Morris K C, Lu Yan, Frechette Simon
National Institute of Standards and Technology, Gaithersburg, MD 20899, USA.
Smart Sustain Manuf Syst. 2020;4(2). doi: 10.1520/ssms20190041.
The manufacturing systems of the future will be even more dependent on data than they are today. More and more data and information are being collected and communicated throughout product development lifecycles and across manufacturing value chains. To enable smarter manufacturing operations, new equipment often includes built-in data collection capabilities. Older equipment can be retrofitted inexpensively with sensors to collect a wide variety of data. Many manufacturers are in a quandary as to what to do with increasing quantities of data. Much hype currently surrounds the use of AI to process large data sets, but manufacturers struggle to understand how AI can be applied to improve manufacturing system performance. The gap lies in the lack of good information governance practices for manufacturing. This paper defines information governance in the manufacturing context as the set of principles that allow for consistent, repeatable, and trustworthy processing and use of data. The paper identifies three foundations for good information governance that are needed in the manufacturing environment-data quality, semantic context, and system context-and reviews the surrounding and evolving body of work. The work includes a broad base of standard methods that combines to create reusable information from raw data formats. An example from an additive manufacturing case study is used to show how those detailed specifications create the governance needed to build trust in the systems.
未来的制造系统将比现在更加依赖数据。在整个产品开发生命周期以及制造价值链中，越来越多的数据和信息正在被收集和传递。为了实现更智能的制造运营，新设备通常具备内置的数据收集功能。旧设备可以通过廉价地加装传感器来收集各种各样的数据。许多制造商对于如何处理日益增多的数据感到困惑。目前，人工智能在处理大型数据集方面备受炒作，但制造商们难以理解如何将人工智能应用于提高制造系统性能。差距在于缺乏适用于制造业的良好信息治理实践。本文将制造业背景下的信息治理定义为一套原则，这些原则允许对数据进行一致、可重复且可靠的处理和使用。本文确定了制造环境中良好信息治理所需的三个基础——数据质量、语义上下文和系统上下文——并回顾了相关的以及不断发展的工作。这项工作包括广泛的标准方法基础，这些方法结合起来可以从原始数据格式创建可重复使用的信息。一个增材制造案例研究的例子被用来展示这些详细规范如何创建建立系统信任所需的治理。
