System and method for trim loss optimization for metal industries

[0017] The drawings discussed below and various embodiments used to describe the principles of the present invention in this patent document are for illustration only, and should not be construed as limiting the scope of the present disclosure in any way. Those skilled in the art will understand that the principles of the present disclosure may be implemented in any type of suitably arranged device or system.

[0018] For simplicity and clarity, some features and components are not explicitly shown in each figure, including those features and components illustrated with respect to other figures. It will be understood that all the features illustrated in the drawings can be adopted in any of the embodiments described in this patent document. The omission of features or components from a particular drawing is for the purpose of simplicity and clarity, and is not intended to imply that the feature or component cannot be adopted in the embodiment(s) described with respect to the drawing.

[0019] figure 1 Illustrated is an example industrial process control and automation system 100 according to the present disclosure. Such as figure 1 As shown in, the system 100 includes various components that facilitate the production or processing of at least one product or other material (such as cutting or trimming metal parts in the metal industry). For example, the system 100 may be used to facilitate the control of components in one or more industrial plants. Each workshop represents one or more processing facilities (or one or more parts thereof), such as one or more manufacturing facilities for producing at least one product or other materials. Generally speaking, each workshop can implement one or more industrial processes, and can be individually or collectively referred to as a process system. A process system generally refers to any system or part of it that is configured to process one or more products or other materials in some way.

[0020] in figure 1 Here, the system 100 includes one or more sensors 102a and one or more actuators 102b. The sensor 102a and the actuator 102b represent components in the process system that can perform any of a wide variety of functions. For example, the sensor 102a can measure a wide variety of characteristics in the process system, such as flow, pressure, or temperature. In addition, the actuator 102b can modify a wide variety of features in the process system, such as the actuation of a metal cutting machine. Each of the sensors 102a includes any suitable structure for measuring one or more characteristics in the process system. Each of the actuators 102b includes any suitable structure for acting on or affecting one or more conditions in the process system.

[0021] At least one network 104 is coupled to sensors 102a and actuators 102b. The network 104 facilitates interaction with the sensor 102a and the actuator 102b. For example, the network 104 may transmit measurement data from the sensor 102a to the actuator 102b and provide control signals to the actuator 102b. The network 104 may represent any suitable network or combination of networks. As a specific example, the network 104 may represent at least one Ethernet network (such as an Ethernet network supporting the FOUNDATIONFIELDBUS protocol), an electrical signal network (such as a HART network), a pneumatic control signal network, or any other or additional type The internet.

[0022] The system 100 also includes various controllers 106. These controllers 106 may be used in the system 100 to perform various functions to control one or more industrial processes. For example, the first set of controllers 106 may use measurements from one or more sensors 102a to control the operation of one or more actuators 102b. The second set of controllers 106 may be used to optimize the control logic or other operations performed by the first set of controllers. The third group of controllers 106 can be used to perform additional functions. Therefore, the controller 106 can support a combination of methods such as regulatory control, advanced regulatory control, supervisory control, and advanced process control.

[0023] Each controller 106 includes any suitable structure for controlling one or more aspects of an industrial process. At least some of the controllers 106 may, for example, represent proportional-integral-derivative (PID) controllers or multi-variable controllers, such as controllers that implement model predictive control (MPC) or other advanced predictive control (APC). As a specific example, each controller 106 may represent a computing device running a real-time operating system, a WINDOWS operating system, or other operating systems.

[0024] At least one network 108 connects the controller 106 and other devices in the system 100. The network 108 facilitates the transfer of information between components. The network 108 may represent any suitable network or combination of networks. As a specific example, the network 108 may represent at least one Ethernet network.

[0025] Operator access to the controller 106 and other components of the system 100 and interaction with the controller 106 and other components of the system 100 may occur via various operator stations 110. Each operator station 110 can be used to provide information to and receive information from the operator. For example, each operator station 110 may provide information identifying the current state of the industrial process to the operator, such as the values ​​of various process variables and warnings, alarms, or other states associated with the industrial process. Each operator station 110 may request information that affects how the industrial process is controlled, such as by requesting set points or control modes of process variables controlled by the controller 106 or other information that changes or affects how the controller 106 controls the industrial process. This may include requesting this information from the controller 106 or from other devices, such as the historian 114 or the server 116. In response to such requests, each operator station 110 can receive the requested information. Each operator station 110 includes any suitable structure for displaying information to and interacting with the operator. For example, each operator station 110 may represent a computing device running a WINDOWS operating system or other operating systems.

[0026] Multiple operator stations 110 may be combined together and used in one or more control rooms 112. Each control room 112 may include any number of operator stations 110 in any suitable arrangement. In some embodiments, multiple control rooms 112 may be used to control an industrial plant, such as when each control room 112 contains an operator console 110 that is used to manage discrete parts of the industrial plant.

[0027] Here, the control and automation system 100 also includes at least one history database 114 and one or more servers 116. The history library 114 represents a component that stores various information about the system 100. The history repository 114 may, for example, store information generated by various controllers 106 during the control of one or more industrial processes. The history repository 114 includes any suitable structure for storing information and facilitating the retrieval of that information. Although shown here as a single component, the history library 114 may be located anywhere in the system 100, or multiple history libraries may be distributed in different locations in the system 100.

[0028] Each server 116 represents a computing device that executes a user's application program or other application program of the operator station 110. Application programs may be used to support various functions of the operator station 110, the controller 106, or other components of the system 100. Each server 116 may represent a computing device running a WINDOWS operating system or other operating systems. It should be noted that although shown as being local within the control and automation system 100, the functionality of the server 116 may be remote from the control and automation system 100. For example, the functions of the server 116 may be implemented in a computing cloud 118 or a remote server communicatively coupled to the control and automation system 100 via the gateway 120.

[0029] In some embodiments, the control and automation system 100 includes or is part of a manufacturing system that produces metal parts or metal products. Manufacturing companies that produce metal parts usually supply metal parts in the form of ingots, which are obtained by casting liquid metal into a square section. Some examples of ingots include slabs (for example, 500-1800 mm wide and 50-300 mm thick), billets (for example, 40 to 150 mm²), and blooms (150 to 400 mm²). In some systems, continuous casting is used to cast liquid metal into slabs, billets and blooms. These shapes are further processed by hot rolling, forging or extrusion to produce materials in standard forms such as plates, sheets, rods, pipe bodies and structural segments.

[0030] Almost all major metal products (for example, pipes, tubes, hollow bars, ship plates, coils, angle steel, I-beams, steel bars, etc.) can be made from flat sheets. Currently, metal parts cutting planning is facing various optimization challenges for interdependent cutting processes (including cutting processes with multiple stages). The interdependent stages of the coil cutting process can include metal rolling, slitting, secondary slitting, uncoiling, and flat sheet cutting. figure 2 The diagram illustrates the common steps or stages that are usually implemented in the forming process of metal parts.

[0031] Metal parts planning is under pressure to reduce the conversion loss from coil material to final product (for example, pipe, hollow section, angle steel, etc.). Different types of equipment are used in the process of converting from flat sheets to final products. Based on the process and customization requirements involved in the conversion, the flat sheet requirements and tolerances are changed. In the metal rolling process, a higher thickness metal sheet (such as aluminum) is converted into a lower thickness sheet having an elongated length. Optimizing this conversion constitutes a three-dimensional conversion problem.

[0032] Due to diversified industrial applications (for example, shipbuilding, industrial and steel manufacturing, oil and gas applications, construction (including buildings, infrastructure, etc.), engineering, and major infrastructure applications), the complexity of the cutting and slitting process has been Increase over time. In some cases, consumers need customized sizes or customized sizes and shapes according to specific requirements. In addition, the transportation, availability, and material handling facilities of metal products create a major demand for customized sizes.

[0033] Due to different requirements at different stages, producing cutting solutions is very complicated for the metal industry. A comprehensive solution for the product is needed. Some metal manufacturing processes only consider optimization in a single dimension (for example, only length), such as length cutting optimization. Some processes consider optimization of two dimensions (for example, length and width), such as the winding and unwinding process and the flat sheet cutting process. Some processes consider optimization in three dimensions (for example, length, width, and thickness), such as a rolling process, where thickness is converted to length.

[0034] To optimize the slitting process, the metal industry will benefit from a complete end-to-end solution for parent roll manufacturing in the previous two stages (hot rolling and cold rolling). Such solutions will help reduce cutting losses in the next stages.

[0035] To solve these and other problems, one or more components of the system 100 may support mechanisms for cutting loss optimization in the metal industry. For example, this function may be implemented in the operator station 110, the server 116, or the computing cloud 118 or remote server. Additional details about this feature are provided below.

[0036] although figure 1 An example of an industrial process control and automation system 100 is shown, but it can be figure 1 Make various changes. For example, the system 100 may include any number of sensors, actuators, controllers, networks, operator stations, control rooms, history libraries, servers, and other components. In addition, figure 1 The composition and arrangement of the system 100 in is for illustration only. According to specific requirements, components can be added, omitted, combined, further subdivided, or placed in any other suitable configuration. In addition, specific functions have been described as being performed by specific components of the system 100. This is just for illustration. Generally speaking, control and automation systems are highly configurable and can be configured in any suitable way according to specific needs. In addition, figure 1 An example operating environment in which cutting loss optimization can be performed is illustrated. This function can be used in any other suitable system.

[0037] image 3 Illustrated is a block diagram illustrating an example process 300 for crop loss optimization according to the present disclosure. The process 300 can be used, for example, to optimize the cutting loss during the forming or manufacturing of metal parts, including industrial process control and automation systems (such as, figure 1 System 100). In some embodiments, the process 300 may be performed by one or more components of the system 100, such as the operator station 110, the server 116, or the computing cloud 118. However, the process 300 can be used with any other suitable system. For ease of explanation, the process 300 will be described as being performed by a computing device.

[0038] At step 301, the computing device receives one or more metal parts order requirements from the user. This may include the user entering this (these) order request at the operator station. The user can input or select one or more metal parts customization requirements for processing or manufacturing different sizes, shapes, quantities, and metal parts composition profiles. User input may also include one or more conversion paths. Each conversion path indicates that the initially manufactured product shape can be converted into an intermediate product shape (for example, bloom, slab, or small billet) and/or final product shape (for example, I-beam, track, plate, coil , Rod, rod, tube, etc.) one or more pieces of equipment.

[0039] At step 303, the computing device combines or isolates the metal part order requirements based on the metal part composition profile and thickness. That is, metal pieces with the same or similar composition distribution or thickness are grouped together, and metal pieces with different composition distributions or thicknesses are placed in different groups. E.g, Figure 4 Illustrated is an example of a combination of customized requirements grouped by thickness for different grades of pipes with the same metal piece specifications according to the present disclosure. Such as Figure 4 As shown in, metal pieces with the same shading (and the same number) have the same thickness, and can be grouped together in a stock for processing in a manufacturing process. Once the computing device groups the subscription requirements, these subscription requirements are input to the size conversion engine executed by the computing device.

[0040] At step 305, the size conversion engine analyzes the order requirements and performs the conversion of the roll size associated with the order requirements to generate input for the cutting algorithm described in step 313 below. Specifically, the size conversion engine uses an effective decomposition of a three-dimensional problem to a two-dimensional problem based on the spatial decomposition to determine the roll width and roll length in order to fulfill each order requirement in an optimized manner. In some embodiments, the size conversion engine operates using the sequence described below as steps 305a to 305e.

[0041] At step 305a, the size conversion engine converts a certain number of customized requirements into a number of blocks required for a specific shape and size based on the weight per meter parameter. The weight per meter is the standard industrial value for the density of metal parts. For example, the tube customer can be given one or more specifications, such as diameter, length, thickness, metal properties, and quantity (in terms of total weight). The size conversion engine converts these into the required number of blocks based on specifications and tolerances.

[0042] At step 305b, the size conversion engine converts one or more three-dimensional shapes indicated in the order request into a flat sheet (two-dimensional). The number of sheets required to complete the order requirement is derived from the number of required blocks.

[0043] At step 305c, the size conversion engine considers the width of each block along with the width of the roll that will be produced by the cutting algorithm.

[0044] At step 305d, the size conversion engine sums the lengths of all blocks to obtain the length required to complete the specific order requirements.

[0045] At step 305e, the size conversion engine performs conversion for each order request and provides input (for example, length and width) to the cutting algorithm.

[0046] At step 307, the computing device obtains multiple interdependent transformations or metal part forming machine parameters for use as input to the cutting algorithm. The machine parameters obtained in step 307 may vary depending on the embodiment and the type(s) required by the order. Generally speaking, the key machine parameters that can be input to the cutting algorithm include the following:

[0047] ·Deckle of the machine (for example, maximum fixed amplitude and/or minimum fixed amplitude)

[0048] ·Edge cutting requirements

[0049] ·Cutting length

[0050] · Number of slitting machines

[0051] · Weight handling details

[0052] ·Minimum roll width

[0053] ·Max roll width

[0054] ·Minimum diameter

[0055] ·The maximum diameter.

[0056] At step 309, based on the route selected for each order requirement, the computing device determines the conversion or metal part forming machine for each order requirement. To make this decision, the calculation device considers machine tolerances, welding tolerances, and/or bending and springback tolerances. Each type of machine (eg, guide making machine, winding machine, forming machine, etc.) has its own tolerances and losses. These tolerances are added to the width before slitting the parent roll. There are two types of springback tolerance: positive when elongation occurs, and negative when contraction occurs. Depending on the embodiment, the computing device may consider positive rebound, negative rebound, or both. Figure 5 Illustrated are examples of different rebound factors that may occur during bending operations. In addition, the computing device can determine one or more alternative routes for each product. For example, there can be two or more manufacturing routes for the same product. Each route can include machines of different specifications, where losses and tolerances are different for different machines. Alternative routes can be used to effectively select routes based on loss and availability.

[0057] At step 311, the computing device converts all the tolerances determined in step 309 (for example, welding tolerance, metal part tolerance (positive/negative springback, overlap tolerance, etc.) into edge cutting parameters for use as a cutting algorithm This can include: In the cutting algorithm, the calculation device adds all the tolerances of each metal forming machine to the width in a specific customized requirement during the cutting. As a specific example, consider having a diameter d Of the tube. Therefore, the material width can be 3.14 x d. And, the final width to be cut on the winder is the material width plus these tolerances.

[0058] At step 313, the computing device obtains the output of the size conversion engine from step 305, the machine parameters from step 307, and the edge cutting parameters from step 311. These are provided to the cropping algorithm as inputs in a two-dimensional form.

[0059] At step 315, the computing device uses the aforementioned input to execute the cropping algorithm. The cropping algorithm produces one or more optimized solutions, which may include one or more of the following outputs:

[0060] ·The best use of fixed amplitude

[0061] ·Minimized cutting loss

[0062] ·The best combination of groups and customized requirements

[0063] ·The optimal number of parent rolls required.

[0064] In some embodiments, the cropping algorithm uses linear programming techniques to arrive at a solution.

[0065] At step 317, the computing device uses one or more parent roll requirements (as determined in step 315 by the cutting algorithm) for generating sub-rolls as the route and machine for the current plan and other alternative routes or routes. Input to the three-dimensional conversion engine of a reel machine (for example, a multi-winder). Other inputs are also provided to the 3D conversion engine, including the type of process (cold rolling or hot rolling), one or more machine parameters from step 307 (for example, the number of stages), one or more Metal properties 319 and temperature distribution information 321. It helps to make correct decisions to assess the suitability of a set of customized routes. For example, after cutting, the best route can be evaluated based on cutting loss. Using the input parameters provided, the computing device can execute a three-dimensional conversion engine to calculate the number of parent rolls required based on the thickness. That is, the parent roll has a greater thickness than the final product.

[0066] At step 323, based on the input, the computing device determines whether only the hot rolling process or both the hot rolling process and the cold rolling process will be performed. If a hot rolling process is to be performed, followed by a cold rolling process, the process 300 moves to step 325. Otherwise, if only the hot rolling process is to be performed, the process moves to step 329.

[0067] In the case of performing a hot rolling process and then performing a cold rolling process, at step 325, the calculating device calculates the number of coils required for the cold rolling process. This calculation is a higher thickness conversion (for example, three-dimensional) calculation. Then, at step 327, the calculation device uses the thickness of the cold rolling process and the number of parent coils as inputs for calculating the number of coils required for the hot rolling process.

[0068] In the case where only the hot rolling process is performed, step 329 is executed. At step 329, the calculation device calculates the number of coils required for the hot rolling process. For 3D conversion, only stage-wise calculations are implemented.

[0069] although image 3 An example of the process 300 for cutting loss optimization is illustrated, but it can be image 3 Make various changes. For example, although shown as a series of steps, image 3 The various steps shown in can overlap, occur in parallel, occur in a different order, or occur multiple times. In addition, some steps can be combined or removed according to specific needs, and additional steps can be added.

[0070] Image 6 Illustrated is an example device 600 for supporting metal piece cutting loss optimization according to the present disclosure. The apparatus 600 can be used, for example, in the above image 3 The process 300 described. In some embodiments, the apparatus 600 may represent figure 1 The device used in the described operator station 110, server 116, or computing cloud 118. However, the device 600 can be used in any other suitable system.

[0071] Such as Image 6 As shown in, the device 600 includes at least one processor 602, at least one storage device 604, at least one communication unit 606, and at least one input/output (I/O) unit 608. Each processor 602 can execute instructions, such as instructions that can be loaded into the memory 610. The instruction may be associated with a process for optimizing the cutting loss of metal parts. Each processor 602 represents any suitable processing device, such as one or more microprocessors, microcontrollers, digital signal processors, application specific integrated circuits (ASIC), field programmable gate arrays (FPGA), or discrete circuits.

[0072] Memory (memory) 610 and persistent storage (persistent storage) 612 are examples of storage devices 604, which represent the ability to store information (such as data, program code, and/or other suitable information in a temporary or permanent manner) and facilitate Any structure(s) for the retrieval of this information. The memory 610 may represent a random access memory or any other suitable volatile or non-volatile storage device(s). Persistent storage 612 may include one or more components or devices that support long-term storage of data, such as read-only memory, hard drive, flash memory, or optical disk.

[0073] The communication unit 606 supports communication with other systems or devices. For example, the communication unit 606 may include a network interface card or a wireless transceiver that facilitates communication through a wired or wireless network. The communication unit 606 may support communication through any suitable (one or more) physical or wireless communication links.

[0074] The I/O unit 608 allows data input and output. For example, the I/O unit 208 may provide a connection for user input through a keyboard, mouse, keypad, touch screen, or other suitable input device. The I/O unit 608 may also send output to a display, printer, or other suitable output device.

[0075] although Image 6 An example of the device 600 for supporting the optimization of cutting loss of metal parts is shown, but it can be used for Image 6 Make various changes. For example, according to specific requirements, components can be added, omitted, combined, further subdivided, or placed in any other suitable configuration. In addition, the computing device can assume a wide variety of configurations, and Image 6 The present disclosure is not limited to any specific configuration of the computing device.

[0076] As discussed above, the embodiments of the present disclosure provide a system and method capable of the following advantageous technical improvements:

[0077] · Effective spatial decomposition of three-dimensional problems to two-dimensional problems.

[0078] ·The best classification and clustering of customized requirements (for example, customer customized requirements, inventory customized requirements, etc.) based on thickness and metal component profile.

[0079] · During the forming process of metal parts, a cutting solution is produced for any type of shape (eg square, C-shape, I-shape, etc.) formed by at least one metal sheet, strip, or chart (chart) Program.

[0080] · Reduce overall loss or cutting loss during the metal part conversion (for example, sheet making and forming) process.

[0081] ·The correlation between welding tolerance, springback bending factor, and edge cutting concepts in the solution of two-dimensional problems.

[0082] · Effective processing of multiple stages before and after the coil slitting stage.

[0083] · Effective handling of compromises between different purposes.

[0084] · The best use of the defect monitoring system. If the defect is in the middle of the coil, the defect monitoring system can detect the defect, the defective part can be removed, and the order requirements can be assigned to the remaining part of the coil.

[0085] ·Multi-winding machine (for example, winding machine) supporter to evaluate effective production plan and minimum loss at different winding machines.

[0086] In addition, the disclosed embodiments provide a system and method that:

[0087] · Launch through the cloud, and it can reduce infrastructure costs.

[0088] ·Reduce conversion loss.

[0089] · Reduce recycling costs, which leads to a reduction in energy costs.

[0090] · Improve productivity.

[0091] ·Optimize the loss during the coil conversion process.

[0092] ·Effectively serve the customized requirements that can be customized.

[0093] In some embodiments, various functions described in this patent document are implemented or supported by computer programs, which are formed by computer-readable program codes and embodied in computer-readable media. The phrase "computer readable program code" includes any type of computer code, including source code, object code, and executable code. The phrase "computer readable medium" includes any type of medium that can be accessed by a computer, such as read only memory (ROM), random access memory (RAM), hard drive, compact disk (CD), digital video disk (DVD) ) Or any other type of memory. "Non-transitory" computer-readable media excludes wired, wireless, optical, or other communication links that convey temporary electrical or other signals. Non-transitory computer-readable media include media in which data can be permanently stored and media in which data can be stored and later overwritten, such as rewritable optical discs or erasable storage devices.

[0094] It would be advantageous to elaborate on the definitions of certain words and phrases used throughout this patent document. The terms “application program” and “program” refer to one or more computer programs, software components, instruction sets, procedures, functions, and functions that are suitable for implementation in suitable computer code (including source code, object code, or executable code). Object, category, instance, related data or part of it. The term "communication" and its derivatives encompass both direct and indirect communication. The term "include/comprise" and its derivatives mean including but not limited to. The term "or" is inclusive, which means and/or. The phrase "associated with" and its derivatives may mean including, included in, interconnected with, included, included in, connected to or connected to, connected to or Connect with, be able to communicate with, cooperate with, interweave, juxtapose, be adjacent to, bind to, or be bound to, have, have the nature of, and have relationship to or with), etc. The phrase "at least one of" when used with a list of items means that different combinations of one or more of the listed items may be used, and only one item in the list may be required. For example, "at least one of A, B, and C" includes any one of the following combinations: A; B; C; A and B; A and C; B and C; and A and B and C.

[0095] The description in this application should not be interpreted as implying that any specific element, step, or function is an important or key element that must be included in the scope of the claims. The scope of patented subject matter is limited only by the allowed claims. In addition, no claim refers to 35 U.SC § 112(f) with respect to any of the appended claims or claim elements, unless the exact word "member for ..." is used in a specific claim. Or "steps for..." followed by a word segmentation phrase that recognizes the function. Terms such as (but not limited to), "mechanism", module", "device", "unit", "component", "element", "component", "equipment", "machine", "system", "processing The use of “device” or “controller”) in the claims is understood and intended to mean known to those skilled in the relevant art, as further modified or enhanced by the features of the claims themselves, and is not intended to invoke 35 USC § 112(f).

[0096] Although the present disclosure has described certain embodiments and generally associated methods, those skilled in the art will appreciate variations and permutations of these embodiments and methods. Therefore, the above description of example embodiments does not limit or restrict the present disclosure. Other changes, substitutions, and alterations are also possible without departing from the spirit and scope of the present disclosure as defined by the following claims.