and Xie, Y.
Automatic-Controlled Intelligent Production Line for Shoe Soles.
DOI: 10.5220/0012040000003620
In Proceedings of the 4th International Conference on Economic Management and Model Engineering (ICEMME 2022), pages 581-586
ISBN: 978-989-758-636-1
Copyright
c
2023 by SCITEPRESS Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
581
large amount of manpower in production for division
of labor and cooperation, so that the cost of labor and
equipment for the processing of shoe soles remains
high with unstable review efficiency, and unified
efficiencies between each post. In particular, the
production of leather soles needs to go through the
processes of glue spraying, printing, film pressing,
cleaning, and wear-resistant spraying, so even
though the manufactured products of leather soles
can meet the needs of the appearance, wear
resistance, skid resistance, etc., the expensive
production equipment and labor force the processing
cost of the soles high.
2 INTELLIGENT PRODUCTION
LINE
In the process of feeding, the formed materials are
“fed to” (fixed on) the station of the conveyor
machine. Then, in the process of handling, the
materials on each station are processed through the
procedures as follows: one or any combination of
glue spraying, printing, film pressing and abrasive
spraying. Afterwards, during the process of blanking,
the processed materials are taken from the station and
sent to the finished product area. The invention of
this production line is the integration of the
processing technologies of glue spraying, printing,
film pressing and wear-resistant spraying, so that the
molded sole (upper) can be processed at one time,
and the stability of processing efficiency and
precision through the production process is
improved. By using assembly lines and multi-axis
mechanical arms to connect the production processes
in series, the production efficiency, processing
accuracy, and labor cost savings of shoe sole
manufacturing can all be improved. (Fig. 1)
Figure 1: Application of an automatic processing method for shoe sole production and the adopted equipment
2.1 Artificial Shoemaking
With the continues development of technology,
Intelligent technology persistent to impact traditional
manufacturing. As a traditional industry, the footwear
industry requires a large amount of labor and the
production technology is relatively backward, and the
level of automation is low. (Fig. 2)
2.2 Technical Proposal
The production process of shoe making mainly
comprises the processing of soles, shoes, uppers,
insoles and other parts. In this case, an automatic
processing method for sole processing is introduced
and the automatic processing of formed soles is
realized. The production process consists of a series
of consistent steps: automatic glue spraying,
automatic printing, automatic film pressing,
automatic cleaning, and automatic abrasive spraying.
(Fig. 3) The production frequency is set to ≤ 16s/pair
(or 2475 pairs/day, 11 hours per day). See Table 1 for
robot selection.
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Figure 2: Manual operation with health hazard risk
Table 1: Robot selection.
2.3 Automatic Processing Equipment
The automatic processing equipment consists of the
following components: The feeding component is
used to fix the formed materials on the station of the
conveyor machine; The conveying component is used
to convey the materials to each station; The
processing components include one or any
combination of the glue spraying module, the printing
module, the film pressing module and the abrasive
spraying module; The glue spraying module is used
to locate materials via mechanical vision, grab them
from the work station via the first six-axis spraying
robot, spray glue on them, and dry the materials in the
first dryer; The printing module is used to grab
materials and place them on the printing machine
mold via a four-axis robot, conduct air bag extrusion
printing on materials in the printing machine, and dry
the materials in the second dryer; The film pressing
module is used to put materials into the film pressing
machine via a four-axis robot for film pressing; The
wear-resistant spraying module is used to press and
fix the materials on multiple stations via a multi-
station compactor, wipe clean their bottoms via a
bottom wiping robot, spray wear-resistant agents on
them via the second six-axis spraying robot, and dry
them in the third dryer; The blanking component is
used to remove the finished materials from the station
and send them to the finished product area. (Fig. 4)
Robot performance parameters
Performance Parameter Specifications
Payload 7kg
Scope of work 918mm
Number of control axes 6
Repetitive positioning accuracy ±0.02mm
Degree of protection (wrist) IP54
Body weight 51KG
Automatic-Controlled Intelligent Production Line for Shoe Soles
583
Figure 3: Automatic unmanned machine operation
Figure 4: Automatic glue spraying, automatic hot printing, automatic film pressing, automatic sole cleaning and automatic
wear-resistant spraying for the processing of shoe soles.
3 AUTOMATIC CONTROL
Feeding: place the formed materials on the station of
the conveyor machine and fix them on the station.
Handling: the materials at each station connected by
the conveyor machine are processed through
procedures including one or any combination of glue
spraying, printing, film pressing and abrasive
spraying. Glue spraying: locate the material through
mechanical vision, grab the materials from the work
station through the first six-axis spraying robot, spray
glue on them, and make them dry in the first dryer.
Printing: the materials are grabbed by a four-axis
robot and placed on the printing machine mold,
before they are pressed and printed in the printing
machine, and dried in the second dryer. Film
pressing: the materials are put into the film pressing
machine through a four-axis robot for film pressing.
Wear-resistant spraying: press and fix the materials
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on multiple stations through a multi-station
compactor, wipe clean their bottoms using a bottom
wiping robot, spray wear-resistant agents on them
through the second six-axis spraying robot, and dry
them in a third dryer. Blanking: the finished materials
are taken from the station and sent to the finished
product area. Preferably, the conveyor machine is
one or any combination of a conveyor belt, a
transport robot and a multi-axis mechanical arm.
Preferably, the following processing procedures of
alignment are included: alignment, identifying and
positioning the materials through mechanical vision,
and adjusting the position of the station according to
the positioning of the materials to align the materials
with the processing coordinates. Preferably, the three
steps of alignment are set after feeding, glue spraying
and printing, respectively. Preferably, the following
processing procedures of cleaning are included:
cleaning, cleaning the materials after film pressing
using a cleaning machine, and drying the materials in
the fourth dryer. Preferably, the glue spraying quality
inspection, printing quality inspection, and film
pressing quality inspection are implemented to detect
the quality of the processing of glue spraying,
printing, and film pressing, respectively, through
mechanical vision, and remove the defective
materials from the production equipment after
corresponding procedures. Preferably, each station is
provided with a unique identifier that will be read
before and after each processing step, while the
corresponding processing steps are executed
according to the unique identifier, so as to record the
production information of the materials on the
station. Preferably, the processing procedures are
optimized through the digital twin optimization
system: The digital twin optimization system
includes a physical space subsystem, a digital twin
model, a virtual space subsystem and an optimization
model; The physical space subsystem is used to
acquire the assembly working conditions of the
material processing equipment and the production
working conditions of the material processing
equipment through signal acquisition; The digital
twin model is used to collect data according to the
signals of the material processing equipment
provided by the physical space subsystem, and obtain
the twin data of the equipment body, the assembly
processes, the production processes and the
performance of the material processing equipment
according to the collected signals; The virtual space
subsystem is used to examine 3D physical models,
simulate virtual intelligent assembly scenarios, as
well as virtual intelligent production scenarios
according to the information from the digital twin
model; The optimization model is used to iteratively
optimize the twin data of the equipment ontology, the
assembly processes, the production processes and the
performance according to the simulation results of
the virtual space subsystem through deep learning
algorithms, and output the optimized results. (Fig. 5)
Figure 5. Processing Procedures
4 CONCLUSION
In this case, the processing technologies of glue
spraying, printing, film pressing and wear-resistant
spraying are integrated into the the automatic
production process, so that the molded soles (uppers)
can be processed at one time with stabilized
processing efficiency and precision. By using
assembly lines and multi-axis mechanical arms to
connect the production processes in series, the
production efficiency and processing accuracy of
shoe sole manufacturing can be effectively
improved, and the labor cost can be reduced.
Through the combination of digital twin technology,
3D model simulation, the Internet of Things,
virtualization and digital technology, various
attributes of sole production equipment are mapped
into virtual space to form digital images, so as to help
production personnel redesign and optimize the
equipment assembly and the parameters of shoe sole
production line, thereby improving the production
efficiency, utilization of production equipment, and
labor cost savings for shoe sole manufacturing.
ACKNOWLEDGMENTS
This work was supported in part by the National
Natural Science Foundation of China Youth Fund
under Grant 6210023461, in part by the Natural
Science Foundation of Guangdong province under
Grant 2022A1515011749, in part by the Guangdong
Academy of Sciences' (GDAS') Project of Science
and Technology Development under Grant
Automatic-Controlled Intelligent Production Line for Shoe Soles
585
2017GDASCX-0115 and Grant 2018GDASCX-
0115, in part by the Guangdong Academy of Science
for the Special Fund of Introducing Doctoral Talent
under Grant 2021GDASYL-20210103087, in part by
the Opening Foundation of Xinjiang Production and
Construction Corps Key Laboratory of Modern
Agricultural Machinery under Grant BTNJ2021003.
REFERENCES
Alexandru Nitu, Gheorghe Marc.
MICROCONTROLLER'S USING IN MONITORING
THE MAINTENANCE SYSTEM OF FLEXIBLE
MANUFACTURING LINES [J]. Acta Technica
Napocensis, 2018,59(3).
Chen J.-W., Yang L.V., Wang K., Chen W., Yang H.-J..
Scheduling optimization of flexible assembly
production line for heavy truck[J]. IPPTA: Quarterly
Journal of Indian Pulp and Paper Technical
Association, 2018, 30(4).
Chen Jingchuan, Jia Zhiyang, Wang Xiaohan. Dynamic
performance prediction in flexible production lines
with two geometric machines [J]. International Journal
of Production Research, 2022, 60(13).
Eversheim W., Herrmann P.. Recent trends in flexible
automated manufacturing [J]. Journal of
Manufacturing Systems, 1982,1(2).
Fatih Mehmet Özel, Christian-Simon Ernst, Huw C.
Davies, Lutz Eckstein. Development of a battery
electric vehicle sector in North-West Europe:
challenges and strategies[J]. Int. J. of Electric and
Hybrid Vehicles,2013,5(1).
Ferrarini A., Bertrand J.C. Distributed Control of a
Flexible Manufacturing Line: the Way of the Leading
Product[J]. IFAC Proceedings Volumes,1997,30(6).
Fülöp Melinda Timea, Gubán Miklós, Gubán Ákos,
Avornicului Mihály. Application Research of Soft
Computing Based on Machine Learning Production
Scheduling [J]. Processes,2022,10(3).
G.W Zhang, S.C Zhang, Y.S Xu. Research on flexible
transfer line schematic design using hierarchical
process planning[J]. Journal of Materials Processing
Tech., 2002,129(1).
Gheorghe MARC, Maria Loredana BOCA. USING
LOGIC PROGRAMMING FOR IMPROVE AND
INCREASE THE RELIABILITY OF TOOLS AND
EMBEDDED MACHINE TO AVOID SOME
“MISSION CRITICAL, IN FLEXIBLE
MANUFACTURING LINES [J]. Fiabilitate şi
Durabilitate, 2014,1(13).
He Runqin. Automatic Equipment Design of Intelligent
Manufacturing Flexible Production Line Based on
Industrial Motorized Spindle [J]. International Journal
of Information Systems and Supply Chain
Management (IJISSCM), 2022,15(2).
H. Sasaoka. Automation of body assembly operations[J].
Int. J. of Vehicle Design,1987,8(3).
Hidehiko Yamamoto, Jaber Abu Qudeiri, Etsuo Marui.
Definition of FTL with bypass lines and its simulator
for buffer size decision [J]. International Journal of
Production Economics,2007,112(1).
H N Nagendra, A V Karthik, Ravi Verma, S
Kasthurirengan, N C Shivaprakash, A K Sahu,
Upendra Behera. Numerical and experimental
investigations on two-phase flow of liquid nitrogen in
a flexible transfer line[J]. IOP Conference Series:
Materials Science and Engineering,2019,502(1).
Indri Marina, Lachello Luca, Lazzero Ivan, Sibona
Fiorella, Trapani Stefano. Smart Sensors Applications
for a New Paradigm of a Production Line. [J]. Sensors
(Basel, Switzerland),2019,19(3).
Layek L. Abdel-Malek. The Effect of Robots with
Overlapping Envelopes on The Performance of
Flexible Transfer Lines [J]. IIE Transactions, 1988,
20(2).
Luo Dan, Guan Zailin, He Cong, Gong Yeming, Yue Lei.
Data-driven cloud simulation architecture for
automated flexible production lines: application in real
smart factories [J]. International Journal of Production
Research, 2022, 60(12).
Morosan, A D, Danila, A, Sisak, F. THE
DETERMINATION OF THE OPTIMAL CONTROL
LAW FOR A MANUFACTURING SYSTEM
IMPLEMENTED ON FLEXIBLE LINE FMS 200[J].
Bulletin of the Transilvania University of Brasov.
Engineering Sciences. Series I,2013,6(2).
Peter Michalik, Ján Štofa, Iveta Zolotová. The Use of
BPMN for Modelling The MES Level in Information
and Control Systems[J]. Kvalita Inovácia Prosperita,
2013, 17(1).
Pierluigi Petrali, Mauro Isaja, John K. Soldatos. Edge
Computing and Distributed Ledger Technologies for
Flexible Production Lines: A White-Appliances
Industry Case[J]. IFAC PapersOnLine,2018,51(11).
Stockinger Christopher, Stuke Fokko, Subtil Ilka. User‐
centered development of a worker guidance system for
a flexible production line [J]. Human Factors and
Ergonomics in Manufacturing & Service Industries,
2021,31(5).
Tian Chenghua, Jia Pei, Yuan Junfeng, Teng Bowen.
Application of integrated manufacturing system of
flexible production line in spacecraft manufacturing
line [J]. Journal of Physics: Conference Series, 2020,
1549(3).
Yin Juan Zhang. Research on the General NC System of
Quasi Flexible Production Line[J]. Applied Mechanics
and Materials, 2013,2668(401-403).
ICEMME 2022 - The International Conference on Economic Management and Model Engineering
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