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At present, the products of the vast majority of smart manufacturing system related manufacturers are mostly aimed at industries where automation machines have been established for many years or have a solid automation foundation. Therefore, the existing products cannot be directly applied to the fields and needs required by many traditional industries. The purpose of this research is to study how to introduce the latest and appropriate information technology, so that traditional enterprises with long-term insufficient information and automation can realize the vision of smart manufacturing, so that enterprises can cope with the problems encountered and maintain advantages in a rapidly changing environment and enhance competitiveness.
This research mainly designs an IoT and cloud system architecture to be applied in a manufacturing plant, transforming the original traditional work pattern into an edge computing device-smart portable device, AR glasses, tablet, etc., that transmit data to cloud servers via the network The data is stored and processed, and then stored in the database. The advantages of using cloud server processing can reduce the burden on edge devices and reduce the power consumption and heat generation of the device. In addition to traditional data collection and monitoring, we also use Google Teachable Machine's technology identifies target images to solve tasks that originally required additional human resources in the factory. Through the application of this research, the labor cost of traditional factories can be reduced and data can be digitized, transforming traditional manufacturing factories into smart manufacturing factories.
The main contribution of this research is that we design a system to solve the problem of combining things and people in smart manufacturing systems.
The current industrial IoT applications and technologies focus on connecting devices and equipment. However, from raw materials to the front of the factory, On-site personnel processing and subsequent processes all need to be able to connect things, processes, and people together. Through the integration of IoT technology and augmented reality technology, we allow raw materials to collect relevant information from the entry point and automatically enter it into the information collection platform. We will also implement a sensor module that can be carried on the factory personnel. By integrating IoT control modules, personnel, process, environmental information and operation records are automatically collected. With the support of the big data analysis platform, the optimized process can be analyzed from these long-term aggregated data in the future, and a dispatch system can remind and dispatch personnel to complete the work.
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