A Cyber-Physical System for Zero-Defect Production in Aquaponics 4.0 Learning Factory

Rafiq Ahmad; Rabiya Abbasi; Pablo Martinez Rodriguez

doi:10.2139/ssrn.4469132

A Cyber-Physical System for Zero-Defect Production in Aquaponics 4.0 Learning Factory

Rafiq Ahmad^*, Rabiya Abbasi, Pablo Martinez Rodriguez

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Aquaponics is a sustainable fish and plant production process in an indoor ecosystem. Recent development in aquaponics has led to the development of new automated technologies which can serve in high automation, efficiency, and waste minimization. Zero-defect production systems are key to high quality in a production environment where cyber-physical systems, data acquisition, and decision-making are paramount. This paper presents a novel framework based on a cyber-physical systems (CPS) architecture that provides data acquisition, data analytics, and data storage that supports defect damage detection and identification parameters optimizations to create an autonomous aquaponics production system. The proposed method is implemented and validated in the context of an indoor aquaponics environment with a full factory setup created in aquaponics 4.0 learning factory (AllFactory).

Original language	English
Title of host publication	Proceedings of the 13th Conference on Learning Factories (CLF 2023)
Place of Publication	Amsterdam, Netherlands
Publisher	Elsevier
Pages	1-6
Number of pages	6
DOIs	https://doi.org/10.2139/ssrn.4469132
Publication status	Published - 5 Jun 2023
Event	13th CIRP Conference on Learning Factories - ESB Business School, Reutlingen University, Reutlingen, Germany Duration: 9 May 2023 → 11 May 2023 https://www.clf2023.com/

Conference

Conference	13th CIRP Conference on Learning Factories
Abbreviated title	CLF 2023
Country/Territory	Germany
City	Reutlingen
Period	9/05/23 → 11/05/23
Internet address	https://www.clf2023.com/

Keywords

zero-defect manufacturing
industry 4.0
aquaponics
cyber-physical production system

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.2139/ssrn.4469132

Cite this

@inproceedings{62a196fe29a8430892ab1b0ba4a30f39,

title = "A Cyber-Physical System for Zero-Defect Production in Aquaponics 4.0 Learning Factory",

abstract = "Aquaponics is a sustainable fish and plant production process in an indoor ecosystem. Recent development in aquaponics has led to the development of new automated technologies which can serve in high automation, efficiency, and waste minimization. Zero-defect production systems are key to high quality in a production environment where cyber-physical systems, data acquisition, and decision-making are paramount. This paper presents a novel framework based on a cyber-physical systems (CPS) architecture that provides data acquisition, data analytics, and data storage that supports defect damage detection and identification parameters optimizations to create an autonomous aquaponics production system. The proposed method is implemented and validated in the context of an indoor aquaponics environment with a full factory setup created in aquaponics 4.0 learning factory (AllFactory).",

keywords = "zero-defect manufacturing, industry 4.0, aquaponics, cyber-physical production system",

author = "Rafiq Ahmad and Rabiya Abbasi and \{Martinez Rodriguez\}, Pablo",

year = "2023",

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language = "English",

pages = "1--6",

booktitle = "Proceedings of the 13th Conference on Learning Factories (CLF 2023)",

publisher = "Elsevier",

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note = "13th CIRP Conference on Learning Factories, CLF 2023 ; Conference date: 09-05-2023 Through 11-05-2023",

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}

Ahmad, R, Abbasi, R & Martinez Rodriguez, P 2023, A Cyber-Physical System for Zero-Defect Production in Aquaponics 4.0 Learning Factory. in Proceedings of the 13th Conference on Learning Factories (CLF 2023). Elsevier, Amsterdam, Netherlands, pp. 1-6, 13th CIRP Conference on Learning Factories, Reutlingen, Baden-Württemberg, Germany, 9/05/23. https://doi.org/10.2139/ssrn.4469132

TY - GEN

T1 - A Cyber-Physical System for Zero-Defect Production in Aquaponics 4.0 Learning Factory

AU - Ahmad, Rafiq

AU - Abbasi, Rabiya

AU - Martinez Rodriguez, Pablo

PY - 2023/6/5

Y1 - 2023/6/5

N2 - Aquaponics is a sustainable fish and plant production process in an indoor ecosystem. Recent development in aquaponics has led to the development of new automated technologies which can serve in high automation, efficiency, and waste minimization. Zero-defect production systems are key to high quality in a production environment where cyber-physical systems, data acquisition, and decision-making are paramount. This paper presents a novel framework based on a cyber-physical systems (CPS) architecture that provides data acquisition, data analytics, and data storage that supports defect damage detection and identification parameters optimizations to create an autonomous aquaponics production system. The proposed method is implemented and validated in the context of an indoor aquaponics environment with a full factory setup created in aquaponics 4.0 learning factory (AllFactory).

AB - Aquaponics is a sustainable fish and plant production process in an indoor ecosystem. Recent development in aquaponics has led to the development of new automated technologies which can serve in high automation, efficiency, and waste minimization. Zero-defect production systems are key to high quality in a production environment where cyber-physical systems, data acquisition, and decision-making are paramount. This paper presents a novel framework based on a cyber-physical systems (CPS) architecture that provides data acquisition, data analytics, and data storage that supports defect damage detection and identification parameters optimizations to create an autonomous aquaponics production system. The proposed method is implemented and validated in the context of an indoor aquaponics environment with a full factory setup created in aquaponics 4.0 learning factory (AllFactory).

KW - zero-defect manufacturing

KW - industry 4.0

KW - aquaponics

KW - cyber-physical production system

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DO - 10.2139/ssrn.4469132

M3 - Conference contribution

SP - 1

EP - 6

BT - Proceedings of the 13th Conference on Learning Factories (CLF 2023)

PB - Elsevier

CY - Amsterdam, Netherlands

T2 - 13th CIRP Conference on Learning Factories

Y2 - 9 May 2023 through 11 May 2023

ER -