Implementation of Task Routing on SCADA-Based Modular

Production System Using Topkapi Vision Software

Pipit Anggraeni

, Abdur Rohman Harits Martawireja

and Watsabbit Ala Hudalloh

Manufacture Automation & Mechatronics Engineering Department, Bandung Polytechnic for Manufacturing,

Jl. Kanayakan no.21, Bandung, Indonesia

Keywords: Supervisory Control Theory, Task Routing System, Modular Production System, Topkapi Vision.

Abstract: Task Routing System (TRS) applies a series of routes created on the station module in carrying out products

to work efficiently in terms of time and safe operation. The system creates to know the value of process time

and the level of security when simulating a production line on MPS. The station module on this system is a

Modular Production System (MPS) that works with sub-module stations with different interfaces and controls

production simulations. The test results consist of 4 routes. The first route, testing – pick & place - handling

- storing - separating obtained an average time of 507.3 seconds and had 1 unsafe condition. A second route,

testing - handling - storing - separating - pick & place gets an average time of 481.6 seconds and had 2 unsafe

conditions. A third route, testing - storing - separating - pick & place - handling got an average time of 434.3

seconds and had 3 unsafe conditions. A fourth route, testing – pick & place - storing - separating - handling

takes an average time of 443.3 seconds and had no unsafe conditions. So the recommendation of task routing

on the MPS station used is on route 4.

1 INTRODUCTION

The application of technology has been widely

applied in the industrial field, but there are still those

who use simple or conventional technology so it

requires a lot of energy, takes a lot of time and the

results are limited (Setiawan, 2012). Then the

development of technology in the industry at this time

is so fast and followed by an increasingly high level

of competition. One of the technologies that are

progressing is automation technology. The

development of automation systems aims able to

guarantee the quality of products produced, reduce

production time, and reduce costs for human labour

so that the demands of the production process more

quickly and efficiently can be achieved (Mandala et

al., 2015). One of the automation technologies used

by most industries is the Supervisory Control System

and Data Acquisition (SCADA) (Roop, 2016).

SCADA systems can increase production and

make it easier for operators to monitor and control

directly in real-time against ongoing processes

(Carmona et al., 2016).

https://orcid.org/0000-0003-1986-272X

https://orcid.org/0000-0001-5090-1016

The application of SCADA systems in conducting

control and surveillance systems can be used for

automated manufacturing systems, one of which is in

Modular Production Systems (MPS) as a prototype

used in education for production simulation (Diogo et

al., 2008). For the application of the system on MPS,

it is necessary to know how the production system is

carried out so it is important to follow the methods

that allow the integration of all areas involved in the

production process on MPS (Scotti et al., 2015). The

purpose of this method is to avoid a production

process that is not properly monitored which will

hinder the production process (Nugroho, 2015).

The development of automation technology

becomes a change in the manufacturing system used

in the industrial field because of the many variations

in consumer demand for a different product so that it

takes technology that can run with different

workflows automatically in increasing efficiency and

high productivity (Subakti, 2003). Flexible

Manufacturing Systems (FMS) is generally

considered the answer to building flexibility and

speed in a production system. These two things are

828

Anggraeni, P., Martawireja, A. and Hudalloh, W.

Implementation of Task Routing on SCADA-Based Modular Production System Using Topkapi Vision Software.

DOI: 10.5220/0011892000003575

In Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science (iCAST-ES 2022), pages 828-835

ISBN: 978-989-758-619-4; ISSN: 2975-8246

needed so that the production system can produce

products that vary according to customers' wishes

quickly. This application is an example of a production

system where the concept of automation is applied in

different workflows (Pakpahan et al., 2019).

In the application of production to MPS, many

stages of product manufacturing work process

stations that allow for diversity of products to be

carried out when sorting products that will take a lot

of time and human manpower so that the process is

made with a series of routing tasks to optimize and

analyze the production flow process based on

different station standard specifications, to adjust

production capacity and functionality efficiently so

that the process is made with a series of routing tasks

to optimize and analyze the production flow process

based on different station standard specifications, to

adjust production capacity and functionality

efficiently (Rogers & Bottaci, 1997).

Task Routing Systems (TRS) on MPS is integrated

with surveillance control systems to properly monitor

and execute production machines. These control

systems are usually implemented by a programmable

logic controller (PLC), which is monitored and

controlled by the SCADA (Supervisory Control and

Data Acquisition) system to maintain security in the

observed production process (Automation, 2001).

Then from the above can be done research by

integrating the implementation of task routing or Task

Routing System on Modular Production System as a

field level of a plan which is then controlled and

monitored using SCADA system using Topkapi

vision software to monitor the system.

2 METHOD

The research method in this study refers to the

Supervisory Control Theory (SCT) method (Lopes et

al., 2016). Supervisory Control Theory (SCT) is the

theory of a framework on a system for synthesizing

controlling elements, and then carrying out

supervision called supervisors. This method is used to

be able to test the implementation of task routing on

SCADA-based MPS. In addition, the purpose of this

method is to avoid a production process that is not

properly monitored which will hinder the production

process (Nugroho, 2015).

2.1 Modular Production Systems

In this stage, an understanding of the basic theories

related to the system is to be tested, namely in the

form of descriptions of plants, working functions on

plants and plant flowcharts (Scotti et al., 2015). This

information facilitates the analysis and understanding

of systems and provides the basis for the system

modelling stage.

Table 1: Software & Hardware.

Specification

Device Specification

1 Software

- TIA PORTAL V13

- Topkapi Vision V5.1

-Ke

serverEX V6.6

2 Hardware

- 1 Personal Computer (PC)

- 5 Power Supply 24V

- 3 PLC Siemens S7-1200

- 2 PLC Siemens S7-300

- Festo MPS® Unit

- 1 Router TP-Link

-5 Ethernet

2.1.1 Testing Station

MPS Testing Station in Figure 1 serves to identify the

characteristics of the object inputted to then be sorted

automatically using a diffuse colour sensor that

detects the difference in the colour of the object (Ebel

& Pany, 2006).

Figure 1: Sensor and actuator on Testing Station.

Table 2: Testing Station Specification.

No. Specification Type

1Ca

acitive Proximit

Senso

Sensor

tical Proximit

Senso

3 Inductive Proximit

Senso

4 Analogue Senso

5 Lifting Cylinde

Actuator

6 Ejecting Cylinde

7 Air Cushion

8 Pneumatic Su

Additional

Part

9 Slide module

10 I/O Terminal

11 Comparato

Implementation of Task Routing on SCADA-Based Modular Production System Using Topkapi Vision Software

829

2.1.2 Pick and Place Station

MPS Pick & Place Station serves to provide

accessories to the workpiece to be placed by holding

the workpiece using a holding plate and detected by

infrared proximity sensors and then given accessories

that have been smoked by vacuum and placed on the

workpiece, both red, black and silver workpieces

(Didactic, 2016).

Figure 2: Sensor and actuator on Pick & Place Station.

Table 3: Pick and Place Specification.

No. Specification Type

1 Optical Diffuse Sensor

Sensor

Optical Proximity

Sensor (Through Beam)

Inductive Proximity

Senso

4 Pressure Switch sensor

5 Conveyor Belt

Actuator

6 Linear Drive 2 Axis

7 Suction Cup

8 Separator Valve Block

9 DC Gear Motor

Additional Part

10 I/O Terminal

11 Pneumatic Supply

2.1.3 Handling Station

MPS Handling station (handling) is a sub-function of

a material flow. Additional sub-functions are the

transfer process and storage process. Referring to the

VDI 2860 standard, a handling station is a process of

drafting, defined as changing or temporarily placing

an object in a predetermined layout (Ebel & Pany,

2006). Functions on the handling station are as

follows: Determine the material characteristics of an

item, Move work objects from the original place,

Move workpieces based on metallic (red) or black

and Move the workpiece to the next station.

Figure 3: Sensor and Actuator on Handling Station.

Table 4: Handling Station Specification.

No. Specification Type

1 Optical Diffuse Sensor

Sensor

2 Fibre-Optic Sensor

Inductive Proximity

Senso

4 Pneumatic Gripper

Actuator

5 Linear Flat Cylinder

6 Lifting Cylinder

7 Slide Module

Additional Part

8 Receptacle Module

9 I/O Terminal

10 Pneumatic Supply

11 Valve Terminal

2.1.4 Storing Station

MPS Storing station serves to sort and separate

workpieces based on the colour of the workpiece.

This is because there is a colour sensor that will be

active if it detects the workpiece according to the

colour detected (Ebel & Pany, 2006).

Table 5: Storing Station Specification.

No. Specification Type

1 Optical Diffuse Sensor

Sensor

2 Colour Diffuse Sensor

3 Inductive Proximity Sensor

4 Linear Drive Axis

Actuator

5 Rotary Drive Servo Motor

6 Storage Module

7 Pneumatic Gripper

8 Pneumatic Supply

Additional

Part

9 Rack Module

10 Holder Module

11 I/O Terminal

iCAST-ES 2022 - International Conference on Applied Science and Technology on Engineering Science

830

Figure 4: Sensor and Actuator on Storing Station.

2.1.5 Separating Station

Figure 5: Sensor and Actuator on Separating Station.

MPS Separating station serves to separate or sort

workpieces made of metal and non-metallic ones.

This is because there is a proximity sensor that will

be active if it detects a workpiece made of metal, and

then will activate the separator (in the form of a slab

that is moved with pneumatic) (Ebel & Pany, 2006).

Table 6: Separating Station Specification.

No. Specification Type

1 Optical Diffuse Senso

Sensor

2 Inductive Proximity Senso

3 Optical ProximitySensor (Through Beam)

4 Pneumatic Stoppe

Actuator

5 Conveyor Bel

6 Swiveling Wing

7 DC Gear Moto

Additional

Part

8 Valve Terminal

9 I/O Terminal

10 Analog Terminal

11 Pneumatic Supply

2.2 Configuration of Communication

System

The method of data collection that will be done is to

look at the results of sampling the incoming data in

the Topkapi Vision software when the process is

running and completed.

Figure 6: Communication System.

When the initial input is provided by the button, both

in the PLC and in HMI, the system will run and the

value in the form of the digital data type will go to the

PLC and HMI through the communication of data

that has been connected. HMI on Topkapi vision

sampling data when receiving output results from

sensors and actuators on the plant and then stored in

the database on Topkapi Vision to get the data needed

in this study, namely processing time at MPS.

Figure 7: Flow of OPC Server Communication.

Implementation of Task Routing on SCADA-Based Modular Production System Using Topkapi Vision Software

831

Figure 8: Flow of Modbus TCP Communication.

Figure 9: S7-Communication PUT.

2.2.1 Implementation of SCADA System

Implementation of SCADA SystemPerform SCADA

systems by monitoring the operator control system

and monitored on PCs using Topkapi Vision to run

the system on modular production systems.

Implements the entire SCADA system on elements in

the modular production system, by building a control

system on Topkapi vision software for PLC through

an OPC server intermediary for MPS modules:

Testing station, Pick&Place station, Storing station,

Separating station, and Handling station. after

implementing the entire SCADA system, then

running the entire SCADA system on a modular

production system.

Figure 10: SCADA Architecture.

2.2.2 Implementation Task Routing System

Figure 11: Task Routing System Flow Diagram.

In the implementation of the task routing system,

there are 5 stations in sequence according to the

iCAST-ES 2022 - International Conference on Applied Science and Technology on Engineering Science

832

layout of MPS station modules, namely testing

stations, pick&place stations, handling stations,

storing stations and separating stations. On this route,

there will be a process of simulating the production of

workpieces in sequence by conducting

communication between PLC level control and

monitoring of SCADA systems. Then the results will

be obtained time during the process of simulating the

production of workpieces as well as security in

carrying out task routing.

3 RESULTS

This section shows the results of research that has

been made before

3.1 Protocol Communication System

with Topkapi Vision

Data from the study showed the results of

input/output PLC addressing communication

connected to sensors and actuators in the Modular

Production System as well as the name of the sensor

and actuator name based on the model and

specifications from the station to the SCADA

Topkapi Vision software.

3.2 Visualization of SCADA System

Interface on Topkapi Vision

In the visualization of the control interface station,

there are inputs and output signal values on each

station. Each station has its controls. In the control

station, there is also a centralized control as a master

on all stations, namely SCADA system control that

will control all stations in integration at each station.

Figure 12: Visualization of control station interface.

In the visualization of the monitoring station

interface, there is visual image modelling on each

station. Each station will be monitored through visual

image modelling that has been created at the

monitoring station. Visual images at this monitoring

station will later change the signal value when doing

work processes or the production of workpieces.

Figure 13: Visualization Of Monitoring Station Interface.

Figure 14: OPC Server Addressing.

Implementation of Task Routing on SCADA-Based Modular Production System Using Topkapi Vision Software

833

Figure 15: Separating Station Specification.

3.3 Control System Testing

This test aims to find efficient time value as well as

security on the MPS station route during the process.

3.3.1 Task Routing Route-1

Figure 16: Task routing system route 1.

TRS route 1 test result on MPS station with the order

of station module layout: Testing – Pick&Place –

Handling – Storing – Separating.

Table 7: Result Route 1.

Result

experiment

Process Time

SCADA integration

mode

Unsafe

508 s

1 condition

508 s

506 s

Average 507,3s

The table above is a comparison of testing on the

route 1 task routing process with an average process

time value of 507.3 seconds.

3.3.2 Task Routing Route-2

TRS route 2 test results on MPS station with the order

of station module layout: Testing – Handling –

Storing – Separating – Pick&Place.

Table 8: Result Route 2.

Result

experiment

Process time

SCADA integration

mode

Unsafe

484 s

2 condition

482 s

479 s

Average 481,6 s

The table above is a comparison of tests on the

task routing process route 2nd with an average

process time value of 481.6 seconds.

3.3.3 Task Routing Route-3

TRS route 3 test results on MPS station with the order

of station module layout: Testing – Storing –

Separating – Pick&Place – Handling.

Table 9: Result Route 3.

Result

experiment

Process time

SCADA integration

mode

Unsafe

431 s

1 condition

435 s

437 s

Average 434,3 s

The table above is a comparison of tests on the

3rd route routing task process with an average process

time value of 434.3 seconds.

iCAST-ES 2022 - International Conference on Applied Science and Technology on Engineering Science

834

3.3.4 Task Routing Route-4

TRS route 4 test results on MPS station with the order

of station module layout: Testing – Pick&Place

Storing – Separating – Handling.

Table 10: Result Route 3.

Result

experiment

Process time

SCADA integration

mode

Unsafe

431 s

1 condition

435 s

437 s

Average 434,3 s

The table above is a comparison of testing on the

4th route routing task process with an average process

time value of 443.3 seconds.

3.4 Task Routing Test

Table 11: Result Route.

System Task

Routing

Process time (Average)

Unsafe

SCADA integration

mode

Route 1

507,3 s 1

Route 2

481,6 s 2

Route 3

437 s 1

Route 4

443,3 s 0

The table above shows the process time value and the

non-safety value on each route in the task routing

system. The route that has a more efficient time value

is the route 3 task routing system with an average

process time of 443.3 seconds.

4 CONCLUSIONS

In this study, it can be known which MPS layout

sequence is safe and efficient in terms of time

implementation of Task Routing on Modular

Production System based SCADA using Topkapi

Vision software, the result is that the route 4 task

routing system has a good efficiency time value of

443.3 seconds and is safe for production simulation,

which is 100%.

ACKNOWLEDGEMENTS

The author is grateful for the support from the

Department of Mechatronics and Automation at

Bandung Manufacturing Polytechnic for using the

MPS station to make this experiment feasible.

REFERENCES

Automation, I. S. of. (2001). Enterprise Control System

Integration Part 2 : Object Model Attributes.

Carmona, J. A. R., Benítez, J. C. M., & Garćia-Gervacio, J.

L. (2016). SCADA system design: A proposal for

optimizing a production line. 2016 International

Conference on Electronics, Communications and

Computers, CONIELECOMP 2016, 192–197.

https://doi.org/10.1109/CONIELECOMP.2016.7438574

Didactic, F. (2016). Pick & Place station 8034567.

https://www.festo-didactic.com/int-en/services/mps-the-

modular-production-system/stations/pick-place-station-

8034567.htm?fbid=aW50LmVuLjU1Ny4xNy4zMi4xN

DkwLjc4MDA

Diogo, R. A., Vicari, C. A., Loures, E. de F. R., Busetti, M.

A., & Santos, E. A. P. (2008). An Implementation

Environment for Automated Manufacturing Systems.

In IFAC Proceedings Volumes (Vol. 41, Issue 2). IFAC.

https://doi.org/10.3182/20080706-5-kr-1001.01787

Ebel, F., & Pany, M. (2006). Bestimmungsgemäße

Verwendung / Intended use.

Lopes, Y. K., Trenkwalder, S. M., Leal, A. B., Dodd, T. J.,

& Groß, R. (2016). Supervisory control theory applied

to swarm robotics. Swarm Intelligence, 10(1), 65–97.

https://doi.org/10.1007/s11721-016-0119-0

Mandala, H., Rachmat, H., Sukma, D., & Atmaja, E.

(2015). Perancangan Sistem Otomatisasi Penggilingan

Teh Hitam Orthodoks Menggunakan Pengendali PLC

Siemens S7 1200 dan Supervisory Control and Data

Acquisition ( SCADA ) di PT . Perkebunan Nusantara

VIII Rancabali. Jurnal Tugas Akhir | Fakultas

Rekayasa Industri, 2(1), 1–8.

Nugroho, C. E. (2015). Sistem SCADA untuk Pengepakan

Produk. Compare A Journal Of Comparative

Education, 77.

Pakpahan, E. K. A., Kristina, S., & Setiawan, A. (2019).

Model Simulasi untuk Sistem Manufaktur Fleksibel.

Jurnal Telematika, 13(2), 119–126.

Rogers, G. G., & Bottaci, L. (1997). Modular production

systems: A new manufacturing paradigm. Journal

of Intelligent Manufacturing, 8(2), 147–156.

https://doi.org/10.1023/A:1018560922013

Roop, D. W. (2016). Power System SCADA and Smart

Grids. IEEE Power and Energy Magazine, 14(1), 115–

116. https://doi.org/10.1109/MPE.2015.2481786

Scotti, W. A. F., Portilla, N. B., De Queiroz, M. H., & Cury,

J. E. R. (2015). Modular and systematic design of

supervisory control system integrating PLC, SCADA

and task routing for a modular production system. IEEE

International Conference on Automation Science and

Engineering, 2015-October, 807–812. https://doi.org/

10.1109/CoASE.2015.7294180

Setiawan, H. (2012). pengaruh orientasi pasar,

orientasi teknologi dan inovasi produk terhadap

keunggulan bersaing usaha songket skala kecil di kota

Palembang. Jurnal Orasi Bisnis

, 8(2), 12–19.

https://jurnal.polsri.ac.id

Subakti, M. M. I. (2003). Simulasi Dan Fleksibelitas

Pengurutan Pada Flexible Manufacturing System.

Implementation of Task Routing on SCADA-Based Modular Production System Using Topkapi Vision Software

835