System for optimizing operation of industrial machines by modifying input of standard process parameters

Abstract

To manage the complexity that must be taken into account when setting up and running industrial machining operations, and parameters that have a large amount of influence.SOLUTION: The present invention relates to a method of modifying process parameters based on optimal operating performance criteria for a metalworking process. The method includes the steps of inputting standard process parameters for at least one product to be machined and generating operating data based on the standard process parameters. The operating data is compared to an optimal operating performance criterion and presented to a decision subject. The subject may be able to modify the process parameters to improve the operation of a metalworking process.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to methods, industrial machine systems, computer program products, and non-transitory computer readable media for varying process parameters based on optimal operational performance criteria for industrial machining operations, such as metal machining processes. [Background technology]

[0002] Today's industrial machine systems typically consist of machines with actuator systems to achieve relative motion between machine parts or operating devices and workpieces. State of the art industrial machine systems are highly specialized to perform operations such as beam cutting, milling, turning, drilling, boring, punching, punch press, press breaking, bending, welding, and assembly operations. Machine systems represent a significant investment for most potential customers, especially smaller or medium-sized shops, as the versatility and productivity that a machine system will contribute to a business are major factors in making an investment decision. Once the investment is made, ensuring that the machine system is used to its full potential is one of the main factors to increase productivity.

[0003] The industrial machine system is controlled by a CNC (Computerized Numerical Control) unit, an NC (Numerical Control) unit, a PLC (Programmable Logic Control) unit, and / or associated sensory processing devices that work together to provide instructions to the actuator system to perform the required movements to perform the intended industrial operation. The machine system further comprises a machine controller, which is essentially a computer having a processor and a conventional operation system, such as Windows or Linux, configured to control the CNC / NC / PLC unit based on machine controller instructions, such as G-code or XML. The machine controller includes or is connected to an HMI (Human Machine Interface) and is configured to read programs and collect machining parameters, such as cutting parameters. This allows the machine controller to issue complete instructions to the CNC / NC / PLC unit for execution by the actuator system included with the machine. Traditionally, both the CNC / NC / PLC unit and the machine controller are physically included in the industrial machine, which forms an independent, self-contained industrial machine system, with the machine controller forming an essential, physically connected part of the machine.

[0004] A CNC system may be defined as comprising a machine tool, referred to herein as a machine, a part program, which is a detailed set of commands that the machine follows, and a machine controller (or machine control unit), which is a computer that stores the program and executes the commands into actions by the machine tool.

[0005] The management, control and monitoring of operations performed by industrial machines requires expertise and experience from the machine operator as well as software-based support systems to be accomplished. For example, to generate a program for the operations of the manufacture of a particular metal product, the program needs to be based both on a set of predefined principles, such as the calculation of the sequence of operations based on optimization techniques or shortest path principles, and also on the operator's know-how about what is the best sequence from a more practical point of view. The variables to be considered and controlled may relate to material properties, logistics, and of course the actual geometry, shape, size and dimensions, as well as the sequence in which the products should be manufactured.

[0006] The manufacturing process according to the prior art is based on a fairly linear sequence, including steps of building and designing the product, followed by steps of purchasing the necessary manufacturing materials, reserving manufacturing capacity, and allocating resources. The product is then manufactured and delivered to inventory or to the consumer. Traditional manufacturing processes tend to be somewhat inflexible, and therefore do not utilize the manufacturing means to their full potential. Thus, the inability to synchronize steps in the process results in full efficiency and productivity not being achieved throughout the manufacturing process. One of the reasons for this is that data, such as dynamic manufacturing variables, that are required to further optimize the manufacturing process are stored in separate locations. The separate locations of the data prevent exchange and comparison of process parameters, and therefore maximum productivity for a given manufacturing process cannot be obtained with a given set of available manufacturing means.

[0007] As mentioned, industrial machining operations as well as the associated design and build processes (including parametric design options), material selection, purchasing, logistics, etc. are based on a large number of dynamic manufacturing variables and changing requirements, all of which affect the outcome of the industrial operation. Human operators are consequently faced with a great deal of complexity when attempting to optimize operations that involve a large number of variables. The operator may know what is actually required, but will need assistance in determining the most effective way to achieve the desired result, requiring assistance, or preferably automated services, that are currently not found anywhere. [Prior art documents] [Patent documents]

[0008] [Patent Document 1] US Patent Application Publication No. 2015 / 0205289 [Patent Document 2] US Patent Application Publication No. 2004 / 0267395 Summary of the Invention [Problem to be solved by the invention]

[0009] Thus, the relevant problem that must be considered when setting up and performing an industrial machining operation is to manage this complexity and the plethora of influencing parameters that, if not properly managed, may adversely affect the efficiency, accuracy, quality, and productivity of the industrial machining operation, whether or not the influencing parameters relate to logistics, material properties, manufacturing quality, currently used tooling, available tooling, or operator requirements. If properly managed, significant improvements in productivity and efficiency can be expected. [Means for solving the problem]

[0010] It is therefore an object of the present invention to alleviate the above-mentioned problems associated with the prior art by providing a method, industrial machine system, computer program product, and non-transitory computer readable medium for varying process parameters based on optimal operational performance criteria for a metalworking process, said method comprising: inputting standard process parameters for at least one product to be machined; generating operational data based on standard process parameters; selecting at least one optimization technique and defining a function, said function including standard process parameters; generating a function for optimization by using standard process parameters as a basis for defining ranges of performance variables and / or ranges of process parameters; applying an optimization technique to the function, whereby an optimal operational performance criterion is determined to obtain a set of commands used to control the metalworking process; comparing the generated operational data to an optimal operational performance standard; presenting the optimal operational performance criteria to a decision maker and enabling the decision maker to modify standard process parameters based on the presented optimal operational performance criteria for the metalworking process; Includes.

[0011] By standard process parameters is meant here variables that are inputs without prior optimization and without prior comparison of various information sources related to the metalworking process. The operational data are typically machine settings that are required to convert the raw material into the final product, applying to a predefined machining process and machine system. The optimization technique is any method that allows the process parameters to be either maximized or minimized depending on the environment. The application of the optimization technique can generate operational data within a predefined range that provides alternatives for carrying out the metalworking process. These alternatives cannot be realized unless some process parameters are taken into account, thus providing an opportunity to further improve productivity. The operational data may include at least one of the following performance variables, quality, delivery time, and total cost. The metalworking process may be any industrially applicable cutting technique based on laser, flame, plasma, water jet, ion, air, bending, pressing, punch press, press break, welding, milling, drilling, and turning.

[0012] As mentioned, the present invention allows decision-making entities, such as human operators or computerized means, to use data from various sources to increase efficiency and productivity. By using the present invention as a monitoring service configured to collect information from various sources, of which the machine may be one, all of the entered standard process parameters can be modified by using all available information. Examples of other sources of information may be elements that interface with the machine or machine controllers via Internet of Things (IoT) enabled elements, Enterprise Resource Planning (ERP), Manufacturing Execution Systems (MES), Customer Relationship Management Systems (CRM), Procurement Management Systems (SMS), Computer Aided Design / Manufacturing Systems (CAD / CAM) and associated databases.

[0013] According to an embodiment of the invention, all relevant information is made available via the industrial machine system and / or other sources. This allows a rapid iterative process to be used to optimize each step, either before or during the process, according to the actual settings and machine configuration. The optimization process can also be used for design, purchasing, ordering, and manufacturing planning. For example, the product design can be changed with the available tools, the materials can be changed according to the current stock, the delivery time can be changed with the machine availability, the product design can be changed to achieve a given quality. Depending on the situation, this quality can be lower or higher than originally expected, but always within specified limits.

[0014] Further examples of process parameters that can be varied using the means and methods according to the invention are as follows:

[0015] The manufacturing process can be changed from an integrated combination machine, such as punch / bending, to a combination of separate processes, such as laser cutting and press crushing, for example. This example would be a change aimed at reducing the manufacturing cost for the production of the same or nearly the same product.

[0016] Freeform beam cutting as individual units can be changed to freeform cutting as clusters with only one cut from the intermediate cutting beam. When cutting a part from sheet metal, the geometric segments of the part and / or the tangential segments of the part can be modified by swapping or changing their relative positions and / or shapes, preferably resulting in an improvement in the quality of the part.

[0017] Material thickness and material type and / or quality may be altered to reduce weight and cost per unit of product. Alternatively, product geometry may be altered to reduce material waste and thereby lower manufacturing costs. Material size, shape, form, and dimensions may be reduced for the same or similar reasons as above. Product geometry may include data on bending curves, elongation, strain, compensation factors, and tooling preferences.

[0018] Part and / or product geometries can be modified to minimize setup times and costs, which reduction is achieved by reducing or even eliminating the need for tooling changes. Material sizes, shapes, formats, and dimensions can also be modified so that less material is required in inventory.

[0019] Batch sizes can be adjusted to reduce costs, which may result in possible changes to machine configurations depending on the batch size. The actual machine configurations can also be changed to obtain various benefits and simplifications in the manufacturing process.

[0020] Process parameters for metalworking processes are typically predefined or predetermined parameters for the production of a particular product, such as production sequence, batch quantity, product geometry, and predefined tolerances, etc. They may be the required metalworking operations, the required tool configurations, the automation configurations for picking and / or picking up and placing and / or stacking the parts produced, the stacking pattern of the articles to be manufactured, and / or process parameter data from previous operations. Process parameters are not related to machining parameters, which are typically a different type of parameter used to control machining operations.

[0021] On the other hand, performance variables related to metalworking processes are typically variables such as determined tolerances of the article being manufactured, process time, tool availability, tool life, material removal rate, operator work environment, on-hand orders, delivery times, required pressure processing locations, etc., and / or performance variable data from previous operations. Performance variables are dynamic and can be adjusted within predetermined ranges to achieve predefined characteristics of the product.

[0022] The determined tolerances of a manufactured article (as opposed to predefined tolerances, see above) are parameters related to the quality of the product and include any of the performance variables of material properties such as stiffness, toughness, product geometry such as size and thickness, radius, angles, and dimensions, and manufacturing defects such as ridges, bend lines, pressure deformations, lead-in marks, micro-joint marks, and / or other visual attributes.

[0023] The modified data can be further used in different applications such as CAD, CAM, ERP, MES, CRM, procurement management, etc. The invention is also applicable in areas such as purchasing and optimizing machine performance criteria. These criteria can be defined as instructions or programs of instructions for controlling industrial machines such as CNC machine tools.

[0024] An example of traditional linear scheduling is the task of whether to make a first type of punch or a second type of punch. This is solved by a traditional scheduling or manufacturing execution system. Another example is a piece that needs to be punched out of the material before it can be bent, this decision can also be made in a linear flow management system. A third example is whether to use one or more cutting heads in a beam cutting operation, this is a linear decision based on the default number of cutting heads on the machine divided by the number of parts to be made. Again, this third task is solved by a traditional scheduling or manufacturing execution system. All of the above examples can of course also be solved by the present invention.

[0025] However, the present invention differs from traditional, linear scheduling systems. It allows information to be utilized from multiple sources to determine, for example, whether a given product should be manufactured by laser cutting and press breaking techniques instead of a combination of punching and bending techniques. This facilitates reducing manufacturing costs while allowing for improved product quality. This is made possible by the modification of standard process parameters based on proposing optimal operational performance criteria for the metalworking process. To obtain the optimal operational performance criteria, proposed orders to external partners may be prepared, including materials, tools, spare parts, maintenance, and / or logistics, as necessary. The optimal operational performance criteria may include at least one of the following: benchmark production cost, amount of waste, quality, and accuracy of delivery.

[0026] Various embodiments and examples of the present invention will now be described with reference to the accompanying drawings. [Brief description of the drawings]

[0027] [Figure 1] 1 is a flow chart illustrating optimization of an operational sequence of an industrial machine system or the like by inputting standard process parameters, followed by modifying and submitting optimal operational performance criteria. [Diagram 2] FIG. 1 diagrammatically illustrates an industrial machine system according to one embodiment. [Diagram 3] FIG. 2 illustrates another embodiment of an industrial machine system according to the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0028] Both the detailed description and the drawings to which it refers are given by way of example only. Like reference numbers in different drawings refer to like elements.

[0029] Figure 1 is a flow chart illustrating the optimization of operation sequences in an industrial machine system or manufacturing support system that is connected, or at least connectable, to multiple sources of information. The system can be configured to provide support for business operations related to the design and construction process (including parametric design options), material selection, purchasing, logistics, etc., by inputting standard process parameters and subsequently modifying and suggesting optimal performance criteria.

[0030] The sequence starts (S10) and an operator either manually or automatically inputs (S20) standard process parameters related to the product to be machined or evaluated. A product in this context refers either to a single item to be manufactured or to multiple components that can be assembled. The input of the standard process parameters can be done anywhere. An example is that an application (app) developed for a mobile terminal, such as a so-called smartphone, is used as a tool for the input of the standard process parameters. This app can then be made available to all stakeholders along the value chain during the manufacturing process, such as for example designers, purchasers, logistics experts, manufacturing specialists, etc. In a next step, the computing system according to the invention generates operational data based on the standard process parameters (S30).

[0031] After generating the operational data, the computing system, which is also connected or connectable to multiple information sources, selects (S40) at least one optimization technique that defines a function, the function including standard process parameters. This is followed by generating (S50) the function for optimization by using the standard process parameters as a basis for defining ranges of performance variables and / or ranges of process parameters. Information regarding the process parameters and performance variables may be retrievable through multiple integrated data sources.

[0032] The generated optimization function is applied (S60) to a function including the standard process parameters, thereby determining optimal operating performance criteria for the standard process parameters and performance variables to obtain a set of commands used to control the metalworking process. Information regarding the standard process parameters and performance variables may be available through multiple integrated sources of information.

[0033] Once the optimal operational performance criteria are determined, the operational data is compared with the optimal operational performance criteria (S70) and, if there is a difference and the optimal operational performance criteria provides a performance advantage to the operator, the result is presented to a decision-making entity (S80). This decision-making entity, whether a human operator or a computerized fully or semi-automated service layer, may be capable of modifying standard process parameters based on the presented optimal operational performance criteria for the metalworking process. The decision-making entity may also be realized in the form of an app for a smartphone, preferably the same or similar app as mentioned in connection with the step of inputting the standard process parameters.

[0034] When evaluating the difference between the standard process parameters and the optimal operating performance criteria (S90), if the decision-making entity makes a recommendation or decision to change (Yes), at least one process parameter included in the proposed operating sequence is changed (S95) and adopted and used as the modified operating data by the industrial machine system. If the decision-making system makes a recommendation or decision not to accept the proposal (No), the sequence will continue with the originally generated operating data applied (S100). Whatever the decision, the sequence will proceed to the start point (S10) or the end point (S110). The modified data can be further used in different applications such as CAD, CAM, ERP, MES, CRM, procurement management, etc. The present invention is also applicable in areas such as purchasing and optimization of machine performance criteria, where the criteria can be defined as instructions and / or programs of instructions for the control of industrial machines such as CNC machine tools.

[0035] Figure 2 diagrammatically illustrates a first embodiment of the invention. The system comprises a machine 1, which may be a machine for beam cutting (2D or 3D), punching, punch pressing, press breaking, bending, gluing, sewing, tape and fiber application, milling, drilling, turning, routing, picking and placing, as well as combinations of such machines. Beam cutting includes techniques such as laser, welding, friction stir welding, ultrasonic welding, flame and plasma cutting, pinning and sewing.

[0036] The machine comprises an actuator system 2 for performing industrial operations. The actuator system comprises at least one actuator, i.e. a motor for linear or rotary movements. Typically, the actuator system is configured to perform two- or three-dimensional movements of the working part of the machine and the workpiece relative to each other.

[0037] The actuator system is controlled by an actuator controller 3, in the form of a CNC / NC / PLC unit and / or associated sensing and processing devices. The actuator controller controls the actuators at a low level, i.e. by sending low level control commands for the operation of the actuator system. The actuator system is connected to the actuator controller via a machine internal communication network 4, which may for example comprise a communication bus.

[0038] The machine optionally includes other systems such as a sensor system 10 for sensing various process parameters of the machine, and other controllers 11 for processors, networks, communication links, or other computing devices to transmit data and make decisions. These systems may also be connected to a machine common internal communication network 4 and to a computing system in communication with the machine, such that a machine controller 9 is connected to the sensor system for receiving the sensor data. The machine controller may be further configured to remotely control an actuator system of the machine in response to the sensor data.

[0039] Alternatively, the CNC / NC / PLC unit and / or associated sensing and processing equipment and / or the mentioned machine controller can be physically attached to or otherwise connected to the industrial machine, which in this case forms an independent self-contained industrial machine system, with the machine controller forming an essential and physically connected part of the machine. Both of the two alternative embodiments of the industrial machine system have their respective advantages and for the purposes of the present invention, both integrated or separate configurations of sensor system and actuator controller are equally applicable.

[0040] The machine, when configured according to the remote alternative, may also comprise a communication client 5 connected to the actuator controller 3 for establishing communication with a computing system 6 connected to the machine. The communication client is in this case a functional unit enabling the machine or any subcomponent of the machine to communicate with the machine controller. The computing system connecting to the machine may be a cloud-based computing system connected to the Internet. A centrally located computer connecting or connectable to multiple data sources is an alternative embodiment. The communication client 5 and the computing system connecting to the machine may be configured to establish a secure communication 7 with each other over the Internet, for example by initiating an encrypted communication by HTTPS / TSL or by establishing a VPN (Virtual Private Network). Alternatively, the communication may be established via a firewall or proxy server 8. As a further alternative, any subcomponent of the machine, such as the actuator controller 3, may be configured to connect itself to the computing system 6 or to the above-mentioned central computer having access to multiple data sources, although, as mentioned, both remote and integrated configurations are equally applicable for this purpose.

[0041] The above-mentioned computing system 6 in communication with the machine includes a machine controller, which may be remotely connected to the machine, and which may be configured to remotely control the actuator system of the machine via the actuator controller by modifying operating parameters of the actuator controller.

[0042] The machine controller 9 is hosted in a virtual machine in the remote computing system 6. In that manner, the resources of the machine controller can be utilized in an efficient manner. The machine controller can, for example, be configured to read and execute machine program code, control machine parameters, allow machine parameters to be manually controlled or adjusted, and act as an interface with related systems. The machine controller is connected to an HMI (Human Machine Interface) unit 12, which can be remotely connected to the machine controller via an Internet connection 13, or in another embodiment, is integrated with the machine. In either manner, a machine operator can manage and control the operation of the machine from a remote location, for example connected to the Internet. The HMI unit 12 and / or the remote computing system 6 can be configured to request user identification of the operator, for example by requesting a password or other means of identification.

[0043] One embodiment of the present invention is illustrated in FIG. 2. Locally on the machine 1, an actuator system 2 is included, which comprises actuators for performing machining operations. An actuator controller 3 is part of or connected to the actuator system 2. The actuator controller is configured to receive instructions from a remote machine controller and execute the instructions block by block in a closed loop system. Thus, each task performed by the actuator is monitored and after the sub-operation is finished, the actuator will perform the next sub-operation until the entire operation is finished. This means that the operation of the actuators of the machine is controlled at a low level by the actuator controller. The actuator controller typically includes a memory and a processor to store and execute instructions and log data. The actuator system does not include a conventional machine controller or an HMI. The actuator system of the machine is therefore dependent on receiving instructions from the remote machine controller. Once the complete set of work instructions or a defined subset thereof is received and verified, it can be executed without further instructions from the machine controller. The subset of work instructions may be a part of a complete machine operation, but at least includes enough information for the actuator system to perform at least a part of the operation. The operations are preferably performed step by step in a closed loop system within the machine requiring minimal manual effort from the operator. The machine has only simple functions such as an emergency stop button and an on / off button. Otherwise, the machine relies on commands from a remote machine controller to operate.

[0044] The machine controller is typically located physically separate from the machine, in the cloud. Monitoring the ongoing process, loading instructions, modifying instructions, and creating new instructions can only be done at the remote machine controller. Thus, the machine controller of the present invention corresponds to a conventional machine controller, only it is not a physical part of the machine, but is remotely connected to the machine. Instructions monitored and controlled by the machine controller and the interconnected HMI include operating parameters such as cutting speed, cutting depth, pressure, etc.

[0045] The machine controller is not part of the closed loop system of the actuator controller. Therefore, unless a new command is sent from the machine controller, the actuator system of the machine will complete the received motion command in its entirety without waiting for further commands, unless a specific command to end or change the motion is received from the machine controller. Typically, commands are provided only for a complete motion, so that new commands are only valuable for the following motion, not the motion in progress. This can be set as a safeguard, but it is up to the operator to decide what type of operational security should be implemented.

[0046] The machine controller is configured to send instructions one at a time, or several batches of instructions. Any conventional manner of sending information may be utilized. The machine controller is further configured to receive the information and make decisions based on said information. For example, the machine controller may act on feedback data to make decisions and / or send new instructions based on said feedback.

[0047] The system of the invention offers the possibility of remote control of industrial machines without the risk of commands being dropped as a result of poor communication, e.g. due to latency in an Internet connection. This is confirmed, for example, because the movements are received in full and acknowledged by the actuator controller. Thus, communication failures can be quickly discovered and movement commands repeated, if necessary.

[0048] To facilitate monitoring, the machine is equipped with a monitoring unit 14, such as a camera, video camera, or other image capture means, for monitoring the operation of the machine. The monitoring unit is connected to a remote computing system 6 via a communications client 5 and is configured to provide operational information to the remote computing system. The operational information is processed and transmitted to the HMI 12.

[0049] The machine controller is arranged to receive the machine program from a CAD / CAM system or by manual input from an operator, for example via the HMI unit 12 .

[0050] According to one embodiment, the remote computing system is configured to monitor operational parameters of the machine and disable remote control of the machine's actuator systems by the machine controller when the operational parameters exceed a threshold. Such operational parameters may be the number of operating hours, number of operating cycles performed by the machine, etc. Thus, by restricting access to the machine controller, the operating costs and usage of the machine can be controlled and limited.

[0051] The remote computing system is configured to collect machine and / or manufacturing data and forward the data to another system (not shown) for data analysis and / or optimization. The machine data can be used, for example, to optimize supply chains (purchasing, manufacturing, distribution), demand chains (marketing, sales, service), machine maintenance, or other big data applications.

[0052] The monitoring unit can also be configured to monitor the manufactured articles and their various characteristics, including their tolerances. Computer vision is another term used in the industry for such identification of geometry-related characteristics. Tolerance refers to material properties such as stiffness, toughness, product geometry such as size, shape, radius, angle, and dimensions, and manufacturing defects such as ridges, bend lines, pressure deformations, and / or other visual attributes. The monitoring unit can be further configured to connect to a computing system 6 that is connected to the machine via a communication client 5 to provide operational information to the computing system.

[0053] In one embodiment, a computing system in communication with the machine is configured to monitor an operational parameter of the machine and disable remote control of the actuator system of the machine by the machine controller when the operational parameter exceeds a threshold. Such operational parameters may be the number of operational hours, number of operational cycles performed by the machine, etc.

[0054] The computing system is configured to collect machine and / or manufacturing data and transfer the data to another system for data analysis and / or optimization. This system may be any kind of manufacturing execution system (MES) enterprise resource planning (ERP). The machine data can be used to optimize, for example, the supply chain, i.e., purchasing, manufacturing, and distribution; the demand chain, i.e., marketing, sales, and service; and the maintenance of the machine or its integral or separate parts. The machine data can also be made available to other systems, such as big data applications designed to merge the data to derive results based on a large amount of information, which reduces the possibility of deriving inaccurate results.

[0055] Fig. 3 represents an alternative embodiment of an industrial machine system according to the invention. The industrial machine system differs from the one described in relation to Fig. 1 in that the machine does not comprise an actuator controller. The actuator controller 3' is physically separated from the machine and is comprised in a computing system 6 in connection with the machine. The computing system is connected to the machine via one or more data lines 7, which may be encrypted, for example via the Internet. The machine 1 comprises at least one communication client 15 for establishing communication between the machine and the computing system 6 in connection with the machine. This communication client 15 is connected to the actuator system 2 of the machine and is therefore called an actuator client. The client is configured to send and receive low-level communications from the actuator controller to the actuator system. Similarly, the machine may optionally comprise a sensor communication client 16 for communicating any sensor data from the sensor system 10, and any further controller client 17 for communicating with other controllers 11 in the machine. Similar to what is shown in relation to Fig. 2, the communication between the machine and the computing system in connection with the machine may be established via a firewall or a proxy server.

[0056] In the following, examples of the present invention will follow, intended to further clarify the functionality and principles of operation. As explained in connection with the background of the present invention, traditional processes of manufacturing planning are sequential in nature. This means that information that controls the manufacturing process is collected from a local database, and manufacturing planning is done in response to instructions emerging from the locally stored information. Examples of this include: (1) taking an order; (2) selecting or creating at least one control algorithm; (3) making a portion of raw material of a given quality; and (4) forming a given component by bending, milling, turning, etc.; and (5) delivering the component to a customer according to the order specifications. This process is sequential in nature, and data that controls the process is collected locally.

[0057] The invention utilizes various sources to collect information, such as batches of orders including geometric drawings, batches of materials, batches of existing configurations of tools and machines, etc., via the mentioned central computer, as previously described. Information related to the manufacturing process according to this specification typically comes from different sources, e.g., ERP / MES, machines, IoT-enabled units, CAD / CAM, and one or more monitoring units. Information is collected by a central computer configured as an intermediate means and located between various endpoints. The endpoints are typically information sources that may or may not affect the manufacturing process, e.g., ERP / MES, machines, IoT information, CAD / CAM, and monitoring units as previously mentioned. Information on process parameters and performance variables may be retrievable through multiple integrated information sources.

[0058] The central computer can be either a general-purpose computer or a computer configured to function as a machine controller. The central computer will always be connected or can be connected to at least two endpoints with data to obtain the information to be optimized. It is believed to be the minimum requirement to perform and fully accomplish a non-sequential optimization process for multiple variables. Several methods of optimization can be used, based on combinatorial theory, dynamic variation, multivariate analysis, etc. Any of the methods allow for non-sequential, non-linear optimization and are suitable for use with complex systems with many dynamic variables.

[0059] The present invention utilizes non-sequential optimization, which is a numerical process or method that is not sequential or linear compared to traditional processes. Some of the steps in the manufacturing process may undergo optimization. One example is the geometry of the part to be manufactured, which may be altered to reduce tool changes. Another example is scheduling machining operations, which may be altered to reduce setup times, provided that information is retrieved, for example, from the machine, the monitoring unit, and / or from an IoT-enabled unit. A third and fourth example is scheduling machining operations, which may be adjusted to reduce material changes, provided that information is collected from at least two end points, information that can be retrieved and reused from previous process steps, for example, changing visual attributes or tool combinations via the monitoring unit or rotating the part on its surface. Other possible examples include reconfiguring machine tools, such as backgauge positioning, pressure, pressure location, etc., or ordering of tools, materials, maintenance, spare parts to reduce manufacturing disruptions.

[0060] One of the prerequisites for this type of optimization is to allow the retrieval of data from multiple sources, for example ERP / MES, machines and their configurations, IoT information, CAD / CAM, machine monitoring units, etc. The information is then retrieved and made available to a central computer in order to allow the optimization of several separate process steps related to their current situation, including dynamic influences that are not controllable since they may depend on the unreachable environment, such as updates in the management system.

[0061] The invention can also introduce so-called refurbishability and customizability control in various endpoints containing information, such as ERP / MES, machines and their configuration, IoT, CAD / CAM (both for design and configuration), and at least one monitoring unit. For example, the invention allows changing material specifications as a means to potentially reduce material and tool changes, required tolerance intervals and associated strength and solidity ranges. According to another embodiment of the invention, it is also possible to change the geometry / shape of the product to minimize tool changes, but still maintain the tolerances that have visual marks from the drawing, or alternatively on its coordinates, which may be backgauges positioned to avoid them completely. It can also allow jobs to be scheduled to reduce material / tool ​​changes while still respecting delivery times. This allows communication with customers to potentially allow delivery times to become a variable that affects the price of manufactured goods. To realize those options and new opportunities, two or more endpoints must be able to control in a non-sequential manner, for example via machine tools, via IoT information and databases in the ERP / MES, to schedule orders, tools, material changes, and change product geometries. For example, modifications to the geometry that can result in a reduction or minimization of tool changes can be checked against any form of tolerance interval in a drawing that may be available in the ERP / MES or even available to the customer or designer as a variable that affects the ratio between manufacturing cost and market price.

[0062] As has become clear based on the above, the present invention is distinguished from conventional process planning systems (MES) that implement manufacturing scheduling systems that are configured to retrieve information from local databases. These systems may even rely on operators keying in data on orders and deliveries followed by sequential schedules. The present invention is based on an entirely different level of optimization based on actual, even real-time data, which is retrieved by a central computer, which in some cases may also share the information. According to the present invention, the central computer is connected, connectable or integrated with multiple end points or any other possible information sources, such as ERP, MES, CAD, CAM, machines, IoT connections, at least one customer and / or at least one provider, at least one CRM management system, and / or monitoring units, etc. In addition, the central computer may be connected to other providers of information related to multiple variables that affect the production, such as materials, tools, spare parts, maintenance, designs, part specifications or customers, constructions, and / or products. Information on process parameters and performance variables may be retrievable through multiple integrated data sources, typically the sources mentioned above. Different numbers of connected, connectable, or integrated endpoints provide different optimization advantages and different costs and / or complexities of the integrated system.

[0063] In one embodiment, the data can be retrieved from two end points. In one example, the data can be retrieved from two end points, such as an ERP system and a machine. The advantage of having the data retrieved from two end points, such as an ERP system and a machine, is that the product geometry can be modified to meet desired tolerances while still using the current machine settings.

[0064] In one embodiment, the data is available from three endpoints. In one example, the data is available from three endpoints, such as the MES, the machine, and the IoT. An added advantage when the data is available from three endpoints, such as the MES, the machine, and the IoT, is that it is possible to control the accessibility of additional tools through the IoT and to configure the machine with a complete tooling configuration consisting of a combination of current and accessible tools. Additionally, the product geometry can be altered to meet desired tolerances while still using some of the current machine settings.

[0065] In one embodiment, the data is available from four endpoints. In one example, the data is available from four endpoints, such as MES, machine, IoT, and customer. An additional benefit when the data is available from four endpoints, such as MES, machine, IoT, and customer, is that the customer can be integrated to accommodate the change in product geometry. Furthermore, the product geometry can be changed to meet desired tolerances while still using some of the current machine settings. It is also possible to control the accessibility of additional tools through IoT and to configure the machine with a complete tooling configuration consisting of a combination of current and accessible tools.

[0066] In one embodiment, the data is available from five endpoints. In one example, the data is available from five endpoints, such as MES, machine, IoT, customer, and designer. An additional benefit when the data is available from five endpoints, such as MES, machine, IoT, customer, and designer, is that it is possible to integrate both the customer and the designer to accommodate the change in the product geometry. Furthermore, the product geometry can be changed to meet the desired tolerances while still using some of the current machine settings. It is also possible to control the accessibility of additional tools through the IoT and to configure the machine with a complete tooling configuration consisting of a combination of current and accessible tools.

[0067] In one embodiment, data is available from more than five endpoints. In one example, data is available from six endpoints, such as MES, machine, IoT, customer, designer, and sheet material provider. An additional advantage when data is available from six endpoints, such as MES, machine, IoT, customer, designer, and sheet material provider, is that it is possible to integrate sheet material providers to resize sheet material to fit multiple of the modified product geometries, provide the modified sheet material, and manufacture the modified product geometries from the modified sheet material. Furthermore, product geometries can be changed to meet desired tolerances while still using some of the current machine settings. Still further, it is possible to control the accessibility of additional tools through IoT and configure machines with a complete tooling configuration consisting of a combination of current and accessible tools. Furthermore, it is possible to integrate customers and designers to accommodate the changes in product geometries.

[0068] An alternative definition of a central computer is when different endpoints such as ERP, MES, CAD, CAM, machines, IoT, customers, providers, information sources, at least one CRM management system, and / or monitoring units are integrated with each other to exchange data and make decisions. [Explanation of symbols]

[0069] 1 machine 2 Actuator System 3 Actuator Controller 3' Actuator Controller 4. Machine internal communication network 5 Communication Client 6. Computing Systems 7. Communications 8 Firewall / Proxy Connections 9 Machine Controller 10 Sensor System 11 Other Controllers 12 HMI (Human Machine Interface) Unit 13. Internet Connection 14. Surveillance Unit 15 Actuator client, communication client 16 Sensor client, sensor communication client 17 Controller Client

Claims

1. 1. A method for varying process parameters based on optimum operational performance criteria for a metalworking process, comprising: inputting, by an operator, desired process parameters for at least one product to be machined into a computing system; generating, by the computing system, operational data based on the desired process parameters; selecting, by the computing system, at least one optimization technique and defining a function, the function including the desired process parameters; generating, by said computing system, a function for optimization by using said desired process parameters as a basis for defining ranges of performance variables and / or ranges of process parameters; applying, by the computing system, the generated optimization function to the function including desired process parameters, whereby an optimal operating performance criterion is determined for obtaining a set of commands used to control the metalworking process; comparing, by the computing system, the generated operational data to the optimal operational performance criteria; if the comparison indicates a difference and the optimal performance criterion provides a performance advantage to an operator, presenting, by the computing system, the optimal performance criterion to a decision entity and enabling the decision entity to modify the desired process parameters based on the presented optimal performance criterion for the metalworking process; A method for varying process parameters based on optimum operational performance criteria for a metalworking process, comprising:

2. 10. The method for modifying process parameters based on optimal operational performance criteria for a metalworking process as recited in claim 1, wherein proposed orders to external partners are prepared including materials, tools, spare parts, maintenance, and / or logistics as needed to obtain optimal operational performance criteria.

3. 2. The method for altering process parameters based on optimal operational performance criteria for a metalworking process as recited in claim 1, wherein the operational data includes at least one of performance variables, quality of product manufactured, delivery time, and total cost.

4. 2. The method for varying process parameters based on optimal operational performance criteria for a metalworking process as recited in claim 1, wherein the optimal operational performance criteria includes at least one of: baseline production cost, amount of material removed, quality of product produced, and accuracy of delivery.

5. 2. The method for varying process parameters based on optimum operational performance criteria for a metalworking process according to claim 1, wherein the metalworking process is any industrially applicable cutting technique based on laser, flame, plasma, water jet, ion, air, bending, pressing, punch press, press break, welding, milling, drilling, and turning.

6. 2. The method for varying process parameters based on optimum operational performance criteria for a metalworking process as recited in claim 1, wherein said metalworking process relates to sheet metal working.

7. 10. The method for varying process parameters based on optimum operational performance criteria for a metalworking process of claim 1, wherein said process parameters and performance variables are dynamically monitored and controlled, preferably in real time.

8. Retrieving process parameters from different sources related to said metal machining process, such as production sequence, batch volume, product geometry and predefined tolerances, required metal machining operations, required tool configurations, stacking patterns of the articles to be manufactured, and / or process parameter data from previous operations; Retrieving performance variables from different sources related to said metal machining process, such as determined tolerances of the article being manufactured, process time, tool availability, tool life, material removal rate, operator work environment, on-hand orders, delivery times, required pressure processing locations, and / or performance variable data from previous operations; storing said process parameters and performance variables in an integrated memory associated with a computer system, such as an enterprise resource planning (ERP) system or a manufacturing execution system (MES) system; making said process parameters and / or performance variables available to a machine controller or computing system for applying optimization techniques to select an optimal operational performance criterion; 10. The method of claim 1 for varying process parameters based on optimum operational performance criteria for a metalworking process, further comprising:

9. 2. The method for varying process parameters based on optimal operational performance criteria for a metalworking process as claimed in claim 1, wherein the tools and / or the articles being manufactured and / or sources along the production line and / or sources in the logistics are equipped with electronic circuitry, software, sensors and / or network connectivity enabling these objects to exchange data such as process parameters and / or performance variables with a computer system.

10. The desired process parameters are predefined and / or defined tolerances of an article to be manufactured, and the predefined and / or defined tolerances are: Material properties such as stiffness, toughness, size, format, and thickness; Product geometry, such as radii, angles, and dimensions; Manufacturing defects such as ridges, bend lines, pressure deformations and other visual attributes 2. The method for varying process parameters based on optimum operating performance criteria for a metalworking process of claim 1, wherein the performance variables include any of the following:

11. 2. The method for varying process parameters based on optimal operational performance criteria for a metalworking process of claim 1, wherein the desired process parameters are product geometry, the product geometry including data on bending curves, elongation, strain, compensation factors, and tooling preferences.

12. 10. The method for varying process parameters based on optimal operational performance criteria for a metalworking process of claim 8, wherein process parameters include the tool configuration as well as other enabling requirements such as spare parts, tooling, maintenance, materials, geometry, and / or dimensions.

13. 13. A method for varying process parameters based on optimum operational performance criteria for a metalworking process according to any one of claims 1 to 12 adapted for use in a Computer Numerical Control (CNC / NC) or Programmable Logic Controller (PLC) system.

14. A machine (1) comprising an actuator system (2) for performing an industrial operation, a computing system (6) in communication with the machine and comprising a machine controller (9); Equipped with An industrial machine system, wherein the machine controller is adapted to carry out a method according to any one of claims 1 to 13.

15. 15. The industrial machine system of claim 14, wherein the computing system (6) is configured to collect machine and / or manufacturing data, use the machine and / or manufacturing data for data analysis and / or optimization, and / or transfer the machine and / or manufacturing data to another system for data analysis and / or optimization.

16. A computer program product comprising computer program code which, when executed, enables a processor in a computer to perform the method of any one of claims 1 to 13.

17. One or more non-transitory computer-readable media comprising data representing a set of coded instructions configured to be executed by a processor in a computer, the instructions comprising the method of any one of claims 1 to 13.

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