Scientific injection molding visualization technology

Abstract

The invention provides a scientific injection molding visualization technology which comprises a design stage, a mold testing stage and a volume production stage. In the design stage, the product structure and mold design can be optimized through mold flow analysis technology (CAE emulation technology). In the mold testing stage, injection molding technological parameters are gradually tested andoptimized through a scientific injection molding seven-step method, the scientific injection molding seven-step method comprises viscosity curve testing, mold cavity balance testing, pressure drop testing, process window testing, sprue freezing testing, clamping force testing and cooling time testing, and scientific and reasonable injection molding technological parameters can be obtained throughthe scientific injection molding seven-step method; by means of staged injection molding forming technology, products which are more even in volume shrinkage rate, smaller in deformation and more stable in production are obtained; and by means of mold cavity pressure and temperature measure technology, the injection molding forming technology is optimized, real-time quality monitoring is conductedon injection molding production, and thus, unmanned automatic injection molding production is achieved.

Description

technical field [0001] The invention relates to the technical field of injection molding, in particular to a scientific injection molding visualization technology capable of realizing automatic production of injection molding. Background technique [0002] At present, most technicians in the field of injection molding technology use traditional experience, that is, trial and error methods for injection molding production, resulting in waste of energy and costs, mainly in the following areas: [0003] 1. The setting of injection molding process parameters is only based on experience and varies from person to person, lacking necessary data support and scientific basis; [0004] 2. Injection molding process parameters are not optimized, resulting in a waste of injection molding costs and a reduction in injection molding quality; [0005] 3. The traditional experience inheritance model of masters leading apprentices is not conducive to the implementation of standardized data-ba...

AI Technical Summary

Problems solved by technology

[0003] 1. The setting of injection molding process parameters is only based on experience and varies from person to person, lacking necessary data support and scientific basis;

[0004] 2. Injection molding process parameters are not optimized, resulting in a waste of injection molding costs and a reduction in injection molding quality;

[0005] 3. The traditional experience inheritance model of masters leading apprentices is not conducive to the implementation of standardized data-based production by enterprises;

[0006] 4. Unable to realize automatic production of injection molding

Images