27 results about "Distributed manufacturing" patented technology

An information technology system for a distributed manufacturing network includes an additive manufacturing platform configured to manage workflows for a set of distributed manufacturing network entities associated with the distributed manufacturing network. The information technology system includes a set of digital twins generated by the additive manufacturing platform. The information technology system includes an artificial intelligence system configured to be executed by a data processing system in communication with the additive manufacturing platform. The artificial intelligence system is trained to generate process parameters for the workflows managed by the additive manufacturing platform using data collected from the set of distributed manufacturing network entities. The information technology system includes a control system configured to adjust the process parameters during an additive manufacturing process performed by at least one of the set of distributed manufacturing network entities.

The invention relates to the technical field of manufacturing data acquisition, and discloses a distributed manufacturing data acquisition system based on NB-IoT. The system comprises a heterogeneous node sensing layer, a narrowband signaling scheduling layer, an edge fusion processing layer, a cloud collaborative decision-making layer and a closed-loop optimization feedback layer. The heterogeneous node sensing layer obtains multi-source data through a sensor array, generates an equipment operation state thermodynamic diagram and divides region priorities; the narrowband signaling scheduling layer deploys NB-IoT nodes, transmits time division multiplexing signaling and generates a node load distribution diagram; the edge fusion processing layer synchronizes the clock, fuses the multi-source data and the load distribution map, and generates fusion confidence; the cloud collaborative decision-making layer converts the fusion confidence into an executable instruction and issues the executable instruction; and the closed-loop optimization feedback layer monitors the load change of the system, generates an optimization index and dynamically optimizes an acquisition strategy. The system can penetrate through network congestion, improves the real-time performance and accuracy of data acquisition, dynamically adapts to the change of a manufacturing environment, and is suitable for a distributed manufacturing scene.

The invention relates to the technical field of intelligent optimization of discrete combination problems, in particular to a distributed heterogeneous machining workshop order allocation method and system based on simulation, workshops are accurately described by constructing simulation models of the machining workshops, and a hybrid genetic algorithm is combined with simulation to find order allocation schemes meeting requirements, so that the optimization of the machining workshops is realized. According to the method, a factory delivery date relaxation calculation mode is improved, maximization and minimum factory delivery date relaxation are taken as a target, a high-quality order allocation scheme is efficiently generated, whether each order can be completed in time or not is verified through production simulation of each machining workshop, an order transfer operation is designed to adjust overdue order allocation, and the order allocation efficiency is improved. Compared with a traditional method, the efficiency of processing heterogeneous workshops is higher, order allocation of simulation verification is more real and reliable, the resource utilization rate and the on-time completion rate can be improved in a complex distributed manufacturing scene, the order delay risk is reduced, and the method is suitable for the field of multi-factory collaborative production scheduling.

The invention relates to a distributed manufacturing multi-production task-oriented resource configuration method, a service platform and a medium. The method comprises the following steps: determining the task completion degree of a manufacturing task associated with each manufacturing unit when an interrupt instruction is received; according to the task completion degree, current manufacturing tasks are determined from all the manufacturing tasks corresponding to the manufacturing configuration information, an alternative manufacturing unit associated with each current manufacturing task is determined, and the alternative manufacturing units are associated with at least one manufacturing device; performing hybrid coding based on the current manufacturing task, the task completion degree and the manufacturing equipment to generate a plurality of hybrid coding bodies; after the fitness of the hybrid coding bodies is determined according to a preset fitness function, performing corresponding genetic evolution operation iteration and simulated annealing search iteration by utilizing a genetic simulated annealing algorithm based on the plurality of hybrid coding bodies and the corresponding fitness until the iteration is performed for a preset number of times; and selecting a target hybrid coding body from the plurality of generated candidate hybrid coding bodies to obtain a resource configuration result.

The invention discloses an outsourcing production and logistics combined scheduling method for an overseas manufacturing base. The method comprises the following steps: S1) acquiring data of a customer order, an outsourcing factory, an overseas manufacturing base workshop and a delivery ship; s2) establishing constraint conditions according to the factory, workshop and marine transportation data, wherein the constraint conditions comprise a processing workshop constraint, a parallel machine constraint and a task order time window constraint; s3) an outsourcing production and logistics combined scheduling model of the overseas manufacturing base is established according to the constraint conditions, and the target of the combined scheduling model is to minimize the maximum processing completion time and the total cost; and S4) designing a two-stage joint optimization strategy to combine with an improved decomposition multi-objective optimization algorithm of reinforcement learning to solve the production and logistics joint scheduling model in the distributed manufacturing environment, and obtaining an optimal scheme of production distribution scheduling. According to the constraint condition of the actual production workshop, the optimal joint scheduling scheme is solved, and the overall cost of the supply chain can be reduced.

The invention relates to the technical field of distributed manufacturing resource intelligent scheduling, in particular to a distributed manufacturing resource intelligent scheduling method and system, and the method comprises the following steps: obtaining equipment operation state data and workpiece quality data; based on the equipment operation state data and the workpiece quality data, evaluating the equipment performance degradation degree; correcting equipment capability parameters in the scheduling system according to the equipment performance degradation degree; before task allocation, task risk assessment information is generated based on the equipment performance degradation degree and task requirements; and according to the task risk assessment information, assisting a dispatcher to make a task allocation decision. The intelligent level of the scheduling system and the accuracy of decision making can be improved.

The invention discloses a production and logistics integrated decision-making method for improving distributed manufacturing efficiency. The method comprises the following steps: S1, obtaining process information of a workpiece to be processed, processing workshops specified by the process, processing machines of the process, corresponding processing time, the number of logistics vehicles, the maximum cargo capacity of each logistics vehicle and logistics time between the workshops; s2, the production and logistics integrated decision model of the distributed manufacturing system is utilized, decision variable values of the production and logistics process are obtained through an improved teaching optimization algorithm, and the decision variable values comprise the machining sequence of all procedures on a machine and the goods taking and delivering sequence of all workpieces. According to the method, production and logistics completion time is taken as an optimization target, a multi-load logistics vehicle is taken as a logistics tool, a processing sequence and a logistics task execution sequence are optimized in a collaborative manner, and an improved teaching optimization algorithm is designed, so that the solvability of the model is ensured, and the distributed manufacturing efficiency is effectively improved.

The present subject matter relates to a method comprising: receiving, at a messaging middleware (325), a data access request in a first format from a first application (321) of a public network (237B); processing the data access request by the messaging middleware (325), the processing including converting a first format of the data access request to a second format of a second application (306) of a particular enterprise network (237A); and sending the data access request in the second format to the second application (306); processing, by the second application (306), the data access request, thereby generating data; the generated data is sent by the second application (306) to the first application (321) through the messaging middleware (325).

The present invention discloses a task set allocation method for collaborative optimization of production and transportation based on cloud manufacturing, which relates to the field of cloud manufacturing production technology. The method includes encoding the allocation of manufacturing service providers of all task sets using a one-dimensional positive integer vector method and randomly generating an initial solution. The present invention realizes efficient modeling of the allocation relationship of task set groups on distributed manufacturing service providers by adopting a one-dimensional positive integer vector encoding method. The method combines the optimal sorting method for minimizing the completion time of a single MSP to simultaneously determine the optimal processing sequence of the workpiece group and the processing sequence of the workpieces within the group. The closed-form expression of the completion time of each machine is obtained based on mathematical derivation, thereby effectively evaluating the performance of the overall scheduling scheme. The method forms a multi-level and multi-angle search collaborative mechanism by introducing a contrast perturbation mechanism, a multi-neighborhood search structure and an iterative greedy strategy, which significantly enhances the diversity retention and deep search capabilities of the algorithm in the solution space.

A method for reducing carbon dioxide emissions using trusted on-demand distributed manufacturing includes, through operation of a processor in a system, automatically calculating carbon dioxide reduction (carbon offset) of a manufactured product, storing the calculated carbon dioxide reduction, automatically transmitting the calculated carbon dioxide reduction to a certification body, and receiving carbon offset credit issued by the certification body.

The invention relates to the technical field of production scheduling, in particular to an optimal scheduling method for distributed production and manufacturing of notebook parts. The method comprises the following steps: obtaining notebook product structure data and production equipment data; setting electronic component surface mounting parameters according to the notebook product structure data; performing surface mounting simulation according to the production equipment data and the surface mounting parameters of the electronic component to obtain surface mounting data; component missing solder detection is carried out based on the surface mounting data, and component missing solder data are obtained; determining the soldering amount of soldering paste according to the missing soldering data of the component; evaluating the wear degree of the scraper based on the welding amount of the soldering paste; and surface mounting precision parameter adjustment is performed on the surface mounting data according to the abrasion degree of the scraper, and surface mounting adjustment parameters are obtained. According to the invention, real-time monitoring and optimization adjustment in the notebook computer production process are realized based on the production scheduling technology, so that the production efficiency and the qualified rate of the product quality are improved.

Disclosed herein is a method for redundant transmission in a distributed manufacturing automation system. The method includes: sending by an automation apparatus of the system a data item to a receiver through a first cellular network using a first sub-band of an industry frequency band, the first cellular network including a first base station and a first core network device; and sending by the automation apparatus the data item to the receiver through a second cellular network using a second sub-band of the industry frequency band, the second cellular network including a second base station and a second core network device.

The application discloses a kind of manufacturing collaborative systems based on cloud edge architecture, it is related to the field of intelligent manufacturing.It includes cloud layer for global planning and analysis, production edge layer for real-time scheduling and execution, and basic equipment layer.Edge layer is deployed with multiple edge execution MES and internet-of-things interface gateway, rule engine and event listening mechanism are built-in edge execution MES, support event triggering, condition judgment and timing scheduling, and can run autonomously when disconnected, guarantee production continuity;Internet-of-things interface gateway is used to uniformly access devices of multiple industrial communication protocols, through protocol adaptation and device abstraction, realize standardized access to heterogeneous devices, reduce system integration complexity;Multiple edge execution MES realizes event-driven collaborative work through standardized interface and asynchronous message mechanism. The present application can realize the efficient cooperation of cloud centralized decision and edge autonomous execution, and further improve the real-time performance, reliability and scalability of distributed manufacturing system.

The present application relates to the technical field of distributed manufacturing resource intelligent scheduling, and particularly relates to a distributed manufacturing resource intelligent scheduling method and system, the method comprising the following steps: obtaining equipment operation state data and workpiece quality data; based on the equipment operation state data and the workpiece quality data, evaluating the equipment performance degradation degree; according to the equipment performance degradation degree, correcting the equipment capability parameters in the scheduling system; before task allocation, based on the equipment performance degradation degree and the task requirements, generating task risk assessment information; according to the task risk assessment information, assisting the dispatcher to make task allocation decisions. The above can improve the intelligent level of the scheduling system and the accuracy of the decisions.

The present subject matter relates to a method comprising creating, in a distributed manufacturing automation system (100, 200), overlay networks (300, 400, 500, 600) having nodes, where each of the overlay networks (300, 400, 500, 600) spans one or more levels (101, 113, 115, 117) of an automation pyramid, where the nodes represent system resources of a network (130, 133, 135, 137) of the system (100, 200). An application may be created for performing a manufacturing task. Applications may be partitioned into application components according to predefined functionality and information streams, where the application components belong to one or more levels (101, 113, 115, 117) of the automation pyramid. One or more overlay networks (300, 400, 500, 600) that enable execution of the application components may be selected. A connection to the selected overlay network (300, 400, 500, 600) may be established. The application components may be deployed in the selected overlay networks (300, 400, 500, 600) using the established connections. The application may be used to plan and / or control manufacturing in the distributed manufacturing automation system (100, 200).

The present subject matter relates to a method comprising creating in a distributed manufacturing automation system (100, 200) overlay networks (300, 400, 500, 600) of nodes, wherein each overlay network of the overlay networks (300, 400, 500, 600) spans one or more levels (101, 113, 115, 117) of an automation pyramid, wherein the nodes represent system resources of networks (130, 133, 135, 137) of the system (100, 200). An application for performing a manufacturing task may be created. The application may be divided into application components according to the predefined functions and information flow, wherein the application components belong to one or more levels (101, 113, 115, 117) of the automation pyramid. One or more overlay networks (300, 400, 500, 600) that enable execution of the application components may be selected. Connections to the selected overlay networks (300, 400, 500, 600) may be established. The application components may be deployed in the selected overlay networks (300, 400, 500, 600) using the established connections. The application may be used for planning and / or controlling the manufacturing in the distributed manufacturing automation system (100, 200).

A system (100) for enabling trusted on-demand distributed manufacturing includes a first interface (120) configured to receive product data from a product data source (110-A, 110-B, 110-N), a second interface (130) configured to exchange manufacturing data from a manufacturing data source (140-A, 140-B, 140-N), a trust anchor module (170) configured via computer executable instructions to add a physically unclonable function (PUF) to a product, generate a non-fungible token (NFT) to represent the product on an NFT platform (172), a matching module (174) configured via computer executable instructions to match the product characteristics with requirements of a buyer and manufacturing capabilities of a producer, and a traceability module (176) to verify success of a manufacturing process.

The invention relates to the technical field of computers, and discloses a socialized productivity scheduling method and system based on real-time inventory matching priority, and the system comprises a user terminal which is used for receiving an order request and displaying a scheduling result; the intelligent scheduling server is in communication connection with the user terminal and is used for processing the order request and executing a scheduling algorithm; the database is connected with the intelligent scheduling server and is used for storing producer information, equipment states, inventory data and historical order data; wherein the intelligent scheduling server comprises a real-time state acquisition module which is used for acquiring the equipment state of the distributed production node in real time through an API (Application Program Interface) or active reporting of a producer. According to the invention, by integrating social idle distributed manufacturing resources, a multi-level collaborative production network covering local street graphic and text stores to source factories is constructed, and accurate and efficient matching of production orders and optimal producers is realized by using real-time state monitoring and a multi-dimensional weight scoring algorithm.

The embodiment of the invention discloses a multi-task optimization method for multi-user target requirements of a distributed manufacturing system, and relates to the technical field of intelligent manufacturing. According to the scheme, the method comprises the steps that a distributed manufacturing platform receives manufacturing demand information uploaded by a client terminal and establishes a manufacturing task set; performing matching processing on the manufacturing task set and the manufacturing resource set to obtain a candidate service set corresponding to the manufacturing task; and determining service information matched with the sub-tasks of the manufacturing tasks in the manufacturing task set from the candidate service set, obtaining a feasible service combination corresponding to the manufacturing tasks, and then sending order information to a corresponding enterprise terminal according to the obtained feasible service combination. The method can accurately and effectively reflect the effect that the scheduling scheme optimizes different user targets, alleviates the calculation pressure when a scheduling control system of the distributed manufacturing system deals with task scheduling caused by too many tasks and targets, and promotes the improvement of the operation efficiency of the distributed manufacturing system.

A system (100) for reducing carbon dioxide emissions using trusted on-demand distributed manufacturing, with a processor (102) and a memory (104), includes a first interface (120) configured to receive product data from a product data source (110-A, 110-B, 110-N), a second interface (130) configured to exchange manufacturing data from a manufacturing data source (140-A, 140-B, 140-N), a matching module (174) configured via computer executable instructions to match the product data with the manufacturing data based on manufacturing characteristics for producing a product (154) as described in the product data, a carbon footprint module (180) configured via computer executable instructions to determine a traditional carbon footprint and an actual carbon footprint of the product (154), and determine a carbon dioxide reduction based on the traditional and the actual carbon footprint of the product (154), and wherein the system (100) is configured to automatically transmit the carbon dioxide reduction to a certification body (240).

The invention discloses a multi-target collaborative scheduling method for an Andon system and maintenance resources, and relates to the technical field of industrial manufacturing. The invention innovatively provides a multi-target collaborative scheduling method based on a three-dimensional evaluation matrix, an abnormal level, an equipment value and a maintainer skill, realizes automatic distribution of a maintenance task to the nearest skill matching personnel, and pushes a work order in real time through WeChat. The AGV and the maintenance robot are integrated in the system for cooperative operation, the AGV automatically distributes spare parts according to the maintenance scheme, the maintenance robot receives disassembly and assembly guidance through AR glasses, and the maintenance efficiency of complex equipment is improved. Meanwhile, a cross-factory resource borrowing mechanism is established, when local spare parts are insufficient, the inventory of adjacent factories is automatically retrieved, an allocation instruction is generated, and efficient sharing and collaboration of multi-factory maintenance resources are achieved. According to the method, the abnormal response speed, the equipment utilization rate and the maintenance resource scheduling intelligent level are remarkably improved, and the method is suitable for a large-scale distributed manufacturing scene.

The present subject matter relates to an authentication method in a distributed manufacturing automation system (100, 200). The distributed manufacturing automation system (100, 200) is configured to include a plurality of levels of automation pyramids. The method comprises: receiving, from a user of a level (117) of the automated pyramid referred to herein as a source level, a data access request for data in a set of systems of another level (115) of the automated pyramid referred to herein as a target level, the data access request comprising a token, the token comprises a group of sub-tokens for authenticating the group of systems respectively; sending the group of sub-tokens to the group of systems; receiving a set of verification values from the set of systems, respectively; the set of verification values is used to authenticate the user for the set of systems, respectively.

The application discloses a kind of process beat driving distributed manufacturing multi-source data cooperation and closed-loop control method, belong to industrial automation and intelligent manufacturing field, through real-time acquisition main drive motor operating frequency by sensor and calculate real-time capacity, anchor the main control beat of whole line cooperation;Based on front-end discharge bin level and change rate, a cross-process load prediction model is constructed, and the operating beat of the feed frequency converter is dynamically adjusted;Using industrial communication network to summarize multi-process operation parameters to establish interaction matrix, extract the load feature vector of the back-end process for real-time state monitoring;When triggering early warning, execute adaptive speed reduction algorithm to fine-tune the main drive frequency, and simultaneously adjust the heating power compensation of each temperature zone;Under the condition of maintaining the continuous operation of the system, the abnormal non-stop closed-loop disposal is realized, the consistency of the material sintering thermal history is ensured, the problem of whole line shutdown and material scrap caused by local fluctuation is effectively solved, and the production stability and product quality consistency of distributed manufacturing are improved.

The application discloses a kind of scheduling method of distributed manufacturing based on empire competition algorithm, comprising the following steps: establishing the objective function including minimizing maximum completion time, minimizing maximum machine load and minimizing total energy consumption, and setting the constraint condition of objective function according to the assembly process of product;Set coding and decoding rules, encode process sequencing and machine selection to obtain process sequencing vector OSV and machine selection vector MAV;Set the hybrid initialization rule of OSV and MAV, generate initial solution set;Calculate the objective function value of all initial solutions in initial solution set, select the better solution as the colony from it, the remaining initial solution is as the colony, adopt OX cross to realize the assimilation between colony, adopt POX cross to realize the assimilation between colony and colony, generate new solution set;Design the neighborhood of OSV and MAV, carry out variable neighborhood descent search to colony, obtain the optimal production scheduling scheme.

A method, computer program product, and system are disclosed. The method, when implemented in a computer system, includes obtaining product information, selecting a production node from a plurality of production nodes, and communicating production information to the production node. The product information is configured to facilitate production of a product. The selecting performed by the computer system comprises determining a physical location of a destination of the product and identifying the production node. The identifying is based, at least in part, on the physical location and one or more production criteria. The production information comprises information identifying the product. The computer system is configured to communicate with each production node of the plurality of production nodes. The communicating is configured to result in production of the product by the production node.

The present subject matter relates to an authentication method in a distributed manufacturing automation system (100, 200). The distributed manufacturing automation system (100, 200) is configured as an automation pyramid comprising a plurality of levels. The method comprises: receiving, from a user of a level (117) of the automation pyramid, herein referred to as source level, a data access request for data in a set of systems of another level (115) of the automation pyramid, herein referred to as target level, the data access request comprising a token, the to-ken comprising a set of sub-tokens for authentication against the set of systems respectively; sending the set of sub-tokens to the set of systems; receiving, from the set of systems, a set of verification values respectively; using the set of verification values for authenticating the user against the set of systems respectively.

An information technology system for a distributed manufacturing network includes an additive manufacturing management platform with an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from a set of distributed manufacturing network entities and execute simulations on digital twins of the set of distributed manufacturing network entities to make classifications, predictions, and optimization-related decisions for the set of distributed manufacturing network entities. The information technology system includes a distributed ledger system integrated with a digital thread and configured to provide unified views of workflow and transaction information to the set of distributed manufacturing network entities.