Digital Design and Manufacturing major learning content is as follows:

Product CADCAE technology applications, reverse engineering, industrial product design, 3D printing technology applications, industrial product testing technology, material molding process and mold design, precision high-speed machining and multi-axis linkage processing, project management, reverse engineering, Robot Operation and Maintenance, Mold Parts Processing and Automation, 3D Digital Design, Basic Mechanical Design and Manufacturing, and other courses.

Knowledge Expansion:

Digital technology and manufacturing technology are important concepts in the modern industrial field, and they ****together promote the intelligent and efficient development of manufacturing. Digital technology is a method of digitally representing, analyzing, and managing physical entities, processes, and data through digital means, while manufacturing technology is a method and process of machining and assembling materials, parts, and components into a final product.

I. Digital technology:

Digital technology includes a number of aspects such as computer technology, information technology and communication technology, and their application in the manufacturing field is known as digital manufacturing, intelligent manufacturing or Industry 4.0.

II. Main features include:

1, digital design and simulation: using computer-aided design (CAD) software, product design, simulation and optimization can be carried out in a digital environment, which reduces the cost and time of making physical prototypes.

2, digital manufacturing: digital manufacturing includes computer numerical control (CNC) machine tool (CNC) technology, additive manufacturing (3D printing), laser cutting, etc., and realizes high-precision and high-efficiency production process through digital control and automation.

3, Internet of Things (IoT) technology: IoT connects sensors, devices and products together to achieve real-time data collection and interconnection, thus enabling monitoring, optimization and predictive maintenance of the production process.

4, Big Data Analytics: Through large-scale analysis of production process and product data, hidden correlations and trends can be identified, providing data-supported decision-making.

5, Artificial Intelligence and Machine Learning: The use of artificial intelligence technology can equip machines with the ability to learn and make intelligent decisions, enhancing the automation and intelligence of the production line.