130 results about "Production order" patented technology

The invention discloses an AI-based intelligent factory dynamic production scheduling optimization method and system, and belongs to the technical field of factory dynamic production scheduling, and the method comprises the following steps: obtaining and integrating the working states of various types of equipment in a factory, the stock position states of different materials, and the manual data; the production order state, the process route requirement, the plan and the completion time of each process and the delivery date requirement of the customer are determined; generating an initial production scheduling plan through an AI optimization algorithm in combination with supply chain material data, factory storage space, equipment switching cost, production rules, each order process dependency relationship and a production target; according to the method, the initial scheduling plan is generated by acquiring and integrating multiple types of production data, the dynamic events are monitored, multiple schemes are generated through evaluation, the optimal scheme is selected through economic model evaluation, and production refinement, dynamic response and benefit optimization are achieved.

The invention relates to an intelligent scheduling management method and system for aluminum profile production, and the method comprises the following steps: obtaining and cleaning the original data of a to-be-produced order, and obtaining standardized preprocessing production order data; extracting production characteristic data in the orders, and performing priority ranking on the orders according to the production characteristic data; task time windows are distributed to all the process link devices based on the sorting result, and a task time window distribution table is generated; resource matching analysis between the equipment and the task is carried out based on the table, and an equipment-task adaptation degree matrix is obtained; finally, the adaptation degree matrix is sent to an industrial control system, the production line is driven to automatically execute corresponding machining tasks, and the technical problem that a traditional aluminum profile production line mostly depends on artificial experience to conduct task scheduling and equipment arrangement and is difficult to adapt to the market trend of multiple varieties, small batches and fast delivery time, and consequently the production efficiency is low is solved.

The invention belongs to the technical field of intelligent manufacturing, and discloses a production order automatic scheduling correction method and system, and the method comprises the steps: obtaining a product material list; determining a product process route according to the product type and the process comparison result; marking resource configuration of a process route and a production scheduling state of the product; creating a production order for the products of which the production scheduling states are to be scheduled, and forming a production order level material list according to order information of each level and a product material list; according to the production requirements of the products, the production scheduling logic of the products is selected from the shortest construction period logic, the earliest delivery time logic and the emergency order insertion logic, and production scheduling of the production work orders is carried out; when the production work order is arranged, generating a processing equipment Gantt chart based on the processing information of the processing equipment and the production work order information; and correcting the production scheduling plan of the production order by using the automatic correction logic in the Gantt chart of the processing equipment. The automatic production scheduling efficiency of production is improved, and the customer satisfaction is reduced and improved.

The invention relates to the technical field of intelligent manufacturing, and discloses a production scheduling system of a production line and a scheduling method thereof. According to the system and method, key information such as production orders, equipment states and raw material inventory is collected in real time through the data collection unit, basic data is provided for subsequent analysis, the data analysis unit can rapidly evaluate the production capacity and the resource utilization rate, the orders are subjected to priority ranking, and it is ensured that the production efficiency is improved in the dynamically changing market environment. The production plan can preferentially meet the most emergency and important requirements, the scheduling decision-making unit rapidly generates an optimized preliminary schedule by applying an advanced scheduling algorithm, the manual intervention time is shortened, the response speed is improved, the scheduling execution unit ensures that a production instruction is issued and executed in time, the production progress is monitored in real time, and the production efficiency is improved. And the optimization unit continuously improves a scheduling strategy by evaluating and feeding back an execution result, so that the production efficiency is improved, the cost is reduced, and meanwhile, the timeliness of delivery and the customer satisfaction are ensured.

The invention, which relates to the technical field of printing production management, discloses a production processing tracking system and tracking method for a printing industry, and the method specifically comprises the steps: creating a corresponding production order in a preset printing production management system based on customer demand information, generating a unique identification code for each production order according to a dynamic random number algorithm, and associating and binding the unique identification code with each production order; obtaining a process node of each production order associated with the unique identification code to construct a process dependency graph of each production order; calculating the remaining delivery time of each production order associated with the unique identification code, and sorting each production order in real time to construct a self-adaptively updated priority scheduling queue; obtaining a current process node of each production order, and obtaining a state attribute of each process node of each production order and a corresponding execution progress; and carrying out full-link visual display on the state attribute of each process node of each production order and the corresponding execution progress, and inputting a unique identification code through a client to carry out query.

The invention provides a carbon powder production line energy consumption optimization method and system, and is applied to the technical field of energy consumption optimization in the production and manufacturing field, and the method comprises the steps: obtaining a production order, decomposing the production order into subtasks and time-of-use electricity price information, dividing a time slot, calculating the energy cost, constructing a mathematical optimization model according to the energy cost, and solving the mathematical optimization model. And a group of optimal decision variable values are found, so that the total energy cost is minimum, and all production constraints are met. Through the steps, the method integrates the production task, the equipment capability, the dynamic energy price and the production constraint into an optimization framework, and finds the production scheduling scheme with the lowest energy cost through the solving model, so that the technical problem of reducing the energy consumption cost while meeting the production requirement is solved, and the method has the advantages of reducing the energy consumption and improving the production efficiency. And the production plan is optimized.

The invention belongs to the technical field of order management, and particularly relates to a production order supply planning management system based on data analysis, and the system comprises an order data collection module which is used for collecting customer order data, and the customer order data comprises historical order data and current order data; the order data analysis module is used for calculating the demand quantity of product orders in M periods in the future based on the obtained historical order data; the supply chain data collection module is used for collecting data of each production line in a supply chain; the supply chain data analysis module is used for calculating the actual order demand quantity of the product in the M periods in the future based on the product order demand quantity and the data of the production line in the supply chain; and based on the data of the production line in the supply chain and the actual demand of the product, the delivery time index of the order product required by the current customer is calculated.

The invention provides a production management system for a processing industry, and the system comprises a model construction module which constructs a processing industry model and an artificial intelligence algorithm model; the production planning module performs demand order splitting, merging and priority ranking processing according to the processing industry model to form a production order and a corresponding work order; the production execution module carries out processing production according to the work order and collects production operation data in real time; and the scheduling updating module dynamically updates the production order and the work order by using an artificial intelligence algorithm model according to the processing result of the production operation data. Through productization modeling and configurable scheme design, flexible definition and calling can be realized in processing, so that information transmission, recording and business management and control of products in the whole process of research and development design, demand transmission, production plan scheduling, production execution process, sales and delivery and the like are satisfied.

The invention discloses a production scheduling system based on production orders. The production scheduling system comprises a data integration module, an intelligent scheduling module and the like. According to the system, data of an ERP system and data of a delivery system are associated, cleaned and integrated through a data integration module, and effective input is provided for an intelligent scheduling module. The intelligent scheduling module adopts a weight calculation method, calculates order priority values by comprehensively considering various factors such as order delivery remaining date, whether an e-commerce order or not, whether an emergency order or not, time required for order production, product priority and the like, sorts the order priority values, and reasonably arranges an order sequence; in the aspect of production resource allocation, the remaining available work number is calculated in combination with productivity, the order demand with high weight is preferably met, and the resource utilization rate is improved; meanwhile, the adjustment of coefficients in a weight formula enhances the accuracy and adaptability of scheduling calculation, so that the scheduling result is more suitable for actual production; the emergency order processing module can quickly process emergency orders and reduce the influence on a normal production plan; in addition, the system also has the functions of automatic execution, report generation, linkage of the ERP system and the delivery system and the like. Through cooperative work of the modules, the overall efficiency and flexibility of production scheduling are effectively improved.

The invention discloses an anomaly analysis method and device for production management and electronic equipment, and relates to the field of data processing. The method comprises the following steps: acquiring a plurality of production orders, and generating a corresponding process tracking code for each production order; associating the process tracking code to a business document in a production management system to generate an associated data set; based on the associated data set, constructing a multi-dimensional production element map, and based on the multi-dimensional production element map, generating a three-dimensional process sand table, the three-dimensional process sand table comprising a topology view, a thermodynamic view and a tracing view; inputting the process delay event into the three-dimensional process sand table, determining upstream and downstream nodes and edges related to the process delay event, and forming an abnormal propagation path; and based on the abnormal propagation path, reasoning the process delay event to obtain an abnormal reason. By implementing the technical scheme provided by the invention, the abnormal reason is quickly positioned, and the production efficiency is improved.

The invention relates to a digital operation auxiliary method, system and equipment for multi-mode production and a medium. The method comprises the steps of obtaining production order information and generating an operation guidance program which comprises a process route, processes, steps and steps, and issuing the process route, the processes, the steps and the steps to an operation terminal. After receiving the operation guidance program, loading the first process information, and determining whether the qualification of the operator meets the requirement or not. And if yes, loading the bill of materials, guiding material taking, and verifying the materials through an indicating lamp or bar code scanning. And after material verification, executing a tool operation step, activating a tool through the operation terminal, setting control parameters, and completing tool operation. And after the operation is completed, collecting and recording operation data including results, material barcodes and tool states, and storing the operation data to the terminal. And judging whether the process is completed, if not, entering the next process step, and if so, uploading operation data. And if the process is the last process, generating and recording product resume information. According to the method, the cooperation efficiency and the quality control capability of the operation process are improved.

The invention provides a production order management method and system based on artificial intelligence, and relates to the technical field of production management. The method comprises the steps of obtaining predicted order information according to historical order information and industry trend information; according to the customer order information, the prediction order information and the product inventory information, generating supplementary library order information; according to the customer order information, the research and development order information and the replenishment order information, determining an order execution sequence and a production process sequence of the order; according to the order execution sequence, the production process sequence and the equipment capacity, a production equipment sequence and a production plan are determined; if the order insertion information is received, the order execution sequence, the production equipment sequence and the production plan are updated according to the information of the orders being executed, the order execution sequence and the order insertion information; if the production plan of the production equipment needs to be updated, the real-time capacity of the production equipment is determined, and the production equipment sequence and the production plan are updated. And the flexibility and response speed of production order management are improved.

The invention provides an industrial production automatic scheduling method and system. The industrial production automatic scheduling method comprises the following steps: S1, multi-source data acquisition: acquiring corresponding data from a material information table, a production order information table, a material list and a process flow table, and based on an MQTT protocol, equipment sends an operation state, predicted maintenance time and equipment productivity information to a server in real time through an MQTT client to form a database; s2, cleaning and clustering the data in the database; s3, performing scheduling calculation by using a particle swarm algorithm to obtain an optimal scheduling scheme; and S4, transmitting the optimal scheduling scheme to a result output module, and generating a detailed report. Compared with the prior art, the scheduling scheme can be comprehensively optimized, the anti-interference capability of the system is enhanced, and the production management refinement degree is improved.

The invention relates to a method for filling a filling installation, comprising a step of receiving tasks to be performed and a set of resources to be used, a step of selecting available resources corresponding to the resources to be used, and of selecting the tasks to be performed and at least one production order such that the set of tasks to be performed of said at least one production order is selected, a step of defining a complete execution sequence of the selected tasks to be performed such that the time to perform each selected task to be performed is less than or equal to the available time of the selected available resources, and a step of filling at least a portion of the plurality of available containers according to the complete execution sequence. Abstract figure: Fig. 1

The invention belongs to the technical field of scheduling optimization, and discloses a manufacturing industry advanced plan scheduling system and method based on artificial intelligence, and the method comprises the steps: generating an initial scheduling scheme according to production order data and manufacturing resource constraint data; analyzing the initial scheduling scheme to establish a basic time sequence graph, and performing man-hour probability distribution fitting on each task node based on historical production data to obtain a probability time sequence graph; and traversing each task node, calculating and correcting the material ready time based on the man-hour probability distribution function of the previous task node and a preset on-time completion confidence coefficient, updating the plan time of each task node, and obtaining a final production schedule. Adjacent processes form a parallel overlapping relation by starting a time delay mechanism, so that the production cycle is effectively shortened; and meanwhile, the planned time is dynamically adjusted based on the man-hour probability distribution, the time margin can be reserved according to the difference of the actual fluctuation characteristics of each process, and the robustness of the scheduling scheme is improved.

The application discloses a kind of based on ERP system's dynamic feeding back calculation processing method, equipment and medium, belong to enterprise informationization ERP technical field, for solving the existing feeding back calculation is prone to deviation, easily influenced by a variety of uncertain factors, it is difficult to accurate prediction and adjustment, increase the technical problem of production risk.Method includes: according to target production product, BOM table is matched and inquired and handled, and the required material information is obtained;According to the inventory result where the required material information is located, the available inventory usage of maximum production is judged, and the usage result is obtained;If the matching result is not check matching result, then according to the required material information, the product quantity of target production product is determined;If the matching result is check matching result, then the available inventory of each required material information in BOM table is circulated, and the product quantity of target production product is determined;Based on product quantity and BOM table, feeding production order information is generated.

The invention discloses an intelligent production scheduling method based on a block chain technology and electronic equipment, and relates to the technical field of industrial intelligent production scheduling. According to the intelligent production scheduling method based on the block chain technology and the electronic equipment, the intelligent production scheduling model is established according to the actual production equipment efficiency and the block chain technology, and the production order data in the period is analyzed by using the data analysis algorithm; according to consumed time and various data in a material tracing real-time process, sorting operation of production orders is realized, a planned production plan is formed, the Internet of Things and a collaborative algorithm are fused, the production process is monitored in real time, problems generated by the orders are effectively predicted in advance, and a multi-target optimization modeling and visualization technology is adopted to realize real-time production planning. Full-chain collaboration and integration technology restrictions of resource management, data analysis and business parallel driving are broken, a production scheduling plan is quickly formed, and intelligent manufacturing is promoted.

The invention discloses an article scheduling method, a processor and a program product. The method comprises the steps that in response to an obtained production work order, the production work order is analyzed, work order demand data is obtained, the production work order is used for requesting to schedule articles stored in a storage area, and the work order demand data is used for representing to-be-scheduled articles needing to be scheduled in the storage area and scheduling information of the to-be-scheduled articles; according to the work order demand data, scheduling authority information of a warehouse management object of the storage area is determined, and the scheduling authority information is used for representing the authority of allowing the warehouse management object to schedule the to-be-scheduled article; and in response to a scheduling instruction from the warehouse management object, satisfying the scheduling permission information, and scheduling the to-be-scheduled article according to the scheduling instruction. The technical problem of low data processing efficiency is solved.

The invention relates to a computer-aided manufacturing process (10) for producing workpieces (12, 12a, 12b, 14, 16) by means of several workpiece orders (20, 20a, 20b, 22, 22a, 22b, 24, 24a, 24b) defined in manufacturing orders (18, 18a-c) from several workpiece blanks (26) with a manufacturing system (28) comprising the process steps: a) Forming (30) a processing queue (32) by separating the workpiece orders (20, 20a, 20b, 22, 22a, 22b, 24, 24a, 24b) contained in the production orders (18, 18a-c) by assigning an order affiliation; b) Creating (36) a cross-order production plan (38) by positioning at least some of the workpiece orders (20, 20a, 20b, 22, 22a, 22b, 24, 24a, 24b) provided in the processing stock (32) on one or more workpiece blanks (26); c) Establishing (40) a partial production plan (42a-d) of the production plan (38), wherein the partial production plan (42a-d) provides for the production of the workpiece orders (20, 20a, 20b, 22, 22a, 22b, 24, 24a, 24b) positioned on a single workpiece blank (26), wherein the establishment is carried out taking into account a occupancy level of the workpiece blank (26); d) Manufacturing (44) the workpieces (12, 12a, 12b, 14, 16) according to the workpiece orders (20, 20a, 20b, 22, 22a, 22b, 24, 24a, 24b) of the part production plan (42a-d). The invention also relates to a manufacturing system (28).

The invention discloses a garment production order accurate quotation system based on multi-factor analysis, which belongs to the technical field of garment production and comprises a data acquisition module, a material unit price setting module, a rule coefficient setting module, a quotation calculation module and a quotation output module. According to the invention, the real-time unit price of the material is formulated based on the collected market dynamic data, then the real-time coefficient of the customer and the real-time coefficient of the order are formulated based on the collected customer related information data and the order feature information data, and then a plurality of order quotations are calculated based on the formulated real-time unit price of the material, the real-time coefficient of the customer and the real-time coefficient of the order. Compared with the prior art, the order quotation can be quickly obtained, adjustment can be performed according to the real-time condition of the market, and the rationality and timeliness of quotation are ensured.

The invention discloses a production scheduling method and device, equipment and a medium. The method comprises the steps of obtaining order information of a production order and equipment information of production equipment; determining at least one target device in the at least one production device based on the order information of the production order and the device information of the production device, and determining an initial production process; acquiring state information of the at least one target device in a production process according to the initial production process; and determining an optimized production process according to the order information, the initial production process and the state information of the at least one piece of target equipment, thereby effectively solving the problems that the progress is influenced by frequent faults of part of equipment, resource waste is caused by low-load operation of part of equipment, and the production efficiency is improved due to the fact that the actual state and performance difference of the equipment are not fully considered in the existing production arrangement mode. The production efficiency is difficult to reach the optimum, the cost is increased, and the delivery is influenced.

The disclosure relates to a method of creating a production order in an automated storage and retrieval system, the production order comprising a preselected set of order components, the method comprising receiving an order component preselection, retrieving the components at the automated storage and retrieval system, collecting the set of components as a production order kit and storing the production order kit at the automated storage and retrieval system.

The invention discloses a method for binding order numbers of three-in-one products in LCD (liquid crystal display) module production, which comprises the following steps of: 1, when a preset model production order of an LCD module is received, writing an order number code containing model information corresponding to the model product into a background system; 2, the LCD module product to be processed is fed into a three-in-one automatic machine table, a product two-dimensional code on the LCD module product is scanned through a code scanning gun arranged on the three-in-one automatic machine table, and the scanned product two-dimensional code is transmitted to an upper computer of the three-in-one automatic machine table; and step 3, the upper computer sends the received product two-dimensional code to a background system. Compared with a traditional mode, order number recognition is added in three-in-one software, the situation that production line workers misplace products is intercepted, and the method has the following effects that the use probability of secondary burning is reduced; the product scrapping probability is reduced; customer complaints are reduced, and the quality of company products is improved; the cost and the reworking cost are reduced.

The application belongs to the technical field of production line management, and discloses a food production line automatic management method and system based on intelligent control, which comprises the following steps: extracting a production line capable of producing a target product based on a product name, then formulating a production plan for a production order and assigning a production line based on preset rules, obtaining control information and initial operation parameters of each process on the target production line before production of the first production order, judging whether the target production line meets preset standards based on the control information and the initial operation parameters, and starting production when the target production line meets the preset standards, collecting and monitoring production progress information and product quality information of the first production order during order production, generating production plan adjustment suggestions or reminding information if production progress or product quality is abnormal, and sending the production plan adjustment suggestions or the reminding information to relevant personnel, and generating a delivery reminder after the first production order is completed. The technical scheme can improve the flexibility of production management and improve the overall production management level.

The present invention discloses a production control method and system for an aviation composite material workshop, belonging to the technical field of workshop production management. The production control method includes the following steps: S1, obtaining production order information; S2, obtaining part drawing number information; S3, classifying the production order information to obtain the first classification information of parts; S4, obtaining part material information according to the production order information; S5, obtaining part process information; S6, obtaining node process information and parallel process information according to the part process information; S7, obtaining part classification information; S8, obtaining workshop production plan information according to the node process information, parallel process information and part classification information; S9, producing parts according to the workshop production plan information. By effectively classifying the parts, the present invention not only improves the production control efficiency of the workshop, but also improves the stability and reliability of the part production quality.

The application discloses a production quality inspection scheduling method, an automatic processing production line and a numerical control machine tool. The production quality inspection scheduling method comprises the following steps: obtaining a production order; performing NLP analysis on the production order to obtain a structured delivery task; scheduling an AGV to transport materials to a processing terminal according to the delivery task to obtain processing materials; judging whether the working state of a quality inspection terminal meets a preset condition; if yes, scheduling the AGV to transport the processing materials to the quality inspection terminal for quality inspection, and then calling the AGV to transport the quality inspection materials to a warehouse; if not, scheduling the AGV to transport the processing materials to a warehouse, and calling the AGV to transport the processing materials from the warehouse to the quality inspection terminal for quality inspection when the quality inspection terminal is idle, and then calling the AGV to transport the quality inspection materials to the warehouse. The application can improve the utilization rate of quality inspection in the production line, further improve the processing efficiency of the production line, increase the yield and save resource costs.

The present application relates to a production management method for industrial capacity allocation, including: identifying production order requirements in a production order, and analyzing the disassembled production order; simulating and allocating the production order to an existing production line; disassembling the production line, recombining the production line, and allocating the production order; comparing the simulation allocation results, and screening the optimal allocation result as the final capacity allocation plan. The present application improves the flexibility of production order allocation by splitting the entire production line into several production units and combining production units with the same type of production functions; by simultaneously performing irregular simulation allocation on the existing production line and performing irregular simulation allocation on the disassembled production line, and evaluating each allocation result to obtain the optimal plan, the degree of automation of the production process is improved, and the efficiency of capacity allocation is ensured.

The application provides a factory control method, system, electronic equipment and storage medium, and relates to the technical field of intelligent control, and the method comprises the steps of: acquiring a factory transfer scheduling instruction of a target product; acquiring product information of the target product and a target factory according to the factory transfer scheduling instruction; updating a product information database of the target factory according to the product information and a production state of the target product in the target factory; updating factory information of the target factory and authorized information corresponding to the target product in the front end according to the updated product information database, so that a front-end user can deliver a production order for scheduling production of the target product to the target factory according to the factory information and the authorized information. The application realizes automatic and accurate control of the target factory, instructs the user to accurately place an order in the target factory according to the factory information and the authorized information, avoids delivering invalid orders or orders that cannot be normally completed, improves the on-time completion rate of orders, and improves the user experience.

This disclosure relates to a method, device, and computer program product for managing vehicle-based electronic tags. The method includes: acquiring information related to a vehicle's production order, including status information indicating the vehicle's real-time production status and association information indicating whether the vehicle's production order is associated with an electronic tag; and determining whether the electronic tag is lost or damaged based on the status information and association information. Specifically, when the vehicle's real-time production status is the start of production, the electronic tag is associated with the vehicle's production order, vehicle-related information is written to the electronic tag, and the electronic tag is attached to the vehicle. When the vehicle's real-time production status is the end of production, the electronic tag is removed from the vehicle, the vehicle-related information in the electronic tag is cleared, and in response to the clearing of the electronic tag, the production order is deassociated with the electronic tag.

This invention discloses a big data-based production planning and management method for automotive rubber sealing strips, belonging to the field of order production planning and management technology. Specifically, it includes: integrating historical order and logistics data to construct a correlated dataset; establishing a logistics cost prediction network by analyzing production time requirements and logistics routes; generating an initial production sequence that meets all delivery deadlines based on the current pending production order pool; filtering orders with cost conflicts and forming a feature set by comparing planned delivery times with predicted low-cost windows in various regions; analyzing the matching relationship between adjustable production time windows and local low-cost windows for each conflicting order to generate a scheduling optimization parameter set; constructing a production sequence optimization model and solving for the optimal production sequence with the lowest overall logistics prediction cost. This invention, while ensuring delivery deadlines, proactively utilizes logistics price fluctuations through intelligent scheduling to reduce overall transportation costs.