Injection molds can be fabricated using 3D printing technology. An inverse computer aided design (“CAD”) file may be generated based upon a visualization file that represents a 3D object. The inverse CAD file can then be altered based upon various parameters associated with the 3D object. One or more injection molds can be fabricated using a 3D printer based on the altered inverse CAD file.

A method for making dies for die casting, and relative die, includes designing moulding parts of the die as plurality of sub-inserts. Each sub-insert of the plurality is bordered by boundary lines defined on the basis of a simulation of thermo mechanical behaviour of the die in operation. The simulation is performed by a processor of a computer and the behaviour is the behaviour of the die if the die were a single piece. The method also includes producing the plurality of sub-inserts and assembling the sub-inserts of the plurality with attachment means, so as to form the die.

An optimization method based on feature extraction and machine learning is provided. At least one input parameter is received. Multiple first historical mold data are retrieved. A similarity calculation is performed according to the input parameter and the first historical mold data. Multiple candidate mold data are selected according to the similarity calculation. The mold design parameters of the candidate mold data corresponding to each input parameter are replaced by the input parameter, and multiple first representative mold data for performing a first simulation analysis are generated. Multiple key feature parameters are found, and multiple second historical mold data are retrieved according to the multiple key feature parameters. An expected data is found, and the mold design parameters of the expected data are filtered and optimized to find multiple second representative mold data for performing a second simulation analysis. At least one set of mold production parameters is generated.

The present invention relates to a system for casting a component by an adjustable molding box. A generating unit serves for generating a component model of the component to be molded, a transmitting unit serves for transmitting the component model via a data network to a determining unit, and the determining unit serves for determining a casting mold model based on the component model. The determining unit is configured such that adjustment data for adjusting the adjustable molding box based on the casting mold model are generatable. A control unit is coupled to the determining unit such that the adjustment data are providable to the control unit, wherein the control unit is configured such that the control unit adjusts the molding box, based on the adjustment data, with a casting mold, which is indicative for a negative profile of the component, and the component is castable by the adjusted molding box.

Provided is a sand mold digital flexible extrusion near-net forming optimization method based on a search algorithm. The method includes: dividing a sand mold Computer Aided Design (CAD) 3D model near-net forming region; acquiring a curved surface function of a near-net forming sand mold CAD 3D model cavity; constructing a flexible extrusion array envelope volume optimization objective function; determining a valid optimization interval R; translating the position of a sand mold CAD 3D model cavity to a search initial position; performing a global search in the valid optimization interval R, comparing flexible extrusion array envelope volume values, and saving the larger value as V(x,y).sub.max and the corresponding position as (x,y).sub.max; and completing the search, translating the position of the near-net forming sand mold CAD 3D model cavity to (x,y).sub.max, and executing a flexible extrusion array shape adjusting procedure.

The invention relates to a method for computationally designing re-usable silicone molds for the reproduction of an object, wherein the silicone mold is fillable with casting material, for example, but not limited to, resin, to form the object.

A method of forming a molding tool includes performing a computer aided engineering (CAE) analysis on a molding tool design. The CAE analysis predicts flow of injection molded material and a location of gas entrapment within a molding recess of the molding tool design. At least one venting design constraint is applied to the molding tool design as a function of the gas entrapment location. Also, a biomimetic shaped passageway for venting gas away from the gas entrapment location is selected from a plurality of biomimetic shaped passageways. A computational fluid dynamic (CFD) CAE analysis of the molding tool design with the selected biomimetic shaped passageway is performed and modifications of the selected biomimetic shaped passageway are CFD CAE analyzed until a final biomimetic shaped passageway is determined and a molding tool with the final biomimetic shaped passageway is formed.

Conventional approaches of physical experiments for the effects of cure kinetics in composites materials may lack in capturing lower length scale effects at bulk level. The computational state of the art approaches has not focused on the issue of scale bridging between multiple length scales for manufacturing effects in composites. This limits its usability for specific materials or situations. Embodiments of the present disclosure provide systems and methods that implement a multiscale analysis for determining residual stress and deformation profiles in molded parts comprising composite material. More specifically, present disclosure implements the multiscale analysis wherein a thermal chemical analysis and thermal mechanical analysis are linked to achieve two-way coupling for curing effects at each node/point of molded parts having composite material to provide flexibility and versatility in terms of exploring multiple material combinations without major modification in the approach.

A system for designing and manufacturing a mold structure for high-strength steel comprises a 3D modeling unit to design a mold structure based on surface topography information and physical property information about a forming material using a 3D modeling program, a forming load simulation unit to apply stepwise forming loads to a shell of the mold structure while the forming material is formed in the mold structure designed by the 3D modeling unit and to simulate a distribution of the forming loads of the mold structure, a numerical analysis unit to produce a stress and degree of deformation of the mold structure according to the forming load distribution and then analyze a possible wear portion and deformation rate of the wear portion, and an optimal parameter producing unit to provide an reinforcement parameter for reinforcing a design (structural) parameter or physical property value of the wear portion.

Injection molds can be fabricated using 3D printing technology. An inverse computer aided design (“CAD”) file may be generated based upon a visualization file that represents a 3D object. The inverse CAD file can then be altered based upon various parameters associated with the 3D object. One or more injection molds can be fabricated using a 3D printer based on the altered inverse CAD file.