Systems and methods for on-loom detection of faults in fabric. An image-capture trigger-mechanism triggers an imaging device to capture a first image of a section of the weaving area at a first instant during each weft insertion cycle and a second image of the section of weaving area may be captured at a second instant during each weft insertion cycle. The images may be timed to provide images of the warp yarns and the weft yarns at optimal instants during the weft insertion cycle. An image processor detects irregularities in the data received from the imaging device

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 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 machine for weaving or winding a fiber preform on a mandrel having an axis of rotation that is substantially horizontal and that serves to receive the preform, the machine having a plurality of cameras pointing towards the underside of the fiber preform in order to scan the hidden face of the fiber preform and acquire images of the hidden face; an image analysis module for processing these images of the hidden face of the fiber preform in a plurality of adjacent scan windows, and for extracting weaving patterns therefrom and comparing them with reference weaving patterns previously stored in the module; a motor for driving the mandrel in rotation about its axis of rotation; and a control unit for stopping rotation of the mandrel if the result of the comparison reveals a difference of appearance between the two weaving patterns.

A machine for weaving or winding a fiber preform on a mandrel having an axis of rotation that is substantially horizontal and that serves to receive the preform, the machine having a plurality of cameras pointing towards the underside of the fiber preform in order to scan the hidden face of the fiber preform and acquire images of the hidden face; an image analysis module for processing these images of the hidden face of the fiber preform in a plurality of adjacent scan windows, and for extracting weaving patterns therefrom and comparing them with reference weaving patterns previously stored in the module; a motor for driving the mandrel in rotation about its axis of rotation; and a control unit for stopping rotation of the mandrel if the result of the comparison reveals a difference of appearance between the two weaving patterns.

A reflection optical sensor (F1-F4) for the detection of a weft thread in a weaving weft feeder (P) comprises a light emitter (1) and a light receiver (2) assembled on a relative supply printed circuit board (3) and housed in an arm (A) of the weft feeder which projects towards the front part of the weft feeder (P) and extends alongside the weft feeder drum (D) whereon the weft thread coils are wound, so as to form a path of direct light radiation, from said light emitter (1) towards a respective reflective surface (R) placed on said drum (D), and of reflected light radiation, from said reflective surface (R) to said light receiver (2), for detecting the presence/absence of a weft thread running through said path. Said light emitter (1) and light receiver (2) are assembled with mutually parallel optical axes on said supply printed circuit board (3). The optical sensor further includes a screening means (8) of the reflected radiation coming from said reflective surface (R) and directed towards said light receiver (2).

The present disclosure relates to a method performed by an alignment system for aligning tethers of a drop stitch fabric prior to feeding the drop stitch fabric to a drop stitch fabric processing machine. The alignment system feeds a drop stitch fabric having a first layer and a second layer tethered by drop stitch tethers, wherein the first layer is moving with a first velocity and the second layer is moving with a second velocity. The disclosure also relates to an alignment system in accordance with to the foregoing.

The present disclosure relates to a method performed by an alignment system for aligning tethers of a drop stitch fabric prior to feeding the drop stitch fabric to a drop stitch fabric processing machine. The alignment system feeds a drop stitch fabric having a first layer and a second layer tethered by drop stitch tethers, wherein the first layer is moving with a first velocity and the second layer is moving with a second velocity. The disclosure also relates to an alignment system in accordance with to the foregoing.

A reflection optical sensor (F1-F4) for the detection of a weft thread in a weaving weft feeder (P) comprises a light emitter (1) and a light receiver (2) assembled on a relative supply printed circuit board (3) and housed in an arm (A) of the weft feeder which projects towards the front part of the weft feeder (P) and extends alongside the weft feeder drum (D) whereon the weft thread coils are wound, so as to form a path of direct light radiation, from said light emitter (1) towards a respective reflective surface (R) placed on said drum (D), and of reflected light radiation, from said reflective surface (R) to said light receiver (2), for detecting the presence/absence of a weft thread running through said path. Said light emitter (1) and light receiver (2) are assembled with mutually parallel optical axes on said supply printed circuit board (3). The optical sensor further includes a screening means (8) of the reflected radiation coming from said reflective surface (R) and directed towards said light receiver (2).

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.