Process mining-enhanced quality management in food processing industries

IF 3.6 Q2 MANAGEMENT
Philipp Loacker, Siegfried Pöchtrager, Christian Fikar, Wolfgang Grenzfurtner
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引用次数: 0

Abstract

Purpose

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 the food processing industry. Thereby, a key focus is on recognising tacit knowledge hidden in event logs to improve quality processes.

Design/methodology/approach

This study applied process mining to detect root causes of quality deviations in operational process of food production. In addition, a data-ecosystem was developed 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.

Findings

The findings revealed practical and conceptional contributions which can be used to continuously improve quality management (QM) in food processing. Thereby, the developed data-ecosystem supports production and QM in the decision-making processes. The findings of the analysis are a valuable basis to enhance operational processes, aiming to prevent quality deviations and non-conforming finished products.

Originality/value

Process mining is still rarely used in the food industry. Thereby, the proposed method helps to identify tacit knowledge in the food processing industry, which was shown by the framework for the preparation of event logs and the data ecosystem.

食品加工业的流程挖掘--强化质量管理
本研究的目的是介绍如何准备事件日志并通过流程挖掘、统计和可视化对其进行分析的方法步骤。目的是找出质量偏差和不合格成品的根源和模式,以及促进食品加工业员工培训的最佳做法。因此,重点在于识别隐藏在事件日志中的隐性知识,以改进质量流程。 设计/方法/途径 本研究应用流程挖掘来检测食品生产操作流程中质量偏差的根本原因。此外,还开发了一个数据生态系统,该系统展示了一个持续改进的反馈回路,并可作为食品加工行业其他应用的榜样。研究结果研究结果揭示了可用于持续改进食品加工质量管理(QM)的实用性和概念性贡献。因此,所开发的数据生态系统可在决策过程中为生产和质量管理提供支持。分析结果是改进操作流程的重要依据,旨在防止质量偏差和不合格成品。因此,所提出的方法有助于识别食品加工业中的隐性知识,事件日志和数据生态系统的准备框架就体现了这一点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.90
自引率
9.70%
发文量
87
期刊介绍: ■Organisational design and methods ■Performance management ■Performance measurement tools and techniques ■Process analysis, engineering and re-engineering ■Quality and business excellence management Articles can address these topics theoretically or empirically through either a descriptive or critical approach. The co-Editors support articles that significantly bring new knowledge to the area both for academics and practitioners. The material for publication in IJPPM should be written in a manner which makes it accessible to its entire wide-ranging readership. Submissions of highly technical or mathematically-oriented papers are discouraged.
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