A method of detecting and compensating for a non-operational mold cavity in an injection molding apparatus having a plurality of mold cavities and an injection molding screw or ram includes injecting, via the injection molding screw or ram, a molten thermoplastic material into the plurality of mold cavities. The method includes measuring a first process parameter of the injection molding apparatus at a pre-determined time during or after the injecting. The method also includes determining, based on the first process parameter, whether one or more mold cavities of the plurality of mold cavities are non-operational. Then, when it is determined that one or more mold cavities are non-operational, the method includes automatically adjusting the first process parameter or a second process parameter of the injection molding apparatus.

A method of detecting and compensating for a non-operational mold cavity in an injection molding apparatus having a plurality of mold cavities and an injection molding screw or ram includes injecting, via the injection molding screw or ram, a molten thermoplastic material into the plurality of mold cavities. The method includes measuring a first process parameter of the injection molding apparatus at a pre-determined time during or after the injecting. The method also includes determining, based on the first process parameter, whether one or more mold cavities of the plurality of mold cavities are non-operational. Then, when it is determined that one or more mold cavities are non-operational, the method includes automatically adjusting the first process parameter or a second process parameter of the injection molding apparatus.

A molding machine teaching aid includes a frame unit, a molding unit, a material supply unit, a drive unit and a monitoring unit. The molding unit includes a fixed die holder, a movable die holder, and two die kernels respectively and detachably disposed on the fixed and movable die holders. The material supply unit includes a heating module for melting a wire material, and an extruder transporting the molten material into a die cavity formed between the die kernels. The drive unit is controllable to drive movement of the movable die holder relative to the frame unit. The monitoring unit is for a user to operate to control the extruder, the heating module and the drive unit.

A molding machine teaching aid includes a frame unit, a molding unit, a material supply unit, a drive unit and a monitoring unit. The molding unit includes a fixed die holder, a movable die holder, and two die kernels respectively and detachably disposed on the fixed and movable die holders. The material supply unit includes a heating module for melting a wire material, and an extruder transporting the molten material into a die cavity formed between the die kernels. The drive unit is controllable to drive movement of the movable die holder relative to the frame unit. The monitoring unit is for a user to operate to control the extruder, the heating module and the drive unit.

A method for determining optimized shape data representing a shape of a molded workpiece formed from a molded material or/and a mold cavity of a molding tool, wherein the molded material hardens depending on at least one solidification parameter, the method including: a) providing shape data representing a shape of the workpiece or/and cavity, b) providing material data representing the molded material, c) providing molding process data representing the molding process, d) providing tool data representing the tool embodying the cavity, e) determining predictive shape data based on initial model data comprising the at least one solidification parameter and data provided in steps a), b), c), and d) simulating the molding process, f) generating optimized predictive shape data as the optimized shape data based on at least predictive shape data determined in step e) and based on first initial AI data comprising the at least one solidification parameter and data provided in steps a, b), c), and d), by means of an artificial neural simulation optimization network trained to optimize predictive shape data.

A method for determining optimized shape data representing a shape of a molded workpiece formed from a molded material or/and a mold cavity of a molding tool, wherein the molded material hardens depending on at least one solidification parameter, the method including: a) providing shape data representing a shape of the workpiece or/and cavity, b) providing material data representing the molded material, c) providing molding process data representing the molding process, d) providing tool data representing the tool embodying the cavity, e) determining predictive shape data based on initial model data comprising the at least one solidification parameter and data provided in steps a), b), c), and d) simulating the molding process, f) generating optimized predictive shape data as the optimized shape data based on at least predictive shape data determined in step e) and based on first initial AI data comprising the at least one solidification parameter and data provided in steps a, b), c), and d), by means of an artificial neural simulation optimization network trained to optimize predictive shape data.

For in mold spraying, a double-inclined mixing nozzle is connected obliquely and fixedly with a side surface of a third half-mold through a lateral sealing structure and connected with a side surface of a first half-mold in an inclined and sealing manner, side faces of a first half-mold and the third half-mold are respectively provided with installation inclined surfaces. A lateral sealing structure includes a mounting plate and a sealing member. The sealing member is sleeved on the double-inclined mixing nozzle and is in transition fit with the double-inclined mixing nozzle and the mounting plate respectively. A butt sealing groove provided on the installation inclined surface of the first half-mold and is in sealing fit with the mounting plate.

For in mold spraying, a double-inclined mixing nozzle is connected obliquely and fixedly with a side surface of a third half-mold through a lateral sealing structure and connected with a side surface of a first half-mold in an inclined and sealing manner, side faces of a first half-mold and the third half-mold are respectively provided with installation inclined surfaces. A lateral sealing structure includes a mounting plate and a sealing member. The sealing member is sleeved on the double-inclined mixing nozzle and is in transition fit with the double-inclined mixing nozzle and the mounting plate respectively. A butt sealing groove provided on the installation inclined surface of the first half-mold and is in sealing fit with the mounting plate.

A manufacturing apparatus includes an injection cylinder to which molten resin is supplied and which is configured to inject the molten resin, and an injection plunger disposed such that the injection plunger fits in the injection cylinder and moves in a first direction and a second direction opposite to the first direction. The injection cylinder includes a base body configured to contain the molten resin, and a sleeve configured to be detachably attached to the base body. The injection plunger is configured to be inserted into an inner portion of the base body through an opening portion formed in the sleeve and slide on the sleeve.

A manufacturing apparatus includes an injection cylinder to which molten resin is supplied and which is configured to inject the molten resin, and an injection plunger disposed such that the injection plunger fits in the injection cylinder and moves in a first direction and a second direction opposite to the first direction. The injection cylinder includes a base body configured to contain the molten resin, and a sleeve configured to be detachably attached to the base body. The injection plunger is configured to be inserted into an inner portion of the base body through an opening portion formed in the sleeve and slide on the sleeve.