System and method for computer vision assisted foam board processing

Abstract

Methods and systems for manufacturing a foam board system are disclosed. In some examples, the system includes an application device to distribute one or more fluids onto a substrate. One or more sensors are configured to measure one or more characteristics of the one or more fluids. A control circuit is configured to compare the one or more measured characteristics to one or more characteristic thresholds and adjust one or more operating parameters of the system in response to a certain one of the one or more measured characteristics falling outside of a certain one of the one or more characteristic thresholds.

Description

[0001] Related application citation

[0002] This application is a non-provisional patent application of U.S. Provisional Patent Application No. 63 / 071,999, filed on August 28, 2021, entitled “System and Method for Computer Vision-Assisted Foam Board Processing,” the entire contents of which are incorporated herein by reference. Background Technology

[0003] This technology relates to a method and system for monitoring and / or determining one or more characteristics of a manufactured board.

[0004] Polyurethane and polyisocyanurate foams are widely used in the construction industry to produce engineered foam boards due to their excellent mechanical properties, fire resistance, and insulation performance. These high-performance characteristics are attributed to the microporous structure within the board created during the manufacturing process.

[0005] Some manufacturing techniques (such as those designed to reduce the cost of manufacturing foam insulation boards) introduce problems during and / or in the finished product, such as reduced appearance and / or integrity. Conventional methods for identifying defects in foam boards are manual, labor-intensive, and many optimal processing conditions are subjectively determined, which can be prone to operator error. This approach is also limited by the small number of measurement locations on the board. This results in a slow, resource-intensive process that often fails to provide a complete assessment of the board's appearance and / or integrity.

[0006] Given the limitations of current technology, a more efficient and comprehensive method and equipment are needed to monitor, determine, and / or control the characteristics of manufactured boards. Summary of the Invention

[0007] In one aspect, this disclosure provides a system for manufacturing foam boards. In some instances, the system includes an application device for distributing one or more fluids onto a substrate. One or more sensors are configured to measure one or more characteristics of the one or more fluids. Control circuitry is configured to compare the one or more measured characteristics with one or more characteristic thresholds, and to adjust one or more operating parameters of the application device in response to any of the one or more measured characteristics falling outside one or more of the characteristic thresholds.

[0008] In another aspect, this disclosure provides a method for manufacturing a foam board. The method includes measuring one or more features corresponding to the distribution of one or more fluids applied to a substrate via sensors; receiving data corresponding to the one or more features at a control circuit; comparing the one or more measured features with one or more feature thresholds at the control circuit; identifying one or more operating parameters corresponding to the one or more measured features at the control circuit; and adjusting one or more operating parameters in response to a feature of the one or more measured features falling outside one of the one or more feature thresholds. Attached Figure Description

[0009] Figure 1 An exemplary system for manufacturing foam boards is shown, representing an aspect of this disclosure.

[0010] Figure 2 Another exemplary system for manufacturing foam boards, based on aspects of this disclosure, is shown.

[0011] Figure 3 Exemplary detailed views of the foam flow and substrate during the manufacturing process of aspects of this disclosure are shown.

[0012] Figure 4 This is a block diagram of an exemplary control circuit for a system for manufacturing foam board, which is an aspect of this disclosure.

[0013] Figure 5 An exemplary method for operating an aspect of this disclosure for manufacturing a system of foam boards is shown.

[0014] The accompanying drawings are not necessarily drawn to scale. In appropriate places, similar or identical reference numerals are used to refer to similar or identical parts. Detailed Implementation

[0015] This technology relates to a method and system for monitoring and / or determining one or more characteristics of a manufactured board (e.g., insulation board, constrained foam board, free foam board, preform, extruded plastic board, etc.). In particular, one or more sensors (e.g., laser scanners, optical imaging systems, etc.) can be arranged to measure one or more characteristics of the foam board and / or one or more components of the foam board. The measurement results are provided to control circuitry and / or a processor, which compares the one or more measured characteristics with one or more characteristic thresholds.

[0016] The control circuitry can be configured to adjust or otherwise control one or more operating parameters of the system based on the comparison result. For example, the system for manufacturing foam boards may include application means for distributing one or more inputs (e.g., fluids, chemicals, gases, solids, or other materials) onto a substrate or surface layer advancing through a conveying system (e.g., a conveyor belt). The system can adjust the distribution of these inputs (e.g., quantity, speed, composition, position, angle, etc.) and the operating parameters of the conveying system (e.g., speed, amount / position of applied heat, orientation of the substrate or surface layer relative to the conveying direction, and / or the position of the applied input, etc.) in response to the comparison result.

[0017] In some instances, the measured feature is compared to one or more thresholds (e.g., stored values, calculated values, etc.) associated with those features. If the measured feature value falls outside the relevant threshold (e.g., a single value, a range of values), the control circuitry can control the application device, delivery system, and / or another component of the manufacturing system to adjust one or more operating parameters (e.g., associated with inputs or other operating parameters) to correct or mitigate the problem, thereby ensuring that the integrity of the manufactured board (e.g., a foam insulation board) is maintained.

[0018] During the manufacturing process, uneven application and / or distribution of the input materials used to produce foam can compromise the integrity of the manufactured panels, leading to reduced thermal insulation, water buildup, film adhesion failure, dimensional stability issues, decreased fire resistance, and reduced compressive strength in the final product. Conventional methods for identifying problems may be limited to visual inspection of a limited portion of the finished panel. For example, highly trained operators observe the appearance of the applied fluid / chemical and the finished panel. Then, for example, operators manually adjust the foam nozzles, altering the material flow location or other processing parameters in a "best guess" manner to optimize production.

[0019] The results of this limited visual observation will be used to determine the integrity of the entire board, and in some cases, the integrity of the entire batch of boards represented by the tested sample board. Such a manual process is time-consuming and resource-intensive, and the results cannot represent the integrity of the entire board or batch. Furthermore, at least because this testing is performed after the board has been completed, it may fail to identify the specific input material causing the problem and / or how to adjust that input material to correct the problem. As a result, the cost and quality of the manufactured boards heavily depend on the attention and judgment of the operators.

[0020] In contrast, the disclosed manufacturing system employs sensors, such as video capture sensors, laser scanners, infrared (IR) scanners, and / or thermal scanners, at one or more stages of manufacturing to measure fluid application and / or characteristics of the finished board in real time. The measurement results are provided to control circuitry to determine if any problems exist, and one or more operating parameters are adjusted during board manufacturing based on the determination results. Therefore, the system is configured to automatically adjust operating parameters based on sensor feedback and the use of one or more control algorithms, resulting in more consistent operation, lower material and operating costs, and / or improved product quality.

[0021] The quality and cost of manufactured foam boards (such as polyisocyanurate insulation boards) are closely related to the ability of the manufacturing system to uniformly distribute fluid (e.g., one or more liquid chemicals) along the width or span of the substrate or surface layer as it advances on the conveying system. In particular, uneven distribution requires more raw materials (which increases costs) and leads to performance problems. For example, uneven foam distribution requires more raw materials to fully fill the board with expanded foam.

[0022] The disclosed systems and methods provide precise and rapid-response control of fluid distribution by employing sensors (e.g., lasers, computer vision, optical imaging systems, and / or thermal imaging) in the first stage of the manufacturing process. In some instances, sensors (e.g., optical imaging systems) detect features related to the quality of the fluid applied to the substrate and / or the final appearance of the dried board. In a range of non-limiting examples, features monitored during the first stage (e.g., foam application) may include or relate to fluid flow location, volume of deposited fluid, width of material flow, volume growth rate, temperature, presence / size / growth rate of bubbles, color, foam accumulation or accumulation rate, and / or substrate / surface layer breakage. In later stages of the manufacturing process (e.g., solid foam boards, cured / finished boards), additional or alternative features may be monitored, such as seam lines, overfilling within the surface layer, underfilling within the surface layer, voids, wrinkles, and / or warping.

[0023] Based on characteristic data received via one or more sensors (e.g., an optical imaging system), the control circuit can determine whether one or more operating parameters should be adjusted. For example, the fluid application device can be adjusted to change the angle or position of the material flow on the substrate, fluid flow rate, fluid application pressure, fluid temperature, composition (e.g., molar ratio), component mass balance, etc. Furthermore, operating parameters of related systems can be adjusted, such as conveyor or laminator speed, production line speed, laminator temperature, height, etc.

[0024] In some instances, one or more sensors are arranged to monitor characteristics of the fluid / input and the finished board / output. For example, a first sensor (e.g., an optical vision system) is arranged to monitor the substrate area where the foam is dispensed as the foam advances through the conveyor system. A second sensor is arranged later in the manufacturing process, for example, to inspect solid foam, or in some instances to inspect the finished foam board to identify defects such as bond lines, wrinkles, warping, overfilling, underfilling, voids, flatness, pores, thermal imaging profiles, bulges / concaves, bubbles, surface defects, surface misalignment, excess foam, thickness, etc.

[0025] Algorithms can be used to compare sensor data with predetermined values, identify differences, and adjust operating parameters accordingly. In some instances, the algorithm includes a feedback loop that can employ machine learning or other artificial intelligence (AI) to provide control values ​​for various system components.

[0026] In some instances, flatness and / or hardness (e.g., mechanical properties, density, etc.) testing devices are used in the second stage (e.g., solid foam boards) to collect data to identify areas defined by peaks and valleys (e.g., deviation from the Z-axis of the surface) of the finished board. The height of the peaks and the depth of the valleys are compared with one or more thresholds to determine areas as test locations requiring further testing. In some instances, as disclosed herein, the results of the comparison can be used to adjust one or more operating parameters, such as the application of fluid flow. Additional testing may include, but is not limited to, determining one or more of the dimensions (e.g., thickness), mechanical properties (e.g., compressive strength, etc.), and the board density of the area. This testing can be performed using a multi-directional motorized testing device fixed to a motorized carriage capable of passing through the surface of the board (e.g., through an XY plane perpendicular to the Z-axis). Alternatively, compressive strength can be tested along the Y-axis of the foam board, which can be considered for adjusting one or more parameters (e.g., the position or orientation of the application device).

[0027] In some instances, sensor measurements from the first stage of the manufacturing process can be analyzed and / or compared based on sensor measurements from the second stage to determine adjustments to manufacturing process parameters. For example, sensor measurements from the first stage (e.g., a scan of the fluid flow before applying the second surface layer / substrate) can cause adjustments to a specific first parameter (e.g., adjustments to the position / or orientation of the application device). Sensor measurements from the second stage (e.g., a scan of the finished board and / or a flatness or hardness test) can cause adjustments to another specific second parameter (e.g., adjustments to the fluid flow rate) and / or the first parameter. Alternatively, control circuitry (e.g., via one or more algorithms) is configured to consider measurements from both the first and second stages together. In this case, the first and second parameters, as well as a third parameter (e.g., adjustments to the conveyor speed), can be adjusted. However, based on a comparison of the measurements from the first and second stages, the amount of adjustment to the first, second, or third parameter can be changed, and / or one or more of the first, second, or third parameters can be avoided. In some instances, sensors continuously monitor the characteristics of the final finished board (e.g., a dried, cured board) and provide the sensor data to the control circuit 220 for analysis.

[0028] By employing the disclosed system and method, it is possible to improve characteristics affecting the quality of the board, such as foam cost, edge collapse, dimensional stability (e.g., hot, cold, wet, dry), insulation value (k-factor / R-value), fire resistance rating, pore orientation, and other results, thereby ensuring the quality and consistency of the entire batch of finished boards.

[0029] Because the monitoring and adjustment system is automated, it is configured to "learn" and update thresholds using artificial intelligence algorithms. In some instances, the algorithms are able to identify signs that specific operating parameters are trending toward undesirable values ​​and implement control over the corresponding actuators, systems, or components. Therefore, operators spend less time monitoring the manufacturing process, and less training is required for those responsible for monitoring the system. Furthermore, the collection of sensor data is used to determine best practices that can be used throughout the manufacturing system and / or guide subsequent processes.

[0030] The following examples will provide a better understanding of the techniques described herein and their advantages. These examples are provided merely to illustrate specific embodiments of the technology. They are not intended to limit the scope and spirit of the technology.

[0031] In the disclosed examples, a system for manufacturing foam boards includes an application device for dispensing one or more fluids onto a substrate, one or more sensors configured to measure one or more characteristics of the one or more fluids, and a controller configured to compare the one or more measured characteristics with one or more characteristic thresholds, determine whether a certain characteristic of the one or more measured characteristics falls outside one or more characteristic thresholds, calculate an adjustment amount for the characteristic based on the one or more measured characteristics or the thresholds in response to determining that the characteristic falls outside the threshold, and generate a command corresponding to the adjustment amount.

[0032] In some instances, one or more control mechanisms are configured to adjust one or more operating parameters of the system, wherein the one or more control mechanisms are configured for manual adjustment by an operator.

[0033] In this example, the controller is also configured to generate an indicator corresponding to the quantity and provide the indicator to a user interface configured to be presented to an operator.

[0034] In some instances, the controller is configured to adjust one of the one or more operating parameters by a first amount when the feature exceeds a first threshold among one or more feature thresholds, and to adjust the operating parameter by a second amount when the feature exceeds a second threshold among one or more feature thresholds.

[0035] In an example, the one or more operating parameters include one of the following: flow rate, location or orientation of the application device, pressure, temperature, delivery speed, composition or mass balance, and location of the deposited fluid.

[0036] In some instances, the one or more sensors are configured to monitor a substrate region downstream of the point where the one or more fluids come into contact with the substrate.

[0037] In one example, the transport system advances the one or more fluids and the substrate along a transport path, and the one or more sensors are configured to scan the one or more fluids as the substrate advances along the transport path. In another example, the one or more sensors are configured to scan the one or more fluids along an axis perpendicular to the transport path.

[0038] In some instances, the conveying system advances the foam board along a conveying path, and the one or more sensors are configured to scan the foam board as it advances along the conveying path. In some instances, the one or more sensors are configured to scan the foam board along an axis perpendicular to the conveying path.

[0039] In this example, the one or more sensors are configured to scan the foam board along multiple axes.

[0040] In some instances, the one or more sensors are fixed to a movable mounting base configured to adjust the orientation or position of the one or more sensors relative to a substrate.

[0041] In the example, the one or more sensors include one or more of the following: a laser scanner, an optical imaging system, a hyperspectral imaging system, a near-infrared sensor, an infrared sensor, an ultrasonic sensor, or a thermal sensor.

[0042] In some instances, the one or more features include one or more of the following: the amount of fluid flow, the position of the fluid on the substrate, the position of the fluid edge on the substrate, the angle of contact between the fluid and the substrate, the volume of the fluid on the substrate, the centroid of the fluid on the substrate, the height of the fluid on the substrate, the consistency of the fluid, and the temperature of the fluid.

[0043] In the example, the one or more features include one or more of the following: volume growth rate, width growth rate, height growth rate, rate of change of the angle of contact between the fluid and the substrate, centroid change rate, and temperature rise rate.

[0044] In some instances, the one or more features include one or more of the following: the presence of air bubbles in the foam, incomplete mixing, abnormal foam color, inconsistent liquid flow from the application device, or foam accumulation on the substrate or the application device.

[0045] In some instances, the one or more features include one or more of the following: foreign matter, substrate alignment or position, conveying speed, or substrate cracks or compression. In some instances, the one or more fluids react to generate polyurethane or polyisocyanurate foam.

[0046] In some instances, the controller is also configured to apply machine learning algorithms to generate the one or more thresholds.

[0047] In some instances, the controller is also configured to store features of the one or more measurements in a storage device, calculate an average feature value based on the features of the one or more measurements over a predetermined time period, and generate the one or more thresholds based on the average feature value and one or more tolerance ranges.

[0048] In some disclosed examples, a system for manufacturing foam boards includes an application device for dispensing one or more fluids onto a substrate, one or more sensors configured to measure one or more characteristics of the one or more fluids, and a controller configured to compare the one or more measured characteristics with one or more characteristic thresholds and adjust the position or orientation of the application device in response to one of the one or more measured characteristics falling outside one of the one or more characteristic thresholds.

[0049] In some instances, the one or more sensors include a first sensor configured to monitor a substrate region downstream of the point where the one or more fluids come into contact with the substrate. In other instances, the one or more sensors include a second sensor configured to monitor the finished board.

[0050] In the example, the second sensor includes one or more of the following: a flatness tester, a hardness tester, a density tester, a laser scanner, an optical imaging system, a hyperspectral imaging system, a near-infrared sensor, an infrared sensor, an ultrasonic sensor, or a thermal sensor.

[0051] In some disclosed examples, a method for manufacturing a foam board includes measuring one or more features corresponding to the distribution of one or more fluids applied to a substrate via sensors, receiving data corresponding to the one or more features at a control circuit, comparing the one or more measured features with one or more feature thresholds at a control circuit, identifying one or more operating parameters corresponding to the one or more measured features at a control circuit, and adjusting one or more operating parameters in response to a feature of the one or more measured features falling outside one of the one or more feature thresholds.

[0052] In some instances, the method includes adjusting one of the one or more operating parameters by a first amount when the feature exceeds a first threshold of one or more feature thresholds, and adjusting the operating parameter by a second amount when the feature exceeds a second threshold of one or more feature thresholds.

[0053] In one example, the adjustments include those made by an operator to the control mechanism. In another example, the adjustments include those made by a robotic device to the control mechanism.

[0054] As disclosed herein, “foam” or “foam insulation material” may include, but is not limited to, polystyrene, polyurethane, polyisocyanurate or phenolic resin.

[0055] As disclosed in this article, “blank” refers to a large-sized solid box-shaped structure formed during the production of polystyrene, polyurethane, or polyisocyanurate insulation materials.

[0056] Figure 1 A system for manufacturing foam board 100 (or "laying device") is shown. Figure 1 As shown, fluid components A and B are provided by chemical storage system 118. In some instances, component "A" may include isocyanate, while component "B" may include one or more of polyols, catalysts, additives, and / or blowing agents. In some instances, a third component "C" (e.g., pentane) may be used as a "blowing agent" to facilitate foam expansion.

[0057] The flow of fluid is controlled by one or more valves and / or pumps 112, which may be controlled by control circuitry or a processor. Conduits, manifolds, valves, or multiple connected pipes 110 supply fluid to a mixing nozzle 102, in which the constituent fluids are combined, react, and delivered via one or more application devices or nozzles 104, for example, in the form of foam. The combined fluid or foam 106 is dispensed onto a substrate 108 (or bottom layer 116), and the position and / or orientation of the mixing nozzle 102 is controlled by control circuitry that manages the application of foam 106.

[0058] The foam 106 applied by the application device 104 is uniformly distributed across the entire width of the substrate 108 to ensure that the foam 106 expands and cures in a uniform manner as it enters the conveyor system or laminator 124. A top layer 114 is provided within the laminator 124, and as the foam 106 expands, the space between the substrate 108 and the top layer 114 is filled with the foam 106. A conveyor belt 120 drives the substrate 108 and the top layer 114 in direction 132 to provide a finished board 125. In some instances, one or more heaters 122 are arranged within the manufacturing system 100 to control the heat of the foam 106, top layers 114, 116, which affects the reaction time, adhesion properties, and strength of one or more components of the board; these are merely non-limiting examples.

[0059] The correct application of foam 106 directly affects the quality of the finished board 125. However, conventional systems rely on operator attention and / or judgment to monitor the foam 106 applied to the substrate 108, typically depending on visually determining the quality of the foam composition and / or the foam distribution on the substrate 108. Often, multiple foam flows are applied to the substrate 108, each with different widths, application angles, volumes, flow rates, etc., further complicating the process. Alternatively, blockages may occur at the application device 104, further impacting the quality and cost of the finished board 125.

[0060] In some instances, a second operator inspects finished board 125 for defects (e.g., underfilling, overfilling, tears, wrinkles, voids, etc.). The second operator communicates with the first operator at the mixing nozzle 102 regarding proposed adjustments to the application, such as changing the position or orientation of the application device 104, flow rate, and the composition of the combined fluid. This process relies on multiple skilled operators who must continuously monitor and evaluate the manufacturing process, which may produce hundreds of finished boards (e.g., 10 to 300 feet of finished foam board per minute). Consequently, the identification of problems in solid foam boards and / or finished products is often delayed, making corrections slow and requiring the entire batch of products to be discarded before the manufacturing process is corrected.

[0061] Figure 2 An exemplary system for manufacturing foam board 100 is shown, comprising one or more integrated sensors 140 and / or adjustable components (e.g., sensor 140, actuator 144, conveying system 124, etc.), providing solutions to many problems in producing cost-effective, high-quality foam boards. Figure 2 As shown, sensor 140 is located at one or more locations along the manufacturing path to monitor one or more features of fluids, foams, substrates, surface layers, finished boards, and / or system 100 at one or more stages of the manufacturing process. Using sensor 140, the measured features can be transmitted to control circuitry 220, which is configured to analyze these features, compare them to one or more thresholds, and / or control adjustments to one or more parameters associated with one or more components to correct for undesirable results.

[0062] Sensor 140 may include one or more measuring devices 142, which may include one or more of the following: laser scanner, optical imaging system, hyperspectral imaging system, near-infrared sensor (NIR), infrared sensor (IR), ultrasonic sensor, or thermal sensor, these are merely non-limiting examples.

[0063] Sensor 140 and / or measuring device 142 may be mounted on an electric carriage or other actuator 144 configured to move the sensor 140 or device 142 at any position or orientation relative to system 100. Therefore, measuring device 142 and sensor 140 can navigate in three-dimensional space above system 100. In some instances, sensor 140 is mounted remotely from measuring device 142, which can provide varying perspectives and / or optimize the measurement of specific features.

[0064] Data collected by sensor 140 is transmitted to control circuit 220. For example, this data may correspond to one or more characteristics of foam 106 or the generated flow 134, such as fluid flow location, deposited fluid volume, flow width, volume growth rate, temperature, presence / size / growth rate of bubbles, color, foam accumulation or accumulation rate, and characteristics of substrate 108 / surface layer 114 / 116, such as substrate / surface layer damage, bonding lines, overfilling within the surface layer, underfilling within the surface layer, voids, wrinkles, and / or warping, these are only some non-limiting examples.

[0065] Based on feature data received from one or more sensors 40, control circuitry 220 can determine whether one or more operating parameters should be adjusted. For example, fluid application device 104 can be adjusted to change the angle or position of the material flow on substrate 108, fluid flow rate, fluid application pressure, fluid temperature, composition balance, etc. In some instances, the flow rate of metering pump 112 can be adjusted, and the position or orientation of application device 104 relative to substrate 108 and / or another application device can be adjusted, which position or orientation controls the distribution and / or composition of foam 106 applied to substrate 108.

[0066] In addition, one or more sensors 140 can monitor operating parameters of the relevant system, such as the conveyor system 124. Data corresponding to one or more parameters of the conveyor system 124, such as conveyor or laminator speed, production line speed, laminator temperature, and height between layers, can be adjusted additionally or alternatively.

[0067] like Figure 2 As shown in the non-limiting examples, during the manufacturing process, a scanner 146 (e.g., laser or optical scanner, 3D camera, 2D camera, or multiple lasers and / or cameras) is projected from the measuring device 142 onto the surface of the plate. In some instances, the sensor 140 may employ a single camera or multiple cameras to increase the field of view. Alternatively, the imaging system may be used to stitch together multiple images from multiple angles and / or sensors to present a 3D image, i.e., combining images from multiple types of imaging (e.g., spectral, NIR, IR imaging, etc.) for generating the composite image.

[0068] The position and / or illumination of sensor 140 are closely related to its performance. For example, natural or ambient light can vary too much, causing system performance to change at different times of the day. Controlled artificial and / or structured light (e.g., lasers, generated monochromatic and / or polychromatic light, etc.) can have a positive impact on system performance. Sensor 140 can be positioned to provide scanning with a predetermined alignment, such as on a predetermined axis relative to the transport direction or on one or more predetermined multi-axis axes, which may be specific to the monitored area of ​​the transport system and / or based on a stage of the manufacturing process.

[0069] Due to the nature of the manufacturing process (e.g., the use of volatile chemicals), the systems and technologies employed may have protective layers, coatings, and / or other features to protect various system components (e.g., from shock, high temperatures, etc.). Actuators, robotic arms, metals, bearings, gears, motors, carriages, etc., used in various systems may also employ one or more such features to prevent contamination and / or impact. Some devices are prone to foam buildup, which can be mitigated by using coverings on moving parts. For example, cameras may have a fluid flow (e.g., air) that can be used to deflect foam droplets to prevent them from impacting the lens.

[0070] Data corresponding to the monitored parameters (e.g., foam height, consistency, growth rate, etc.) are transmitted from sensor 140 to control circuit 220 in a feedback loop. This data is analyzed by one or more algorithms to determine the foam volume, height, and / or position on substrate 108 and / or relative to other foam flows. The results of the algorithms (e.g., the volume of flow 134 at the left or right edge, the volume growth fill rate at a specific time / location throughout the manufacturing process, etc.) instruct control circuit 220 whether to adjust the fluid application, thereby causing actuator 130 (e.g., fixed to one or more mounting brackets arranged above substrate 108) to adjust the position or orientation of the one or more application devices 104 to a desired set point. For example, actuator 130 may move the application device 104 in one or more of six axial directions (forward / backward, left / right, up / down, pitch, yaw, roll) to adjust the flow 134. As a result, the foam flow 134 is more uniformly distributed.

[0071] In some instances, system 100 may include one or more control mechanisms 127 configured to adjust one or more operating parameters corresponding to one or more components of system 100 (e.g., mixing nozzle 102, application device 104, conduit 110, valve and / or pump 112, laminator 124, etc.). For example, the one or more control mechanisms 127 may include one or more user interfaces (e.g., user interface 124), levers, tubes, handles, buttons, mounting brackets, clamps, knobs, switches, etc., configured for manual adjustment by an operator. Furthermore, control circuitry 220 generates an indicator corresponding to the adjustment amount and provides this indicator to display 126 or other user interface 214 to the operator to notify them of manual adjustment.

[0072] In some instances, control circuitry 220 is configured to submit information (e.g., sensor data) to an operator. This information can be alphanumeric, graphical, audible, etc., to inform the operator of the status of the board being manufactured and / or the manufacturing process. In some instances, the display can present information as a graphic showing one or more components of the system, which can present a relative and / or comparative image of measured parameters with desired parameters (e.g., the position and / or orientation of the application device). The image can include text, graphics, or other indicators to draw the operator's attention to areas of interest and / or instruct the operator to resolve identified problems. Instructions can include movements (e.g., adjustments to the position and / or orientation of the application device, delivery speed, etc.) and / or adjustments to the fluid composition according to the desired output.

[0073] Furthermore, the display can present images of the manufactured board at one or more stages of the manufacturing process. As disclosed herein, the display can identify areas (e.g., on the surface of the board) that have been determined to correspond to one or more features located outside a desired range or threshold.

[0074] Although Figure 2 A single sensor 140 is shown, but multiple sensors of different types can be used from a single location, from multiple locations, from multiple angles to simultaneously, periodically, and / or at specific intervals measure common and / or different parameters during the manufacturing process to collect influential data as needed, thereby ensuring proper control of the various systems and subsystems disclosed herein.

[0075] Figure 3An exemplary detail 150 shows the foam flow 134 and substrate 108 monitored during the manufacturing process by a scan 146 using sensor 140. As shown, the scan can be configured as a linear scan along the width of substrate 108, or multiple linear scans along the width or at any other angle relative to the direction of travel 132. Furthermore, the scan can focus on specific features of the process (e.g., foam flow 134) or can extend beyond the edge 163 of substrate 108.

[0076] Therefore, sensor 140 measures one or more features of the foam and / or board, the amount of fluid 134 flowing, the position of fluid 134 on substrate 108, the position of the edge 152 of fluid 134 on substrate 108, the angle 131 of fluid 134 contacting substrate 108, the rate of change of the angle 131 of fluid contacting substrate 108, the volume of fluid 134 on substrate 108, the volume growth rate, the centroid of fluid 134 on substrate 108, the rate of change of the centroid, the width 154 of fluid 134, and the growth rate of width 154. The following are examples of non-limiting phenomena: the height 156 of the fluid 134 on the substrate 108, the growth rate of the height 156, the consistency of the fluid 134, the temperature of the fluid 134, the rate of temperature change, the presence of bubbles 160 in the foam, the presence of incomplete mixing, the abnormal color of the foam, inconsistent flow from the application device, or foam accumulation on the substrate or the application device, foreign matter 158, the alignment or position 164 of the substrate 108 relative to the direction of travel 132, the conveying speed, or cracks or compression 162 of the substrate 108.

[0077] Measurement results from sensor 140 can be transmitted to control circuit 220 via wired or wireless channels. Control circuit 220 uses the measurement results to identify problems in the manufacturing process and to identify adjustments to the corresponding components to correct these problems.

[0078] For example, a measured feature can be compared with a stored optimized feature, which is, for example, stored in a threshold list in memory 222 of the control circuit 220. If the difference is within an appropriate tolerance range, the measured feature will not be classified as a defect. However, if the measured feature is outside the threshold range, the control circuit 220 will designate the feature as a defect. The measured feature can then be compared with a second threshold, which can determine whether adjustment is needed.

[0079] For example, if the volume of fluid on the substrate is higher than a desired threshold level, but the flow rate decreases at an appropriate rate, the algorithm can determine that no adjustment is needed, and the system continues to monitor the process. However, if in this instance the volume of fluid is higher than the desired threshold level, and the flow rate is stable or increasing, the algorithm can determine that adjustments are needed to the pump 112 or valve position (to adjust the flow rate), the mixing nozzle 102 (to adjust the composition balance), the heater (to adjust the temperature), the delivery system (to adjust the speed), and so on—these are just a series of non-limiting examples. If defects are identified and / or adjustments are made, further testing can be performed later in the manufacturing process to determine whether the adjustments provide the expected results.

[0080] In some instances, additional tests can be performed on the finished board 125 at a testing station configured to measure the features described herein, as well as the flatness and / or hardness of the board as it passes through the station. In this case, as described herein, a sensor (e.g., a laser scanner) can scan the foam and / or board throughout the manufacturing process, transmitting this information to control circuitry 220, which can then identify features and / or areas of the board that may require further testing (e.g., additional scans, testing the compressive strength of the finished board 125, etc.). In some instances, control circuitry 220 generates coordinates to guide the additional testing system to the identified features and / or areas.

[0081] For boards requiring additional testing, another testing station can be set up along the conveyor system. Coordinates can be provided to one or more devices at the second testing station to locate areas identified as requiring additional testing. The additional testing can be performed, for example, by flatness and / or hardness testing performed by a computer numerical control (CNC) tester. Alternatively, compressive strength can be measured manually and / or using non-invasive testing equipment (e.g., laser scanning, optical scanning, NIR scanning, IR scanning, ultrasonic, etc.) or other measuring devices. In some instances, the conveyor system can guide boards requiring additional testing to the second testing station, while boards without identified defects proceed to the finishing and / or packaging area.

[0082] All testing systems, technologies, and applications can provide inputs that allow adjustment of any parameter output, and no single testing system, technology, or application is limited to a single parameter.

[0083] Based on the results of scanning and / or compressive strength tests, one or more parameters of the manufacturing system can be adjusted to correct for measured defects. Non-limiting examples include the temperature of the applied material, fluid flow rate, fluid pressure, the location or orientation of the fluid application device, deposition volume, and / or the position of the plate on the production line; these parameters can be adjusted to reduce the presence of defects in the finished plate. In some instances, a quality score can be assigned to the plate, an alarm can be provided to the user, the plate can be marked, or other appropriate methods can be used.

[0084] In some instances, system 100 can be controlled by manually programming control circuitry 220, including modifying thresholds and guiding sensors 140 and / or other testing devices to desired locations throughout the process and / or on board 125. For example, a testing platform can be integrated into an online manufacturing process. Online processes are characterized by completed boards continuously passing through one or more service or testing stations. For example, conveyor system 124 can advance completed boards 125 to a testing station.

[0085] Figure 4 A block diagram of an exemplary embodiment of control circuitry 220 is shown. Control circuitry 220 includes a communication interface 216 for sending and receiving information to and from one or more systems, sensors, devices, and / or components. Interface 216 is operatively connected to a user interface 214, a processor 218, a memory 222, and sensors 140, testing devices or systems 202 (e.g., a flatness and / or hardness tester), an electric carriage 144, an application device 104, a delivery system 124, and a display 126. Sensor 140 may include one or more of a laser scanner 205, an infrared sensor 206, an ultrasonic sensor 208, a mechanical sensor 210, a thermal sensor 212, an optical imaging system 213 (e.g., a vision camera), a force or pressure sensor 215, and / or a hyperspectral imaging system 217, these are merely a series of non-limiting examples.

[0086] Figure 4 The exemplary control circuitry 220 includes a processor 218 capable of executing computer-readable instructions, including one or more artificial intelligence or machine learning algorithms (such as neural networks, deep learning, etc.), and can be a general-purpose computer, laptop computer, tablet computer, mobile device, server, head-up display (HUD), virtual or augmented reality display (VR / AR), and / or any other type of computing device integrated into or remotely from system 100. In some instances, the control circuitry 220 is implemented in a cloud computing environment, on one or more physical machines, and / or on one or more virtual machines and / or containers.

[0087] In some instances, the HUD or VR / AR display can present content associated with the sensor 140 and / or testing device 202 on display 126. For example, measurement results (e.g., overlays, graphics, text, etc.) superimposed on images (e.g., captured images and / or computer-generated graphics) of the manufacturing system 100 can be visually presented. In some instances, an operator can view the superimposed measurement results and guide adjustments to relevant parameters, which can be made, for example, through user interface 214. For example, proposed changes can be displayed on display 126 before implementation to ensure that the changes produce the desired results.

[0088] Memory 222 contains a matrix or other list 224 of feature thresholds, a matrix or other list 226 of operation parameter values, and one or more algorithms 228. For example, control circuitry 220 is configured to access memory 222 storing the lists 224, 226 of values ​​and the algorithms 228. In some instances, control circuitry 220 and memory 222 are integrated (e.g., within a computing device). In some instances, control circuitry 220 is connected to a network interface to access the lists 224, 226 of values ​​and / or the algorithms 228 via a communication network.

[0089] In some instances, storage device 222 or another storage device may include volatile or non-volatile memory, such as ROM, RAM, magnetic storage memory, optical storage memory, or combinations thereof, and may be integrated with control circuitry 220, located at a remote location, or a combination of both. Furthermore, various control parameters (e.g., for operating sensor 140, test device 202, motorized carriage 144, application device 104, and / or delivery system 124) may be stored in storage device 222 along with codes configured to provide specific outputs during operation of system 100.

[0090] Control circuitry 220 is configured to receive one or more feature measurements to determine board integrity. For example, sensor 140 scans the board to measure such features, and the feature data is sent to control circuitry 220, which can determine board integrity based on comparisons between measured features and values ​​stored in memory 222 using lookup tables, algorithms, and / or models stored in memory 222. For example, control circuitry 220 compares measured foam features (e.g., height, flow rate, temperature, expansion rate, etc.) with a threshold 224 stored in memory 222 to determine if the measured value is outside an appropriate threshold. In some instances, threshold 224 includes a setpoint or rate of change (increasing or decreasing) that can be considered relative to another relevant value (e.g., application rate and delivery speed), all of which can be adjusted by an operator or as a result of machine learning updates.

[0091] Based on the comparison, control circuit 220 can determine whether adjustments are needed and / or whether alternative or additional tests are required. If adjustments are needed, control circuit 220 accesses a list of operating parameters 226, which may correspond to one or more feature thresholds 224. Based on the relationship between features and parameters, control circuit 220 can employ algorithms to determine the type and / or amount of adjustments required for a particular system.

[0092] If additional testing is required, the control circuit 220 can identify features and / or areas of the board for the sensor 140 and / or testing device 202 to perform additional testing. Therefore, information about any defects can be compiled and compared with one or more stored quality characteristic values ​​to generate scores, alarms, or instructions for modifying the manufacturing system 100.

[0093] In one example, control circuitry 220 determines the type and severity of a defect in board 125 and provides this information to manufacturing system 232. One or more operating values ​​226 (e.g., flow rate, pressure, temperature, location of deposits, flow position, conveyor speed, etc.) can then be adjusted to ensure that defects are corrected throughout the manufacturing process.

[0094] Based on the collected measurements, any necessary adjustments to the operating parameter values ​​can be determined empirically. In some instances, control circuitry 220 is configured to interpolate and correct the operating values. As described herein, the operating parameter values ​​can then be adjusted to correct defects. Control circuitry 220 can calculate, employ algorithms, models stored in storage device 222, or apply one or more machine learning techniques to determine the desired adjustments.

[0095] The algorithms used by system 100 to determine defects and / or control parameters are not limited to a specific type and / or application, and may employ a single algorithm or multiple algorithms that can be applied simultaneously, periodically, sequentially, and / or in response to specific triggers. For example, if the absolute value of a measured feature is identified as being within a corresponding threshold limit, but the rate of change exceeds the corresponding threshold, control circuit 220 may continue to monitor the feature and / or apply additional algorithmic processing to ensure that the problem does not occur or is mitigated.

[0096] Exemplary algorithms related to detecting individual location features of foam flow (e.g., quantity of foam flow, three-dimensional location, edge location, contact angle, volume, volume-based centroid, height, consistency, temperature, etc.) and multi-location features of foam flow or wave measurement (e.g., volume growth rate, width growth rate, height growth rate, contact angle change rate, centroid change rate, etc.) may include, but are not limited to, one or more of principal component analysis, partial least squares, discriminant analysis, Canny edge detector, ridge detection, speckle detector (i.e., Laplacian operator of Gaussian) and / or semi-empirical models (e.g., involving chemical reaction kinetics, fluid dynamics, thermodynamics, mass transfer, and space filling).

[0097] Exemplary algorithms related to detecting processing problems affecting foam integrity (e.g., the presence of bubbles, the presence of poor mixing, foam color, blockage / blockage of the application device, foam accumulation in the field of view, etc.) and detecting foam-independent features affecting foam board production (e.g., foreign object detection, position of the face layer / substrate (e.g., alignment), conveyor speed, breakage of the face layer / substrate, etc.) may include, but are not limited to, one or more of Bayesian classifiers, support vector machines, decision trees, boosting algorithms, neural networks, radial basis function networks, clustering algorithms, K-nearest neighbors, deep learning, linear regression, multiple linear regression, ensemble techniques, cost-sensitive learning, principal component analysis, You Only Look Once (YOLO), region-based convolutional neural networks (R-CNN), and / or single-frame detectors (SSD).

[0098] Alternatively, the control circuit 220 may receive input from the user interface 214 for inputting commands and / or custom controls (e.g., via a graphical user interface (GUI), a touch screen, a communication path, etc.).

[0099] Figure 5 This is a flowchart illustrating an exemplary machine-readable instruction 300, according to Figures 1 to 4 The example provided herein, the exemplary machine-readable instruction 300, can be derived from... Figure 2 and Figure 4 The control circuit 220 executes to determine the characteristics of the manufactured board (e.g., board 125) and adjust the operating values ​​of the manufacturing system (e.g., manufacturing system 100), or provide information about the characteristic adjustment.

[0100] At block 302, a sensor (e.g., sensor 140) measures one or more features corresponding to the distribution of one or more fluids (e.g., fluid or foam 106) applied to a substrate (e.g., substrate 108). At block 304, data corresponding to the one or more features is received at a control circuit (e.g., control circuit 220). At block 306, the one or more measured features are compared in the control circuit with one or more feature thresholds.

[0101] Based on the comparison results, the control circuit determines whether the measured feature has exceeded a feature threshold level. For example, at block 308, the control circuit may determine that the measured feature has exceeded a first lower feature threshold level and determine that no adjustment is needed or only a first minor adjustment is required. If the first feature threshold level has not been exceeded, the method returns to block 302 and continues to measure the one or more features.

[0102] However, if the first feature threshold level has been exceeded, the method continues to block 310, where the control circuit determines whether the measured feature exceeds a second, higher feature threshold level. For example, the first threshold may have a range exceeding a predetermined target value by 5%, and the second threshold may have a range exceeding a predetermined target value by 10%.

[0103] If the measured feature exceeds a first feature threshold level but does not exceed a second, larger feature threshold level, the method proceeds to block 312, at which point an adjustment command is triggered. For example, the control circuitry may generate a first adjustment amount for one or more operating parameters and provide it to the operator (e.g., via a display or other user interface). In some instances, the control circuitry may command a first adjustment to the one or more operating parameters (e.g., the position or orientation of the application device 104), for example, to a robotic device, one or more actuators, and / or other system components driving the manufacturing process.

[0104] If the measured feature has exceeded the second feature threshold level (and the first feature threshold level), the method proceeds to block 314, at which point another adjustment command is triggered. For example, the control circuitry may generate a second adjustment amount for one or more operating parameters and provide it to the operator. In some instances, the control circuitry may command a second adjustment to the one or more operating parameters (e.g., the position or orientation of the application device 104).

[0105] The methods and systems described herein can be implemented using hardware, software, and / or a combination of hardware and software. Exemplary implementations include application-specific integrated circuits (ASICs) and / or programmable control circuits.

[0106] This document describes the technology in a comprehensive, clear, and concise manner to enable those skilled in the art to implement it. It should be understood that preferred embodiments of the technology have been described above, and various modifications may be made thereto without departing from the spirit or scope of the technology as set forth in the appended claims. Furthermore, the examples provided are not exhaustive but are merely illustrative of several embodiments falling within the scope of the claims.

Claims

1. A system for manufacturing foam boards, comprising: An application device for dispensing one or more fluids onto a substrate; One or more sensors are configured to scan one or more fluid flows on a substrate and measure one or more characteristics of the fluids, wherein the one or more characteristics include one or more of the following: volume growth rate, width growth rate, height growth rate, rate of change of the angle of contact between the fluid and the substrate, centroid change rate, and temperature rise rate; and The controller is configured to: Compare one or more measured features with one or more feature thresholds; Determine whether a certain feature among one or more measured features falls outside a certain threshold among the one or more feature thresholds; In response to the determination that the feature falls outside the threshold, an adjustment amount for the feature is calculated based on the one or more measured features or thresholds; and Generate a command corresponding to the quantity.

2. The manufacturing system of claim 1, further comprising one or more control mechanisms configured to adjust the one or more operating parameters of the system, wherein the one or more control mechanisms are configured for manual adjustment by an operator.

3. The manufacturing system of claim 2, wherein the controller is further configured to generate an indicator corresponding to the quantity and provide the indicator to a user interface configured to be presented to an operator.

4. The manufacturing system of claim 1, wherein the controller is further configured to: If the feature exceeds a first threshold among the one or more feature thresholds, then one of the one or more operation parameters is adjusted by a first amount; and If the feature exceeds the second threshold among the one or more feature thresholds, the operation parameter is adjusted by a second amount.

5. The manufacturing system of claim 1, wherein the one or more operating parameters include one of flow rate, position or orientation of the application device, pressure, temperature, delivery speed, composition or mass balance, and position of the deposition fluid.

6. The manufacturing system of claim 1, wherein the one or more sensors are configured to monitor a substrate region downstream of the point where the one or more fluids come into contact with the substrate.

7. The manufacturing system of claim 1, further comprising a transport system for advancing the one or more fluids and the substrate along a transport path, wherein the one or more sensors are configured to scan the one or more fluids as the substrate advances along the transport path.

8. The manufacturing system of claim 7, wherein the one or more sensors are configured to scan the one or more fluids along an axis perpendicular to the delivery path.

9. The manufacturing system of claim 1, further comprising a conveying system for advancing the foam board along a conveying path, wherein the one or more sensors are configured to scan the foam board as it advances along the conveying path.

10. The manufacturing system of claim 9, wherein the one or more sensors are configured to scan the foam board along an axis perpendicular to the transport path.

11. The manufacturing system of claim 9, wherein the one or more sensors are configured to scan the foam board along multiple axes.

12. The manufacturing system of claim 1, wherein the one or more sensors are fixed to a movable mounting base configured to adjust the orientation or position of the one or more sensors relative to a substrate.

13. The manufacturing system of claim 1, wherein the one or more sensors comprise one or more of a laser scanner, an optical imaging system, a hyperspectral imaging system, a near-infrared sensor, an infrared sensor, an ultrasonic sensor, or a thermal sensor.

14. The manufacturing system of claim 1, wherein the one or more features include one or more of the following: the amount of fluid flow, the position of the fluid on the substrate, the position of the edge of the fluid on the substrate, the angle of contact between the fluid and the substrate, the volume of the fluid on the substrate, the centroid of the fluid on the substrate, the height of the fluid on the substrate, the consistency of the fluid, and the temperature of the fluid.

15. The manufacturing system of claim 1, wherein one or more features include one or more of the following: the presence of bubbles in the foam, incomplete mixing, abnormal color of the foam, inconsistent liquid flow from the application device, or foam accumulation on the substrate or the application device.

16. The manufacturing system of claim 1, wherein one or more features include one or more of foreign matter, substrate alignment or positioning, transport speed, or substrate cracks or compression.

17. The manufacturing system of claim 1, wherein one or more fluids react to generate polyurethane or polyisocyanurate foam.

18. The manufacturing system of claim 1, wherein the controller is further configured to apply a machine learning algorithm to generate the one or more thresholds.

19. The manufacturing system of claim 1, wherein the controller is further configured to: The features of one or more measurements are stored in a storage device; Calculate an average characteristic value based on the characteristics of one or more measurements taken within a predetermined time period; and The one or more thresholds are generated based on the average feature value and one or more tolerance ranges.

20. A system for manufacturing foam boards, comprising: An application device that dispenses one or more fluids onto a substrate during the liquid chemical application stage of the manufacturing process; One or more sensors are configured to scan one or more fluid flows on a substrate and measure one or more characteristics of the fluids, wherein the one or more characteristics include one or more of the following: volume growth rate, width growth rate, height growth rate, rate of change of the angle of contact between the fluid and the substrate, centroid change rate, and temperature rise rate; and The controller is configured to: Compare one or more measured features with one or more feature thresholds; and The position or orientation of the applying device is adjusted in response to one of the one or more measurement features falling outside one of the thresholds of the one or more features.

21. The system of claim 20, wherein the one or more sensors include a first sensor configured to monitor a substrate region downstream of the point where the one or more fluids come into contact with the substrate.

22. The system of claim 21, wherein the one or more sensors include a second sensor configured to monitor the finished board.

23. The system of claim 22, wherein the second sensor comprises one or more of a flatness tester, a hardness tester, a density tester, a laser scanner, an optical imaging system, a hyperspectral imaging system, a near-infrared sensor, an infrared sensor, an ultrasonic sensor, or a thermal sensor.

24. A method for manufacturing foam board, comprising: Scan one or more fluid flows on a substrate using a sensor; The sensor measures one or more characteristics corresponding to the distribution of one or more fluids applied to the substrate, wherein the one or more characteristics include the amount of fluid flow, the position of the fluid on the substrate, the position of the fluid edge on the substrate, the angle of contact between the fluid and the substrate, the volume of the fluid on the substrate, the centroid of the fluid on the substrate, the consistency of the fluid, the volume growth rate of the fluid, the width growth rate of the fluid, the height growth rate of the fluid, the rate of change of the angle of contact between the fluid and the substrate, or the centroid change rate of one or more fluid flows. Data corresponding to one or more features is received at the control circuit; At the control circuit, the one or more measured features are compared with one or more feature thresholds; Identify one or more operating parameters at the control circuit corresponding to the features of the one or more measurements; and The one or more operating parameters are adjusted in response to one or more of the measured features falling outside one or more of the feature thresholds.

25. The method of claim 24, further comprising: If the feature exceeds a first threshold among the one or more feature thresholds, then one of the one or more operation parameters is adjusted by a first amount; and If the feature exceeds the second threshold among the one or more feature thresholds, the operation parameter is adjusted by a second amount.

26. The method of claim 25, wherein the adjustment includes adjustments made by an operator to the control mechanism.

27. The method of claim 25, wherein the adjustment includes adjustments made by the robotic device to the control mechanism.

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