Banana Flakes: Design of Controlling Molding Machine based on

Proximity Sensors

Seri Intan Kuala, Eko Kuncoro Pramono, Galih Riyan Basuki

and Agustami Sitorus

Research Center for Appropriate Technology, Indonesian Institute of Sciences, KS Tubun 5 Street, Subang, Indonesia

Keywords: Banana Flakes Machine Control, Programmable Logic Control, Proximity Sensor.

Abstract: Banana flakes can be an alternative of nutrient-rich breakfast. It had been developed by PPTTG LIPI since

2016 and was carried out on a laboratory scale production. The scaling up was constrained at the cutting stage.

The sticky properties of the dough required a 2-stages roasting treatment before become flakes. The cutting

process manually on the dough that was flattened on a special grill paper. In this study, a control was

developed using a Programmable Logic Control (PLC). The banana flakes molding machine consists of three

main parts, the oil spray, the dough molding part, and the cutting part. Each part had a proximity sensor as a

detector the presence of baking sheets which became inputs for the PLC. The sensor on the spraying part will

control the electric pump oil. And the sensor on the molding part of the dough and the cutter will control the

solenoid valve. Solenoid valve will transmits pneumatic power from the compressor to drive the dough

molding and cutting. A simulation using CX programmer software to ensure the rate of the spraying part and

the cutting part meet the rate of the dough molding.

1 INTRODUCTION

Bananas are the most consumed fruits by Indonesian

(BMKG, Kementerian Pertanian, BNPB, LAPAN,

BPS, WFP, 2017 and Badan Pusat Statistik, 2017)

with consumption levels reach more than 7 million in

2017(Subdirektorat Statistik Holtikultura, 2017).

This condition is balanced by the growth of banana

production which experienced a positive trend from

1980-2015 with an average value of 4.16% per year

(Bappenas, 2016).

Bananas are rich in carbohydrates, food fiber,

certain vitamins, and minerals (Sidhu and Zafar,

2018). Its short shelf life (Singh, Shrivastava and

Kumar, 2018) provides an opportunity to process

bananas into products that have a longer shelf life

such as flour (Ratnasari et al., 2018). Although it has

changed shape, banana flour has high bioactive

compounds especially resistant starch (Amini

Khoozani, Birch and Bekhit, 2019). This further

strengthens the opportunities for gluten-free banana

flour-based processed products (Seguchi et al., 2014)

exclude from maize starch and rice flour (M. Rosell

and Matos, 2015).

Cereal is a breakfast preferred by school-age

children (Khehra, Fairchild and Morgan, 2018). In

addition ready to eat, breakfast with cereal is part of

a healthy lifestyle that plays an important role in order

to meet the nutritional needs (Kruma et al., 2018).

Since 2016 the Center for Appropriate Technology

Research has developed breakfast cereals in the form

of flakes made from banana flour (Surahman et al.,

2016, Ratnawati et al., 2017, Desnilasari et al., 2018).

The production process is still done manually using

common equipment used in household kitchens such

as mixers and hand ovens. The stages of making

banana flakes include the stage of mixing ingredients,

flattening, baking I, cutting, baking II, and packaging

(Ekafitri et al., 2016).

The manual production of banana flakes still has

obstacles in the process of forming into flakes. The

flakes can be formed after the flattened dough has

been baked and continued by cutting process which

done on a special baking paper by scissors. After

becomes small pieces in the form of flakes then baked

again until they reach a certain water content. The

cutting process takes a longer time compared to other

stages of the process because of the need of the first

baking process and the cutting time itself. The

objective of this research is to design a banana flakes

molding machine with an automatic control process

that is expected to overcome this problem.

Programmable Logic Controller (PLC) takes an

Kuala, S., Pramono, E., Basuki, G. and Sitorus, A.

Banana Flakes: Design of Controlling Molding Machine based on Proximity Sensors.

DOI: 10.5220/0009980400002964

In Proceedings of the 16th ASEAN Food Conference (16th AFC 2019) - Outlook and Opportunities of Food Technology and Culinary for Tourism Industry, pages 273-278

ISBN: 978-989-758-467-1

273

important role in the whole process to ensure the

forming dough to the flakes process becomes efficient

and effective by using a system that is easily

programmed, flexible and reliable to be used, and

effective in terms of the financial sector.

2 MATERIALS AND METHODS

Banana flake molding machine used in this study has

3 sub-systems, namely the oil spraying section, the

dough molding section, and the dough cutting section.

Each baking sheet will enter through the first to the

third subsystems through a conveyor belt system. The

controller will detect the baking sheet position and

will control the actuator in each sub-system

automatically. In this research, a control system was

designed using CX-Programmer software which is

the bundling PLC Omron brand software. The

designed control system can be set up automatically

or manually with a workflow as shown in Figure 1.

Figure 1: Control system on Banana flake dough molding

machine.

The manual control system is used to anticipate

unwanted circumstances. In other hand, the manual-

automatic selector switch is used as an input in the

system to prevent double settings. For automatic and

manual control system workflows, see Figure 2 and

Figure 3.

Figure 2: Otomatic control system.

Figure 3: Manual control system.

The first sensor used in this research is inductive

type proximity sensor. This sensor is very suitable to

be applied in industry (Nguyen, 2017) compared to

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capacitive ones because it is more sensitive (Guo,

Shao and Li, 2016), has no moving parts, operates

very fast, very reliable, requires no maintenance and

operates in environmental extreme conditions (Naik

et al., 2016). The second sensor, limit switch is used

for safety switches and the detection of the presence

of container die in molding. Yeop Kim et al., 2014

explain that limit switches can be used for a long time

with robustness is proven. The third sensor is reed

sensor can help pneumatic up and down movements

become faster. Reed sensor is an electric switch that

is operated with a magnetic field, consisting of a pair

of contacts on an iron metal body in a tightly closed

glass envelope (Sadad, Iswanto and Sadad, 2011). All

sensors are placed in a position as seen in Figure 4

with annotation (1) Inductive proximity sensor

sprayer; (2) Inductive proximity sensor molding; (3)

Inductive proximity sensor cutter; (4) Bottom reed

sensor; (5) Up reed sensor; (6) Limit switch.

3 RESULTS AND DISCUSSION

All sensors become inputs to PLC to control actuators

such as conveyor motors, solenoid sprayers, and

pneumatic valves. PLC as the main controller is an

important component in modern industrial control

systems (Ghaleb, Zhioua and Almulhem, 2018) that

is designed to be easy to install and maintain

(Alphonsus and Abdullah, 2016) and is used for all

needs in the industry (Katalin, 2019). The design of

the PLC control system using CX-Programmer

software as shown in Figure 5 with the input and

output information shown in Table 1.

Figure 4: The position of sensors on banana flakes molding

machine.

Figure 5: Ladder diagram of a banana flake dough molding

machine control system.

Banana Flakes: Design of Controlling Molding Machine based on Proximity Sensors

275

Table 1: Input and Output port definition of PLC.

Input Output

0.00 automatic

selector switch

for power

100.00 conveyor belt

motor driver

0.01 stop push button 100.01 sprayer

solenoid

0.02 start push button 100.02 the pneumatic

valve on the

molding section

0.03 manual selector

switch for power

100.03 pneumatic

valve cutter

under limit

0.04 manual selector

switch for motor

100.04 pneumatic

valve cutter to

top limit

0.05 proximity sensor

on the sprayer

section

0.06 manual selector

switch for

sprayer

0.07 limit switch

sensor on the

molding section

0.08 proximity sensor

on the molding

section

0.09 manual selector

switch for

molding

0.10 proximity sensor

on the cutting

section

0.11 bottom reed

sensor

1.01 top reed sensor

From the ladder diagram, the control system of the

banana flake dough molding machine can be seen by

using the timing diagram for each output as Figure 6.

Figure 6: Timing diagram on banana flake dough molding

machine control system.

I0.00

I0.01

I0.02

I0.03

I0.04

Q100.00

M2.00

I0.05

M2.01

I0.06

Q100.01

M2.00

I0.08

M2.01

I0.09

I0.07

Q100.02

M2.00

I0.08

M2.01

I0.09

I0.07

Q100.02

M200

I0.10

I0.11

I1.01

M2.01

I1.02

Q100.04

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4 CONCLUSIONS

The design of a control system for the banana flakes

molding machine to minimize the bottleneck

production process has been simulated. The main

components in this control system are PLC, CX-

Programmer, proximity sensors, limit switch and reed

sensors. Simulation design using the CX-Programmer

can describe system has been running as desired. The

next work of this research is to carry out construction

and testing of the banana flakes molding machine and

the control system that has been designed.

ACKNOWLEDGEMENTS

We would like to gratefully acknowledge Aidil

Haryanto, Novrinaldi, and all PPTTG LIPI and we are

grateful for Kemenristek Dikti through Insentif Riset

Sistem Inovasi Nasional (INSINAS) Riset Pratama

for funding this research.

REFERENCES

Alphonsus, E. R. and Abdullah, M. O., 2016. A review on

the applications of programmable logic controllers

(PLCs), Renewable and Sustainable Energy Reviews,

60, pp. 1185–1205. doi: 10.1016/j.rser.2016.01.025.

Amini Khoozani, A., Birch, J. and Bekhit, A. E. D. A.,

2019. Production, application and health effects of

banana pulp and peel flour in the food industry, Journal

of Food Science and Technology, 56(2), pp. 548–559.

doi: 10.1007/s13197-018-03562-z.

Badan Pusat Statistik, 2017. Konsumsi Buah dan Sayur

Susenas maret 2016.

Bappenas, 2016. Outlook Komoditas Pisang Komoditas

Pertanian Sub Sektor Hortikultura, p. 28.

BMKG, Kementerian Pertanian, BNPB, LAPAN, BPS,

WFP, F., 2017. Buletin Pemantauan Ketahanan Pangan

indonesia, German Humanitarian Assistance, pp. 1–24.

Available at: https://docs.wfp.org/api/documents/WFP-

0000024091/download/.

Desnilasari, D. et al., 2018. Komposisi Pangan Berbentuk

Serpihan Berbahan Baku Pisang Dan Tepung Beras.

Indonesia.

Ekafitri, R. et al., 2016. Laporan Akhir Kegiatan Tematik

Pengembangan Produk Pangan Berbasis Ripe Banana

Flour (Inovasi Pengembangan Teknologi Tepat Guna

Berbasis Pertanian dan Energi Terbarukan.

Ghaleb, A., Zhioua, S. and Almulhem, A., 2018. On PLC

network security, International Journal of Critical

Infrastructure Protection. Elsevier B.V., 22, pp. 62–69.

doi: 10.1016/j.ijcip.2018.05.004.

Guo, Y. X., Shao, Z. B. and Li, T., 2016. An analog-digital

mixed measurement method of inductive proximity

sensor, Sensors (Switzerland). MDPI AG, 16(1). doi:

10.3390/s16010030.

Katalin, Á., 2019. Voltage Monitoring and Supply

Controlling System, in Procedia Manufacturing.

Elsevier B.V., pp. 380–384. doi: 10.1016/

j.promfg.2019.02.229.

Khehra, R., Fairchild, R. M. and Morgan, M. Z., 2018. UK

children’s breakfast cereals - An oral health

perspective, British Dental Journal, pp. 164–169. doi:

10.1038/sj.bdj.2018.531.

Kruma, Z. et al., 2018. Changes in the nutritional value of

breakfast cereals containing germinated spring grain

flakes during storage, Agronomy Research, 16(S2), pp.

1405–1416.

M. Rosell, C. and Matos, M. E., 2015. Market and Nutrition

Issues of Gluten-Free Foodstuff, Advances in the

Understanding of Gluten related Pathology and the

Evolution of Gluten-Free Foods, 1, pp. 675–713. doi:

10.3926/oms.268.

Naik, A. A. et al., 2016. Inductive Proximity Sensor

Interfaced with Arduino, International Journal of

Science Technology & Engineering, 2(09), pp. 245–

250.

Nguyen, H., 2017. Experimental Research Dynamic

Characteristic of Proximity Sensor Hoai Nguyen,

International Journal of Latest Engineering Research

and Applications, 2(4), pp. 49–54.

Ratnasari, D. et al,. 2018. The Effects of Treatments on

Batu Banana Flour and Percentage of Wheat

Substitution on the Resistant Starch, in Vitro Starch

Digestibility Content and Palatability of Cookies Made

with Banana (Musa balbisiana Colla) Flour, in IOP

Conference Series: Earth and Environmental Science.

doi: 10.1088/1755-1315/116/1/012003.

Ratnawati, L. et al., 2017. Makanan Ringan Berbentuk

Serpihan Berbahan Baku Pisang dan Proses

Pembuatannya. Indonesia.

Sadad, R. S. A., Iswanto, I. and Sadad, J. A., 2011.

Implementasi Mikrokontroler Sebagai Pengendali Lift

Empat Lantai, Jurnal Ilmiah Semesta Teknika, 4(2), pp.

160–165.

Seguchi, M. et al., 2014. Development of Gluten-Free

Bread Baked with Banana (Musa spp.) Flour, Food

Science and Technology Research, 20(3), pp. 613–619.

doi: 10.3136/fstr.20.613.

Sidhu, J. S. and Zafar, T. A., 2018. Bioactive compounds in

banana fruits and their health benefits, Food Quality

and Safety, 2(4), pp. 183–188. doi: 10.1093/

fqsafe/fyy019.

Singh, P., Shrivastava, V. and Kumar, A., 2018. Recent

developments in greenhouse solar drying: A review,

Renewable and Sustainable Energy Reviews. Elsevier

Ltd, pp. 3250–3262. doi: 10.1016/j.rser.2017.10.020.

Subdirektorat Statistik Holtikultura, 2017. Statistik

Tanaman Buah-buahan dan Sayuran Tahunan

Indonesia. Available at: https://www.bps.go.id/

publication/download.html?nrbvfeve=MDgxNjY1ZW

M5ZWI2NWZkY2U4YTY5NDcz&xzmn=aHR0cHM

6Ly93d3cuYnBzLmdvLmlkL3B1YmxpY2F0aW9uLz

IwMTgvMTAvMDUvMDgxNjY1ZWM5ZWI2NWZ

Banana Flakes: Design of Controlling Molding Machine based on Proximity Sensors

277

kY2U4YTY5NDczL3N0YXRpc3Rpay10YW5hbWFu

LWJ1YWgtLS1idWFoYW4tZGFuLXNheXVyYW4t

dGFodW5h.

Surahman, D. N. et al., 2016. Makanan Kering Berbentuk

Lembaran Berbahan Baku Pisang Matang dan Proses

Pembuatannya. Indonesia.

Yeop Kim, D. et al., 2014. Wall Shape Recognition Using

Limit Switch Module, International Journal of Control

Theory and Computer Modeling. Academy and

Industry Research Collaboration Center (AIRCC), 4(2),

pp. 1–8. doi: 10.5121/ijctcm.2014.4201.

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