A method, system and computer program product for a heuristic determination of in-process damage class control to manage expected output product category. The heuristic technique determines the predicted damages and their ranges while keeping the initial expected defects, the respective classes and range of defect and mitigation. The method dynamically computes a damage mitigation range of operation while being within the overall constraints and completes the computation in smaller number of loops being run at the edge computers so that the manufacturing equipment can operate at a higher velocity for higher quality of the output. The method includes a step of reducing error of the co-efficient and damage counts. An Internet of Things (IoT) based robot is used to mitigate the damages in the manufacturing steps to ensure that the output class of the product remains what was expected at the start despite damages and mitigation measures.

A computer implemented method (100) and system (200) for indexed tufting of a backing material (200) by a robot tufter. The method comprises: receiving (102) or accessing grid geometry of a backing material (200) wherein the grid geometry is based on a periodicity and dimensions of grid locations (204) of the backing material (200) and representative of optimal locations to receive a tufting needle; determining (104) indexed positions of grid locations of the backing material relative to the tufting needle of the robot tufter using a reference point that is fixed relative to the backing material (200); and controlling (106) the robot tufter to penetrate one or more specified indexed grid locations of the backing material with the tufting needle to create a tuft at the one or more specified indexed grid locations.

The setting of textile machinery parameters is an important aspect that combines implicit knowledge of workers and engineers with explicit knowledge. As yarn and fabrics involved in a textile process are multicomponent artefacts, in order to automatize this process of machine configuration, a method for dissimilarity computation between two yarns is proposed including one or a combination of four algorithms to evaluate the similarity between two yarns, each composed by a list of materials. The method has proved to be successful for spinning setting and it can be applied in other steps of a textile process like weaving.

A method and device are used for generating a jacquard pattern. The method comprises: acquiring structure information of a unit structure of a preform to be prepared, the structure information comprises a warp yarn column number, a warp yarn layer number, a weft yarn column number and a weft yarn layer number, a positional relationship between the warp yarns and the weft yarns of the unit structure of a preform to be prepared; obtaining a row number and a column number of the jacquard pattern to be generated, and correspondence between each pixel in the jacquard pattern to be generated and the warp yarns and weft yarns of the unit structure of the preform to be prepared; and obtaining a pixel value of each pixel, and generating the jacquard pattern to be generated.

The present application discloses a method and device for generating a jacquard pattern, an electronic device. The method comprises: acquiring structure information of a unit structure of a preform to be prepared, wherein the structure information comprises a positional relationship between the warp yarns and the weft yarns of the unit structure of a preform to be prepared; obtaining a row number and a column number of the jacquard pattern to be generated, and correspondence between each pixel in the jacquard pattern to be generated and the warp yarns and weft yarns of the unit structure of the preform to be prepared, according to the structure information; and obtaining a pixel value of each pixel according to the correspondence and the positional relationship between the warp yarns and the weft yarns, and generating the jacquard pattern to be generated.

A display and operating device for a textile machine includes a touchscreen that displays a first main operating mask and of a second main operating mask, both of which present a plurality of retrievable information masks and input masks for operating the textile machine. The first main operating mask includes a machine visualization field that displays a simplified visualization of the textile machine and at least one shortcut operating button related to an operational task to be carried out by an operator on the textile machine. The first main operating mask also includes a first toggle button for accessing and presenting the second main operating mask. The second main operating mask includes a display of an overview of selectable submenus by means of which machine settings of the textile machine are set or changed, and additional information is retrievable.

The present disclosure provides a whole-process automatic loading-and-unloading and logistics system, including an outer yarn preparation area, an inner yarn preparation area, a weaving area and an in-air conveying rail; the outer yarn preparation area is configured to have a carrier assembly, which delivers an outer yarn winding package to an outer yarn branch rail of a twisting machine in a twisting area via the out yarn main rail of the in-air conveying rail; in the inner yarn preparation area, the carrier assembly delivers an inner yarn winding package to an inner yarn branch rail of the twisting machine in the twisting area via the inner yarn main rail of the in-air conveying rail; in the twisting area, the carrier assembly delivers a yarn product to a yarn product donning rail in the weaving area via the yarn product main rail of the in-air conveying rail.

A method, system and computer program product for a heuristic determination of in-process damage class control to manage expected output product category. The heuristic technique determines the predicted damages and their ranges while keeping the initial expected defects, the respective classes and range of defect and mitigation. The method dynamically computes a damage mitigation range of operation while being within the overall constraints and completes the computation in smaller number of loops being run at the edge computers so that the manufacturing equipment can operate at a higher velocity for higher quality of the output. The method includes a step of reducing error of the co-efficient and damage counts. An Internet of Things (IoT) based robot is used to mitigate the damages in the manufacturing steps to ensure that the output class of the product remains what was expected at the start despite damages and mitigation measures.