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Fault Detection Techniques for Process Parameter Monitoring in Dairy Milk and Cream Fat In-Line Standardization: A Comparative Analysis

Anjou, Jacob LU and Wallin, Alexandra LU (2025) In CODEN:LUTEDX/TEIE EIEM01 20251
Industrial Electrical Engineering and Automation
Abstract (Swedish)
Detecting and recognizing when there is a deviation in process behavior is a crucial aspect of industrial automation. This study investigates one such deviation, a volume discrepancy accidentally introduced during the commissioning of a Tetra Pak Standardization Unit (TPSU). The analysis aims to develop theory for a future implementation with the purpose of detecting this deviation by evaluating principal component analysis-based (PCA-based) detection methods and frequency spectrum analysis (FSA). The comparison focuses on the accuracy, validity, reliability,
and feasibility of the detection methods. Results demonstrate that FSA is the most promising method and two approaches to implementation are proposed, evaluating the strengths and... (More)
Detecting and recognizing when there is a deviation in process behavior is a crucial aspect of industrial automation. This study investigates one such deviation, a volume discrepancy accidentally introduced during the commissioning of a Tetra Pak Standardization Unit (TPSU). The analysis aims to develop theory for a future implementation with the purpose of detecting this deviation by evaluating principal component analysis-based (PCA-based) detection methods and frequency spectrum analysis (FSA). The comparison focuses on the accuracy, validity, reliability,
and feasibility of the detection methods. Results demonstrate that FSA is the most promising method and two approaches to implementation are proposed, evaluating the strengths and limitations of each approach. This work acts as a guide and framework for Tetra Pak to use during a potential future implementation and provides insights into necessary future work. (Less)
Please use this url to cite or link to this publication:
author
Anjou, Jacob LU and Wallin, Alexandra LU
supervisor
organization
alternative title
Feldetekteringsmetoder vid övervakning av processparametrar i in-line standardisering av fett i mjölk och grädde: En jämförande studie
course
EIEM01 20251
year
type
H3 - Professional qualifications (4 Years - )
subject
keywords
Fault Detection, Principal Component Analysis, Frequency Spectrum Analysis, Q residual, Hotelling, Parameter monitoring
publication/series
CODEN:LUTEDX/TEIE
report number
5547
language
English
id
9205322
date added to LUP
2025-06-26 09:29:33
date last changed
2025-06-30 13:43:44
@misc{9205322,
  abstract     = {{Detecting and recognizing when there is a deviation in process behavior is a crucial aspect of industrial automation. This study investigates one such deviation, a volume discrepancy accidentally introduced during the commissioning of a Tetra Pak Standardization Unit (TPSU). The analysis aims to develop theory for a future implementation with the purpose of detecting this deviation by evaluating principal component analysis-based (PCA-based) detection methods and frequency spectrum analysis (FSA). The comparison focuses on the accuracy, validity, reliability,
and feasibility of the detection methods. Results demonstrate that FSA is the most promising method and two approaches to implementation are proposed, evaluating the strengths and limitations of each approach. This work acts as a guide and framework for Tetra Pak to use during a potential future implementation and provides insights into necessary future work.}},
  author       = {{Anjou, Jacob and Wallin, Alexandra}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{CODEN:LUTEDX/TEIE}},
  title        = {{Fault Detection Techniques for Process Parameter Monitoring in Dairy Milk and Cream Fat In-Line Standardization: A Comparative Analysis}},
  year         = {{2025}},
}