Process mining-enhanced quality management in food processing industries

Titelangaben

Loacker, Philipp ; Pöchtrager, Siegfried ; Fikar, Christian ; Grenzfurtner, Wolfgang:
Process mining-enhanced quality management in food processing industries.
In: International Journal of Productivity and Performance Management. (2024) .
ISSN 1758-6658
DOI: https://doi.org/10.1108/IJPPM-06-2024-0377

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Abstract

Changing customer requirements, tightening regulations, and increasing competition are forcing companies in the food processing industry to take measures to improve quality management. Process mining can facilitate the identification of process anomalies in operational processes using real event data, which is significantly more accurate compared to conventional assumptions-based models. The purpose of this study is to present a methodical procedure on how to prepare event logs and analyse them through process mining, statistics, and visualisations. The aim is to derive roots and patterns of quality deviations and non-conforming finished products as well as best practice facilitating employee training. In addition, a data-ecosystem is presented which illustrates a continuous improvement feedback loop and serves as a role model for other applications in the food processing industry. The approach was applied to a real-case study in the processed cheese industry. The findings revealed practical and conceptional contributions which can be used to continuously improve QM in food processing. The developed method contributes to identify tacit knowledge which facilitates the improvement of process standards.