| Smart factory is an important part of Industrialization 4.0,which aims to solve the problem of lack of bidirectional connection and interoperability between the enterprise layer,the bottom layer of the workshop and the machine layer in traditional manufacturing.In the traditional manufacturing industry,the information is not smooth,resulting in a lack of decision-making information.The work and innovation done by the thesis include the following six points:1.Designed and implemented a smart factory system suitable for small and medium-sized manufacturing around the key technologies of smart factories,using Radio Frequency Identification(RFID)technology for data collection at the perception layer,and OPC Unified Architecture(OPC UA)technology.2.Aiming at the problem of low inventory management efficiency,an inventory management scheme based on RFID technology is designed.After testing,the scheme effectively improves the efficiency of inventory management,reducing the time taken for product entry and exit by about 75.9%.3.Aiming at the problem of the lack of position information of products in the warehouse,based on the RFID signal model,the algorithm for positioning based on Received Signal Strength Indication(RSSI)is analyzed,and the indoor positioning algorithm using reference tags is proposed and optimized.After testing,the accuracy of the algorithm reaches 91%,and the complexity of the model is low,so the calculation pressure is small.4.In view of the lack of information in the production process,a data acquisition network solution based on OPC UA is proposed.This solution can accurately read and write various parameters in the production process,which improves the interoperability of the production layer and the enterprise layer and the interconnection between the equipment.5.Based on the aforementioned three basic components,the order system and the enterprise layer are built to reduce human intervention in the production process.6.The smart factory operation test was completed.The test results show that the solution proposed in this article can efficiently complete production data collection and warehouse management.The average time taken for order completion is reduced by about 58.5%compared with before system deployment. |
