Harnessing IoT Data and Knowledge in Smart Manufacturing

Joseph S. M. Yuen, K. Choy, Y. Tsang, H. Y. Lam
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Abstract

In the modern digitalized era, the use of electronic devices is a necessity in daily life, with most end users requiring high product quality of these devices. During the electronics manufacturing process, environmental control, for monitoring ambient temperature and relative humidity, is one of the critical elements affecting product quality. However, the manufacturing process is complicated and involves numerous sections, such as processing workshops and storage facilities. Each section has its own specific requirements for environmental conditions, which are checked regularly and manually, such that the whole environmental control process becomes time-consuming and inefficient. In addition, the reporting mechanism when conditions are out of specification is done manually at regular intervals, resulting in a certain likelihood of serious quality deviation. There is a substantial need for improving knowledge management under smart manufacturing for full integration of Internet of Things (IoT) data and manufacturing knowledge. In this chapter, an Internet-of-Things Quality Prediction System (IQPS), which is a mission critical system in electronics manufacturing, is proposed in adopting the advanced IoT technologies to develop a real-time environmental monitoring scheme in electronics manufacturing. By deploying IQPS, the total intelligent environmental monitoring is achieved, while product quality is predicted in a systematic manner.
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在智能制造中利用物联网数据和知识
在现代数字化时代,电子设备的使用是日常生活的必需品,大多数终端用户对这些设备的产品质量要求很高。在电子产品制造过程中,环境控制是影响产品质量的关键因素之一,用于监测环境温度和相对湿度。然而,制造过程是复杂的,涉及许多部分,如加工车间和储存设施。每个工段对环境条件都有自己的具体要求,需要定期手工检查,使得整个环境控制过程变得费时低效。此外,当条件不符合规范时,报告机制是定期手动完成的,这导致了严重质量偏差的一定可能性。为实现物联网数据与制造知识的充分融合,智能制造下的知识管理亟待完善。本章提出了采用先进的物联网技术开发电子制造环境实时监测方案的物联网质量预测系统(IQPS),这是电子制造中的关键任务系统。通过部署IQPS,实现了对环境的全面智能监测,同时对产品质量进行了系统的预测。
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