B29C70/382

Method and devices to construct artificial inline defects to calibrate inspection hardware on automated fiber placement systems

Systems, methods, and devices are provided for the creation of predictable and accurate defects in a fiber tow of an Automated Fiber Placement (AFP) process, with such artificial defects being useful to support calibration of an in situ inspection system used in the AFP process. Various embodiments include methods for creating such artificial defects that support calibration of an in situ inspection system of an AFP system or process. Various embodiments may also include a defect stencils for an AFP system or process.

Stiffening element and reinforced structure

A stiffening element including at least a first stiffening profile and at least a second stiffening profile. The first stiffening profile includes a profile member. At least one structural flange is connected to the profile member. A through-passage extends through the profile member. At least one support flange is connected to the profile member. The second stiffening profile includes a bottom portion and at least one support side portion connected to the bottom portion. A method for manufacturing a stiffening element. A method for manufacturing a reinforced structure, where the reinforced structure includes at least one structural element and at least one stiffening element.

System for additive manufacturing

A system is disclosed for additive manufacturing of a composite structure. The system may include a support, and a print head connected to and moveable by the support. The print head may include an outlet configured to discharge a continuous reinforcement at least partially coated in a matrix. The outlet may be moveable relative to the support. The print head may also include at least one actuator configured to cause movement of the outlet relative to the support.

VERIFICATION OF TOW PLACEMENT BY A ROBOT

Systems and methods are provided for verifying the placement of tows by a robot. One embodiment includes a robot that includes an end effector that lays up tows, actuators that reposition the end effector, a memory storing a Numerical Control (NC) program, and a robot controller that directs the actuators to reposition the end effector based on the NC program, and instructs the end effector to lay up tows based on the NC program. The system also includes a sensor system comprising an imaging device that acquires images of the tows as the tows are laid-up, a measuring device that generates input as tows are laid-up by the end effector, and a sensor controller that receives images from the imaging device and the input from the measuring device, and updates stored data to correlate the images with instructions in the NC program, based on the input.

METHOD FOR MANUFACTURING A THREE-DIMENSIONAL PREFORM
20230166462 · 2023-06-01 ·

Disclosed is a method for producing a three-dimensional preform (1) comprising the following steps: (a) depositing at least one strip (2) of fibers (5) on a three-dimensionally shaped substrate (3); (b) sewing the at least one strip (2) of fibers (5) onto the substrate (3) with at least one sewing thread (4) forming a seam (6).

Flexible thermoplastic composite coupling and method of manufacture

A process for forming a flexible composite driveshaft includes providing a mandrel having a rigid region and a compressible region, applying fiber tape to the mandrel using automated fiber placement with in-situ laser curing in the rigid region and without in-situ laser curing the compressible region, and compressing the fiber tape and compressible material in the compressible region to form diaphragms that extend radially outward to a diameter that is at least twice the size of a diameter of the composite driveshaft in the rigid region.

Method and apparatus for additive mechanical growth of tubular structures
09808991 · 2017-11-07 · ·

A method and apparatus is disclosed for additive manufacturing and three-dimensional printing, and specifically for extruding tubular objects. A print head extrudes a curable material into a tubular object, while simultaneously curing the tubular object and utilizing the interior of the cured portion of the tubular object for stabilizing and propelling the print head.

FIBER-REINFORCED COMPOSITE LAYUP
20220055324 · 2022-02-24 ·

Fiber-reinforced composites is provided. The composites include a plurality of prepreg layers, each comprising a polymeric resin and a plurality of fibers disposed therein; and at least one electrically-conductive layer at least partially embedded in the plurality of prepreg layers. These fiber-reinforced composites can save weight relative to externally provided wires and can be provided in forms suitable for use in automated fiber placement and automated tape layup machines. Advantageous applications include uses in lightning strike protection, energy storage, signal transmission, and power distribution.

Production in composite material of a lobed structure of a flow mixer
11667089 · 2023-06-06 · ·

The invention relates to the production of a composite material of a lobed structure (10) of a flow mixer which comprises a portion having a plurality of lobes (17, 19). For this purpose, a fibrous preform containing a resin will be produced in a simple geometric configuration of developable revolution. This is an intermediate state. By exploiting the thermoformable or thermosetting nature of the resin, the geometry of this intermediate preform is modified to deform it with limited offsets towards the final geometry.

Object design using machine-learning model

A system to aid in design for manufacturing an object includes a processor and a memory configured to store instructions. The processor is configured to receive first data representing a design of the object to be manufactured and second data representing a machine-learning model. The processor is configured to execute the instructions to generate third data using the first data and the second data. The third data indicates at least one of a modification to the design of the object or process conditions for production of the object. The processor is configured to send the design of the object, the process conditions, or both, to a manufacturing tool to enable production of the object. The machine-learning model is representative of production data and based at least partially on one or more of: object features, process parameters, environmental factors, and quality data.