Industry pain point
Slow response: traditional workshops are usually slow to respond, and the production line cannot be adjusted in time in the face of rapid changes in the market and demand.
Inefficient resource allocation: Lack of insight into the whole production process leads to inefficient resource allocation, such as low utilization rate of raw materials and equipment.
Opaque production process: Without real-time monitoring and analysis, the uncertainty of production process increases, making it difficult to control quality and process finely.
Frequent equipment failures: due to the lack of intelligent maintenance strategy, equipment failures often lead to the stagnation of the production line and affect the overall efficiency.
Construction scheme of digital double factory building
Demand analysis and planning stage: firstly, it is necessary to carry out in-depth demand analysis on the existing production workshops, including understanding the current equipment capacity, production technology, product line and the proficiency of workshop operators, and then plan the appropriate digital double-workshop construction scheme.
Integrating the Internet of Things and sensor technology: install sensors in key equipment and areas of the workshop to collect real-time data, including the running status of production equipment, environmental conditions, workpiece quality and other information. This step is very important to realize digital twinning.
Establishing digital twin model: using the collected data, combining with advanced CAD and simulation software, establishing digital twin model. The model should reflect the physical state of the workshop in real time and can be used to test different production strategies and configurations.
Development of integrated analysis platform: Building a powerful data processing and analysis platform, usually using big data and cloud computing technology, can analyze and visualize the data in real time, which is helpful to better understand the production process and implement rapid decision-making.
Testing, optimization and deployment: Test and optimize the digital twin model for many times until the virtual state can reflect the entity state, and ensure that the improved process can bring the expected benefits. After that, the optimized scheme is deployed to the actual production workshop.
Smart workshops will become more convenient, and such smart factories will bring economic benefits, stable production quality and faster market response to enterprises. The construction of digital double factory workshop needs a deep understanding of modern information technology and automation technology, as well as a careful study of the production process. It is not out of reach to combine these technologies, deeply analyze and establish an intelligent production workshop. With more and more enterprises adopting digital twin technology, we have reason to believe that the digital future will be even better.