AI 中文总结
研究利用数据库知识发现方法开发分析模型，作为工业4.0基础设施中数字化资产，以优化大豆油提纯过程，为相关专业人员利用数据优化该工业过程提供了关键模型。
AI 中文摘要
机器学习、人工智能等是在数字化生态系统中实现广泛分析的新兴且极有前景的方法和技术。包含适当分析模型的分析正引发商业智能、信息技术和运营技术专业人员的浓厚兴趣，他们能利用数字化组件、系统及其相关流程背后的大量内外部可用数据和信息。本文作者介绍了应用数据库知识发现（KDD）方法开发和实施的分析模型的基本规范。该分析模型是分析组件的关键部分，作为符合工业4.0（RAMI 4.0）基础设施的数字化资产，用于优化与数字化生态系统相关的工业大豆油提纯过程。
英文摘要
Machine Learning, Artificial Intelligence, among others, are very promising methodologies and technologies that are emerging for implementing a broad spectrum of analytics within digitalized eco-systems. Analytics containing adequate analytical models are generating a burgeoning interest from Business Intelligence-, Information Technology (IT)- and Operational Technology (OT)-professionals, who are able to exploit the huge amount of internally and externally available data and information that lies behind digitalized components and systems and their associated processes. In this paper, the authors present the essential specifications of an analytical model developed and implemented applying the Knowldege Discovery in Databases (KDD) approach. The analytical model is the essential part of an analytics component, positioned as an digitalized asset within an Industry 4.0 compliant (RAMI 4.0) infrastructure, and used to optimize the industrial Soybean Oil Purification Process associated to the digitalized eco-system.
CommentsThis is the author's accepted version of a paper published in: IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society
Journal refIECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society
DOI：10.1109/IECON51785.2023.10312235
