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Clarifying Data Analytics Concepts for Industrial Engineering

机译:澄清工业工程的数据分析概念

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In the last decade manufacturing experienced a shift towards digitalization. Cost decrease of sensors, wireless connectivity, and the opportunity to store big amounts of data pushed a process towards a next generation of IT industry. Manufacturing now has the opportunity to gather large quantities of data, coming from different areas, such as product and process design, assembly, material planning, quality control, scheduling, maintenance, fault detection and cover all the product life cycle phases. The extraction of value from data is a new challenge that companies are now experiencing. Therefore, the need for analytical information system is growing, in order to explore datasets and discover useful and often hidden information. Data analytics became a keyword in this context, but sometimes it is not clear how different methods or tools are defined and could be effectively used to analyze data in manufacturing. The paper aims to present and clarify the meaning of terms that are currently and frequently used in the context of analytics. The paper also provides an overview of the data analysis techniques that could be used to extract knowledge from data along the manufacturing process.
机译:在过去的十年中,制造业经历了向数字化的转变。传感器成本的降低,无线连接性以及存储大量数据的机会将流程推向了下一代IT行业。制造业现在有机会收集来自不同领域的大量数据,例如产品和过程设计,组装,材料计划,质量控制,调度,维护,故障检测,并涵盖所有产品生命周期阶段。从数据中提取价值是公司现在正面临的新挑战。因此,对分析信息系统的需求正在增长,以便探索数据集并发现有用的且通常是隐藏的信息。在这种情况下,数据分析成为关键词,但有时不清楚如何定义不同的方法或工具,以及如何有效地使用这些方法或工具来分析制造业中的数据。本文旨在介绍和阐明在分析环境中当前和经常使用的术语的含义。本文还概述了可用于在制造过程中从数据中提取知识的数据分析技术。

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