The recently – concluded CES 2026 has clearly indicated that AI is moving from the “concept era” to the “implementation era”. This trend brings significant opportunities for the mold industry, and AI is expected to play a crucial role in promoting its development.
AI can greatly optimize mold design. It can automatically recognize geometric features through machine – learning algorithms, and complete parametric modeling. According to the process data provided by users, intelligent design engines such as Agle Mold can automatically extract key parameters and generate the structure of core components, which improves the design efficiency. Moreover, by integrating CAE simulation data, AI can construct a closed – loop of “design – simulation – optimization”, automatically recommend mold structures and materials, and reduce the number of design iterations.
In terms of production scheduling, AI is also a powerful assistant. The mold manufacturing process is complex, involving multiple processes and equipment, and traditional scheduling methods are often inefficient. AI, based on advanced planning and scheduling (APS) technology and large – model algorithms, can take into account various factors such as order priority, equipment capacity, and delivery time, and generate an optimal production plan in a short time. For example, the MoldIQ Engine can achieve intelligent scheduling and dynamic adjustment in minutes, which improves production efficiency and equipment utilization.
AI – enabled automatic quotation is another highlight. Traditional mold quotation requires engineers to spend a lot of time calculating costs, but AI can change this situation. By automatically reading 2D or 3D drawings, extracting key information, and combining with a large – scale process database, AI can quickly generate accurate quotation plans. For example, the AI intelligent quotation system of Modbao can generate a quotation in dozens of minutes, with an efficiency increase of more than 10 times compared with the traditional mode.
In quality inspection, AI has obvious advantages. Using deep – learning algorithms, AI visual inspection systems can quickly and accurately identify defects such as cracks, wear, and dimensional deviations on the mold surface. Compared with manual inspection, it has higher efficiency and accuracy, and can also detect some tiny defects that are difficult to be found by the human eye.
In addition, AI can also realize predictive maintenance of molds. Through the Internet of Things sensors, the cloud – based system collects data such as mold pressure, temperature, and wear, and uses machine – learning algorithms to build a digital twin model, which can predict the mold life and provide early warnings of failures, helping enterprises arrange maintenance plans in advance and reduce sudden downtime losses.
Overall, AI has a broad application prospect in the mold industry. It can improve the efficiency and quality of mold design and manufacturing, reduce costs, and enhance the competitiveness of enterprises. We, as a professional mold factory, are committed to applying these advanced AI technologies to actual production, providing customers with more high – quality, efficient, and intelligent mold products and services. Welcome customers with relevant needs to связаться с нами for discussion, and we look forward to creating a better future with you in the era of AI.
