制造业过程挖掘:文献综述

Yuksel Yurtay
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引用次数: 1

摘要

制造过程挖掘是数据挖掘和机器学习技术应用的一个新兴研究领域,也是业务过程研究的热点。尽管它是最近的一个令人兴奋的主题和业务流程,但还没有做足够的研究。决策支持系统,如企业资源规划、客户关系管理和管理信息系统,存储最有价值的流程细节和事件日志资源数据。在未来的先进信息系统中,现代企业的流程管理、分析和建模功能将作为一种必需品取代它们。作为一种需求,流程挖掘在生产中的根本目的是从事件日志中提炼数据,自动创建流程模型,将模型与事件日志进行比较,改进并使开发持续进行。我们的工作是通过提请注意生产背景下的过程采矿来促进应用和研究。它是基于过去十年的文献综述和业务流程挖掘出版物的初级阶段,重点是生产。本文概述了未来研究的路线图,并给出了有意义的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Process Mining in Manufacturing: A Literature Review
Process mining in manufacturing is a newly expanding field of research in the application of data mining and machine learning techniques and the focus of business processes. Although it is an exciting subject of the recent past and business processes, sufficient research has not been done. Decision support systems such as enterprise resource planning, customer relationship management, and management information systems store the most valuable resource data of process details and event logs. In the advanced information systems of tomorrow, the process management, analysis, and modelling functions of modern enterprises will take their place as a necessity. As a requirement, the fundamental purpose of process mining in production is to refine data from event logs, automatically create process models, compare models with event logs, and improve and make development continuous. Our work is to contribute to application and research studies by drawing attention to process mining in the context of production. It is based on the literature review and primary stages of business process mining publications in the last decade with a production focus. An overview is discussed as a roadmap for future research with meaningful results.
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