Data-driven water-efficient production scheduling in the food industry

Sai Jishna Pulluru; Renzo Akkerman

doi:10.1016/B978-0-444-64235-6.50186-8

Data-driven water-efficient production scheduling in the food industry

Sai Jishna Pulluru
, Renzo Akkerman

Technical University of Munich
Wageningen University and Research Centre

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

Abstract

Reuse and regeneration of water is becoming increasingly important in the food industry. Planning both water reuse and production while at the same time ensuring food safety is a challenge. We propose a novel scheduling methodology to simultaneously plan water reuse and production in food production processes utilizing real time water quality data. We develop a two-stage predictive scheduling and reactive scheduling approach taking into account the dynamic nature of water quality. Overall, our approach can prevent undesired contamination of food products due to reuse of water and achieve higher water efficiency.

Original language	English
Title of host publication	Computer Aided Chemical Engineering
Editors	Anton Friedl, Jiří J. Klemeš, Stefan Radl, Petar S. Varbanov, Thomas Wallek
Publisher	Elsevier B.V.
Pages	1063-1068
Number of pages	6
ISBN (Print)	9780444642356
DOIs	https://doi.org/10.1016/B978-0-444-64235-6.50186-8
State	Published - 1 Jan 2018
Externally published	Yes

Publication series

Name	Computer Aided Chemical Engineering
Volume	43
ISSN (Print)	1570-7946

UN SDGs

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

SDG 2 Zero Hunger

Keywords

data driven approach
food industry
online water quality measurement
real-time scheduling
water efficiency

Access to Document

10.1016/B978-0-444-64235-6.50186-8

Cite this

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title = "Data-driven water-efficient production scheduling in the food industry",

abstract = "Reuse and regeneration of water is becoming increasingly important in the food industry. Planning both water reuse and production while at the same time ensuring food safety is a challenge. We propose a novel scheduling methodology to simultaneously plan water reuse and production in food production processes utilizing real time water quality data. We develop a two-stage predictive scheduling and reactive scheduling approach taking into account the dynamic nature of water quality. Overall, our approach can prevent undesired contamination of food products due to reuse of water and achieve higher water efficiency.",

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Data-driven water-efficient production scheduling in the food industry. / Pulluru, Sai Jishna; Akkerman, Renzo.
Computer Aided Chemical Engineering. ed. / Anton Friedl; Jiří J. Klemeš; Stefan Radl; Petar S. Varbanov; Thomas Wallek. Elsevier B.V., 2018. p. 1063-1068 (Computer Aided Chemical Engineering; Vol. 43).

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

TY - CHAP

T1 - Data-driven water-efficient production scheduling in the food industry

AU - Pulluru, Sai Jishna

AU - Akkerman, Renzo

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Reuse and regeneration of water is becoming increasingly important in the food industry. Planning both water reuse and production while at the same time ensuring food safety is a challenge. We propose a novel scheduling methodology to simultaneously plan water reuse and production in food production processes utilizing real time water quality data. We develop a two-stage predictive scheduling and reactive scheduling approach taking into account the dynamic nature of water quality. Overall, our approach can prevent undesired contamination of food products due to reuse of water and achieve higher water efficiency.

AB - Reuse and regeneration of water is becoming increasingly important in the food industry. Planning both water reuse and production while at the same time ensuring food safety is a challenge. We propose a novel scheduling methodology to simultaneously plan water reuse and production in food production processes utilizing real time water quality data. We develop a two-stage predictive scheduling and reactive scheduling approach taking into account the dynamic nature of water quality. Overall, our approach can prevent undesired contamination of food products due to reuse of water and achieve higher water efficiency.

KW - data driven approach

KW - food industry

KW - online water quality measurement

KW - real-time scheduling

KW - water efficiency

UR - https://www.scopus.com/pages/publications/85049301189

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M3 - Chapter

AN - SCOPUS:85049301189

SN - 9780444642356

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EP - 1068

BT - Computer Aided Chemical Engineering

A2 - Friedl, Anton

A2 - Klemeš, Jiří J.

A2 - Radl, Stefan

A2 - Varbanov, Petar S.

A2 - Wallek, Thomas

PB - Elsevier B.V.

ER -

Data-driven water-efficient production scheduling in the food industry

Abstract

Publication series

UN SDGs

Keywords

Access to Document

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