1、 Construction of a data collection system for work in progress products
Core data dimension
Identity identification data assigns a unique identifier (such as barcode, RFID tag, QR code) to each work in progress, binding basic information such as product model, batch, and process route. For example, in the production of automotive parts, each cylinder block is assigned a unique ID through laser coding, which is associated with its engine model and processing flow.
Real time collection of location status data, including the entry and exit time, dwell time, equipment number, and operator information of work in progress in each process. By using workstation sensors (such as photoelectric switches, RFID readers) or manually scanning codes, record the full path movement trajectory of the work in progress from online to offline.
Process parameter data integration equipment control system automatically captures process parameters related to work in progress (such as temperature, pressure, speed, feed rate, etc.). For example, in the injection molding workshop, the MES system obtains real-time data such as the mold closing pressure and melt adhesive temperature of the injection molding machine, which is bound and stored with the work in progress ID.
Quality inspection data is set at inspection nodes in key processes, and inspection results such as dimensional accuracy, appearance defects, and performance indicators of work in progress are collected through manual input or online detection equipment (such as visual inspection systems and coordinate measuring instruments), and marked as qualified/unqualified status.
2、 Diversified collection technology
automatic identification technology
RFID radio frequency identification: suitable for harsh environments such as high temperature and dust (such as casting workshops), it can quickly identify in batches by non-contact reading of work in progress tag information through fixed readers installed on both sides of the production line.
Visual recognition (QR code/barcode): In precision workshops such as electronic assembly, high-definition cameras are used to scan the QR code on the surface of the product to obtain real-time position and process information, with an accuracy of up to 0.1mm.
IoT sensors: Install IoT sensors (such as GPS, Bluetooth beacons) on product trays or fixtures, track their spatial position in real time through workshop positioning base stations, and control the positioning error within 0.5 meters.
Manual assisted collection is performed at non automated workstations (such as manual assembly processes), where operators scan work in progress labels using PDA handheld terminals, manually enter process start/end times, equipment switching status, and other information, and the system automatically associates them with corresponding production tasks.
Implementation of Dynamic Tracking Technology for Work in Progress
Real time location tracking
Workstation level positioning is achieved by installing sensors or read-write devices at each production workstation to accurately determine whether the work in progress has arrived at that workstation. For example, in a machining production line, when a work in progress enters a CNC machine station with a conveyor belt, the photoelectric sensor triggers a signal, and the MES system updates its position status to "processing in progress".
Build a virtual workshop map in the MES system using workshop level visualization maps, dynamically displaying the distribution of work in progress with different colored icons (such as green indicating to be processed, yellow indicating in progress, and red indicating to be inspected). Click on the icon to view detailed process parameters, dwell time, and abnormal records of the work in progress.
SUMMARY
With the rapid development of smart manufacturing, enterprises are facing unprecedented opportunities and challenges. In such a wave of digital transformation, how to enhance production efficiency and optimize management processes has become an important issue that every enterprise must address. As a key driver of industrial upgrading, smart manufacturing has become an important engine for industry development and improving enterprise competitiveness.
Against this backdrop, Xinhaizhichiao, with its profound technological expertise and rich industry experience, continues to provide leading IoT technologies, smart manufacturing solutions, and MES/MOM/APS systems to customers. Our solutions cover all aspects from the production site to enterprise management, helping businesses achieve more flexible and intelligent production models while improving production efficiency and reducing costs.
As a technological leader in the industry, Xinhaizhichiao continues to promote the deep integration of digital transformation and smart manufacturing, dedicated to providing the most competitive solutions for the global manufacturing industry. We will continue to adhere to the core concept of “Innovation Driven, Smart Manufacturing,” assisting our clients in standing out in the fierce market competition and staying at the forefront of industry development.
If you would like to learn more about smart manufacturing or discuss how to enhance your business efficiency through digital transformation, please feel free to contact us. Xinhaizhichiao is committed to providing you with comprehensive technical support and services, working hand in hand with you to embrace the new era of smart manufacturing.
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