Design and Construction of a Sensor Analytics System for the Monitoring of the Parameters of a Plastic Injection Mould

Babalola Akinloluwa Samuel; Duncan Folley

doi:doi:10.11648/j.ijssn.20210901.14

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Design and Construction of a Sensor Analytics System for the Monitoring of the Parameters of a Plastic Injection Mould

Babalola Akinloluwa Samuel, Duncan Folley

Published in International Journal of Sensors and Sensor Networks (Volume 9, Issue 1)

Received: 25 January 2021 Accepted: 2 February 2021 Published: 23 April 2021

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Abstract

Values of parameters such as temperature, humidity, number of plastic products and the location of plastic injection moulds are required to determine the efficiency of plastic injection moulds with a view to improving the quality of the outputs. This article determined the appropriate sensors for the measurement of these essential parameters in the most suitable form of representation of the data to aid a proficient analysis of the data. A network of sensors for the measurement and analysis of the parameters of plastic injection moulds in operation was designed and constructed. The outputs of these sensors were obtained by connecting the sensors to the General-Purpose Input/Output (GPIO) pins of a Raspberry Pi and writing a Python programme for the connected GPIO pins. The values of the outputs of these sensors were represented in graphical form. The connection of the Raspberry Pi and the sensors were done with a full-sized breadboard and jumper wires. A computer-aided design (CAD) of the connections was produced using Fritzing software. The appropriate sensors determined are MLX90614 infrared thermometer sensor, DHT11 humidity sensor, pixy2 vision sensor and Neo-6m GPS sensor. The output values of these sensors were plotted on a graph with the aid of a Python programme. The plastic industry has grown into a very broad industry as plastics are used to manufacture many materials. This makes it essential to ensure the efficiency of the industrial machines used in the making of these plastic products by using sensors to measure the parameters of a plastic injection mould in operation. This study therefore suggested the measurement of industrial plastic injection moulds with the use of the built sensors analytics system for the purpose of understanding and improving the performance of the injection mould.

Published in	International Journal of Sensors and Sensor Networks (Volume 9, Issue 1)
DOI	10.11648/j.ijssn.20210901.14
Page(s)	25-29
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Injection Mould, Sensors, Parameters

References

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APA Style

Babalola Akinloluwa Samuel, Duncan Folley. (2021). Design and Construction of a Sensor Analytics System for the Monitoring of the Parameters of a Plastic Injection Mould. International Journal of Sensors and Sensor Networks, 9(1), 25-29. https://doi.org/10.11648/j.ijssn.20210901.14

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ACS Style

Babalola Akinloluwa Samuel; Duncan Folley. Design and Construction of a Sensor Analytics System for the Monitoring of the Parameters of a Plastic Injection Mould. Int. J. Sens. Sens. Netw. 2021, 9(1), 25-29. doi: 10.11648/j.ijssn.20210901.14

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AMA Style

Babalola Akinloluwa Samuel, Duncan Folley. Design and Construction of a Sensor Analytics System for the Monitoring of the Parameters of a Plastic Injection Mould. Int J Sens Sens Netw. 2021;9(1):25-29. doi: 10.11648/j.ijssn.20210901.14

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@article{10.11648/j.ijssn.20210901.14,
  author = {Babalola Akinloluwa Samuel and Duncan Folley},
  title = {Design and Construction of a Sensor Analytics System for the Monitoring of the Parameters of a Plastic Injection Mould},
  journal = {International Journal of Sensors and Sensor Networks},
  volume = {9},
  number = {1},
  pages = {25-29},
  doi = {10.11648/j.ijssn.20210901.14},
  url = {https://doi.org/10.11648/j.ijssn.20210901.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssn.20210901.14},
  abstract = {Values of parameters such as temperature, humidity, number of plastic products and the location of plastic injection moulds are required to determine the efficiency of plastic injection moulds with a view to improving the quality of the outputs. This article determined the appropriate sensors for the measurement of these essential parameters in the most suitable form of representation of the data to aid a proficient analysis of the data. A network of sensors for the measurement and analysis of the parameters of plastic injection moulds in operation was designed and constructed. The outputs of these sensors were obtained by connecting the sensors to the General-Purpose Input/Output (GPIO) pins of a Raspberry Pi and writing a Python programme for the connected GPIO pins. The values of the outputs of these sensors were represented in graphical form. The connection of the Raspberry Pi and the sensors were done with a full-sized breadboard and jumper wires. A computer-aided design (CAD) of the connections was produced using Fritzing software. The appropriate sensors determined are MLX90614 infrared thermometer sensor, DHT11 humidity sensor, pixy2 vision sensor and Neo-6m GPS sensor. The output values of these sensors were plotted on a graph with the aid of a Python programme. The plastic industry has grown into a very broad industry as plastics are used to manufacture many materials. This makes it essential to ensure the efficiency of the industrial machines used in the making of these plastic products by using sensors to measure the parameters of a plastic injection mould in operation. This study therefore suggested the measurement of industrial plastic injection moulds with the use of the built sensors analytics system for the purpose of understanding and improving the performance of the injection mould.},
 year = {2021}
}

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TY  - JOUR
T1  - Design and Construction of a Sensor Analytics System for the Monitoring of the Parameters of a Plastic Injection Mould
AU  - Babalola Akinloluwa Samuel
AU  - Duncan Folley
Y1  - 2021/04/23
PY  - 2021
N1  - https://doi.org/10.11648/j.ijssn.20210901.14
DO  - 10.11648/j.ijssn.20210901.14
T2  - International Journal of Sensors and Sensor Networks
JF  - International Journal of Sensors and Sensor Networks
JO  - International Journal of Sensors and Sensor Networks
SP  - 25
EP  - 29
PB  - Science Publishing Group
SN  - 2329-1788
UR  - https://doi.org/10.11648/j.ijssn.20210901.14
AB  - Values of parameters such as temperature, humidity, number of plastic products and the location of plastic injection moulds are required to determine the efficiency of plastic injection moulds with a view to improving the quality of the outputs. This article determined the appropriate sensors for the measurement of these essential parameters in the most suitable form of representation of the data to aid a proficient analysis of the data. A network of sensors for the measurement and analysis of the parameters of plastic injection moulds in operation was designed and constructed. The outputs of these sensors were obtained by connecting the sensors to the General-Purpose Input/Output (GPIO) pins of a Raspberry Pi and writing a Python programme for the connected GPIO pins. The values of the outputs of these sensors were represented in graphical form. The connection of the Raspberry Pi and the sensors were done with a full-sized breadboard and jumper wires. A computer-aided design (CAD) of the connections was produced using Fritzing software. The appropriate sensors determined are MLX90614 infrared thermometer sensor, DHT11 humidity sensor, pixy2 vision sensor and Neo-6m GPS sensor. The output values of these sensors were plotted on a graph with the aid of a Python programme. The plastic industry has grown into a very broad industry as plastics are used to manufacture many materials. This makes it essential to ensure the efficiency of the industrial machines used in the making of these plastic products by using sensors to measure the parameters of a plastic injection mould in operation. This study therefore suggested the measurement of industrial plastic injection moulds with the use of the built sensors analytics system for the purpose of understanding and improving the performance of the injection mould.
VL  - 9
IS  - 1
ER  -

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Author Information

Babalola Akinloluwa Samuel

School of Built Environment, Engineering and Computing, Leeds Beckett University, Leeds, United Kingdom
Duncan Folley

School of Built Environment, Engineering and Computing, Leeds Beckett University, Leeds, United Kingdom

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APA Style

Babalola Akinloluwa Samuel, Duncan Folley. (2021). Design and Construction of a Sensor Analytics System for the Monitoring of the Parameters of a Plastic Injection Mould. International Journal of Sensors and Sensor Networks, 9(1), 25-29. https://doi.org/10.11648/j.ijssn.20210901.14

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ACS Style

Babalola Akinloluwa Samuel; Duncan Folley. Design and Construction of a Sensor Analytics System for the Monitoring of the Parameters of a Plastic Injection Mould. Int. J. Sens. Sens. Netw. 2021, 9(1), 25-29. doi: 10.11648/j.ijssn.20210901.14

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AMA Style

Babalola Akinloluwa Samuel, Duncan Folley. Design and Construction of a Sensor Analytics System for the Monitoring of the Parameters of a Plastic Injection Mould. Int J Sens Sens Netw. 2021;9(1):25-29. doi: 10.11648/j.ijssn.20210901.14

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@article{10.11648/j.ijssn.20210901.14,
  author = {Babalola Akinloluwa Samuel and Duncan Folley},
  title = {Design and Construction of a Sensor Analytics System for the Monitoring of the Parameters of a Plastic Injection Mould},
  journal = {International Journal of Sensors and Sensor Networks},
  volume = {9},
  number = {1},
  pages = {25-29},
  doi = {10.11648/j.ijssn.20210901.14},
  url = {https://doi.org/10.11648/j.ijssn.20210901.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssn.20210901.14},
  abstract = {Values of parameters such as temperature, humidity, number of plastic products and the location of plastic injection moulds are required to determine the efficiency of plastic injection moulds with a view to improving the quality of the outputs. This article determined the appropriate sensors for the measurement of these essential parameters in the most suitable form of representation of the data to aid a proficient analysis of the data. A network of sensors for the measurement and analysis of the parameters of plastic injection moulds in operation was designed and constructed. The outputs of these sensors were obtained by connecting the sensors to the General-Purpose Input/Output (GPIO) pins of a Raspberry Pi and writing a Python programme for the connected GPIO pins. The values of the outputs of these sensors were represented in graphical form. The connection of the Raspberry Pi and the sensors were done with a full-sized breadboard and jumper wires. A computer-aided design (CAD) of the connections was produced using Fritzing software. The appropriate sensors determined are MLX90614 infrared thermometer sensor, DHT11 humidity sensor, pixy2 vision sensor and Neo-6m GPS sensor. The output values of these sensors were plotted on a graph with the aid of a Python programme. The plastic industry has grown into a very broad industry as plastics are used to manufacture many materials. This makes it essential to ensure the efficiency of the industrial machines used in the making of these plastic products by using sensors to measure the parameters of a plastic injection mould in operation. This study therefore suggested the measurement of industrial plastic injection moulds with the use of the built sensors analytics system for the purpose of understanding and improving the performance of the injection mould.},
 year = {2021}
}

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TY  - JOUR
T1  - Design and Construction of a Sensor Analytics System for the Monitoring of the Parameters of a Plastic Injection Mould
AU  - Babalola Akinloluwa Samuel
AU  - Duncan Folley
Y1  - 2021/04/23
PY  - 2021
N1  - https://doi.org/10.11648/j.ijssn.20210901.14
DO  - 10.11648/j.ijssn.20210901.14
T2  - International Journal of Sensors and Sensor Networks
JF  - International Journal of Sensors and Sensor Networks
JO  - International Journal of Sensors and Sensor Networks
SP  - 25
EP  - 29
PB  - Science Publishing Group
SN  - 2329-1788
UR  - https://doi.org/10.11648/j.ijssn.20210901.14
AB  - Values of parameters such as temperature, humidity, number of plastic products and the location of plastic injection moulds are required to determine the efficiency of plastic injection moulds with a view to improving the quality of the outputs. This article determined the appropriate sensors for the measurement of these essential parameters in the most suitable form of representation of the data to aid a proficient analysis of the data. A network of sensors for the measurement and analysis of the parameters of plastic injection moulds in operation was designed and constructed. The outputs of these sensors were obtained by connecting the sensors to the General-Purpose Input/Output (GPIO) pins of a Raspberry Pi and writing a Python programme for the connected GPIO pins. The values of the outputs of these sensors were represented in graphical form. The connection of the Raspberry Pi and the sensors were done with a full-sized breadboard and jumper wires. A computer-aided design (CAD) of the connections was produced using Fritzing software. The appropriate sensors determined are MLX90614 infrared thermometer sensor, DHT11 humidity sensor, pixy2 vision sensor and Neo-6m GPS sensor. The output values of these sensors were plotted on a graph with the aid of a Python programme. The plastic industry has grown into a very broad industry as plastics are used to manufacture many materials. This makes it essential to ensure the efficiency of the industrial machines used in the making of these plastic products by using sensors to measure the parameters of a plastic injection mould in operation. This study therefore suggested the measurement of industrial plastic injection moulds with the use of the built sensors analytics system for the purpose of understanding and improving the performance of the injection mould.
VL  - 9
IS  - 1
ER  -

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