87 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 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 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 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 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 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 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 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.

This invention belongs to the field of nuclear power plant engineering technology, specifically relating to an automated management system for a concrete production line. The system includes: an order management module for managing concrete production orders; a production line management module for managing the operation of multiple production lines; and a warehouse management module for managing a dedicated first material warehouse for each production line and a shared second material warehouse for all production lines. When the order management module assigns a production order to the corresponding production line, the production line management module determines the target concrete output based on the order details and schedules the production line's machinery to retrieve production materials from the first and second material warehouses to initiate concrete production. The warehouse management module updates the inventory in both warehouses after the production order is completed. This invention achieves fully automated management of the entire concrete production process, from order allocation to inventory updates, through the collaborative work of order management, production line management, and warehouse management.

The application discloses a kind of digital production scheduling method and system based on forging process time model, it is related to aerospace forging production field.The method is by each production order is carried out process splitting, with process as unit to carry out month plan, week plan and day plan production scheduling, realize "process+discrete" hybrid manufacturing mode adaptation, break through the process adaptation limit of traditional single manufacturing mode, make production scheduling algorithm and aerospace forging production accurate matching with actual scene, improve process adaptability, by setting maximum holding time constraint double-mode time accounting model and heating furnace-press timing coordination constraint model, carry out the constraint between equipment process, avoid equipment conflict, product quality consistency is poor, delivery cycle is long etc., realize the efficiency, stability and compliance of production.

This invention discloses a pre-set and then linked method for collaborative pricing and production of printed materials, belonging to the field of information management technology in the printing industry. It includes acquiring historical production order data from target customers, extracting specifications, process routes, and material information for each order, constructing a dedicated product template library for that customer, responding to receiving current production requirement parameters, synchronously and in parallel executing and responding to the review and confirmation instruction for the optimal production plan, and automatically generating a production work order associated with that production plan. This invention, through an atomic decomposition mechanism, automatically generates a production work order after reviewing and confirming the optimal production plan, and then decomposes it in parallel into three types of atomic documents: material purchase orders, production task orders, and process outsourcing orders. These three documents are associated through the same work order identifier, achieving end-to-end data connectivity from quotation to production, eliminating information silos, making quotation-to-production possible, and significantly shortening the order response cycle.

The invention provides a production control system and method based on Internet-of-Things equipment, and belongs to the technical field of Internet-of-Things equipment, and the method specifically comprises the steps: determining the production load of a production order in a scheduling plan time period based on an interval time length, and carrying out the adjustment of the production load in different scheduling plan time periods based on the adjustment data of the production load in different scheduling plan time periods, when it is determined that optimization monitoring processing of the Internet of Things equipment needs to be carried out, the monitoring data change type of the Internet of Things equipment of the production equipment is determined according to the monitoring data range of the monitoring data of the Internet of Things equipment under different production loads; and according to the monitoring data change type of the Internet of Things equipment of the production equipment and the interval duration between the delivery date corresponding to the production scheduling plan time period and the delivery date of other production orders, the production scheduling plan time period for optimizing and dynamically adjusting the production load is determined, and the reliability degree of monitoring analysis processing of the Internet of Things equipment is improved.

The invention relates to the technical field of production and manufacturing, in particular to a method and device for determining the available surplus of materials and a storage medium. Comprising the steps of obtaining a to-be-produced order and the number of to-be-produced products corresponding to the to-be-produced order; determining materials required for producing the to-be-produced product, demand dates of the materials and the demand quantity of the materials corresponding to each demand date; determining the total demand quantity of the materials corresponding to each demand date according to the demand quantity of the materials corresponding to each demand date and the number of the to-be-produced products; obtaining current inventory data of the materials; determining delivery in-transit data and delivery in-transit data of materials corresponding to each demand date according to the to-be-produced order; according to the current inventory data of the materials, the delivery in-transit data, the distribution in-transit data and the total demand quantity of the materials on each demand date, the available surplus of the materials on each demand date is determined, the calculation precision is improved, the available surplus is determined more accurately, the production efficiency is improved, and the labor cost is reduced.

The invention discloses an automatic warehouse logistics system for a furniture factory, and particularly relates to the technical field of intelligent manufacturing and logistics scheduling, and the system comprises the steps: constructing an efficiency portrait model for each material circulation path in a warehouse; after a production order is received, analyzing and generating an initial task set; an efficiency portrait model is deeply integrated into an optimization solver, so that the optimization solver can dynamically evaluate extra consumed time caused by inter-task interference for different equipment operation sequence schemes generated in the optimization process, the optimization direction is guided according to feedback, finally, an equipment-level operation plan is generated and converted into an executable instruction to be issued, data is collected after execution, and the efficiency portrait model is obtained. Performing root cause analysis on the task generating the significant deviation, and converting experience into scheduling strategy knowledge for adjusting subsequent optimization constraints to form a self-evolution closed loop; according to the method, accurate quantification and avoidance of dynamic interference in a planning stage can be realized, and the overall efficiency and stability of warehouse logistics under complex mixed batch sorting operation are improved.

The invention belongs to the technical field of automatic production management, and particularly relates to a workpiece counting production management system and method and application. The system comprises process equipment, an execution system, a PLC control unit, an operation touch screen, an upper computer management system, a code scanning gun, a marking machine and a production management system. The workpiece counting production management method comprises the steps of (1) order information initialization and issuing, (2) verification mechanism of an upper computer system on a production order, (3) confirmation of whether a field has a production condition, (4) execution of a production flow, (5) production order completion processing, and (6) production process interruption processing. The whole-process data acquisition and monitoring from order issuing, workpiece production, quality judgment to finished product identification are realized. The system can perform full-process counting and tracking on the workpiece production process, automatically distinguish OK workpieces from NG workpieces, synchronize data with a production management system in real time, and ensure the accuracy and real-time performance of the production data of the management system.

The invention provides an order generation method and apparatus, an electronic device and a storage medium. The method comprises the steps of obtaining order information and material inventory information for a to-be-produced product; based on the order information and the material inventory information, determining material distribution information for the to-be-produced product; the material distribution information comprises the initial distribution quantity of each material; determining whether substitute material group information exists in the material distribution information or not; when substitute material group information exists in the material distribution information, for each substitute material group, determining a first material based on an initial distribution number of materials in the substitute material group; and generating a first production order for the to-be-produced product based on the first material and the non-substitute material in each substitute material group. A production order can be made according to the actual stock of the materials, and accurate material picking is achieved. Meanwhile, order generation is carried out based on whether the substitute material group exists or not, production orders can be flexibly generated according to different conditions, misuse and mixed use of substitute materials are reduced, and convenience is provided for inventory management.

A system and method of a multi-level tank-based production system. Embodiments include planning data for one or more finished goods, the one or more finished goods produced from one or more semi-finished goods stored in one or more tanks, identifying, from the planning data, planned production orders for the one or more finished goods in each time bucket of a planning period, modifying the planned production orders to satisfy lot-size requirements of production operations of the one or more finished goods and time and tank capacity constraints of the one or more semi-finished goods, generating a tank-based production plan based, at least in part, on the modified planned production orders, and producing the one or more finished goods according to the tank-based production plan.

The application provides a multi-level production scheduling method based on production orders, which comprises the following steps: S1, obtaining order information of orders to be sequenced, and constructing an order priority model with different order importance coefficients and user waiting time minimization as targets, wherein a target function and a constraint condition are arranged in the order priority model; S2, constructing a daily production planning model with the order priority model as a target based on the production capacity, vehicle type and color distribution proportion constraints of a workshop, and realizing minimum violation of soft constraints under the premise of meeting hard constraints by proposing an integrated planning and production scheduling mode of upstream and downstream linkage, aiming to meet production constraint conditions and target demand. Through the method, enterprises can better manage production processes, improve production efficiency, and optimize resource utilization, so as to cope with market changes and customer demand, improve the overall service of enterprises, ensure the stability of the supply chain, and improve the production efficiency.

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 calculating the adjusted available time, 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 order 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 order. Abstract figure: Fig. 1