Steel pipe process waiting time intelligent regulation and control system and method based on industrial Internet of Things

Abstract

The invention discloses a steel pipe process waiting time intelligent regulation and control system and method based on the industrial internet of things, and relates to the technical field of steel pipe intelligent manufacturing data analysis. After preprocessing based on the industrial data combination, constructing a steel pipe transportation execution knowledge base, and forming a plurality of groups of underlying data based on the steel pipe transportation execution knowledge base; judging whether the transport decision of the RGV is executed or not based on the plurality of groups of underlying data, and in the execution process of the transport decision of the RGV, monitoring whether process plan data issued by an upper-layer system is changed or not in real time; and when the process plan data changes, forming a three-dimensional warehouse shelf intelligent regulation and control decision based on the material data corresponding to each process and the storage data corresponding to each material data. The method is suitable for steel pipe manufacturing enterprises using the Internet of Things as a hub to construct a production management and control system, and is especially suitable for steel pipe manufacturing enterprises with multi-process collaborative production layout.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis in intelligent manufacturing of steel pipes, specifically an intelligent regulation system and method for the waiting time of steel pipe processes based on the industrial Internet of Things. Background Art

[0002] In the field of steel pipe manufacturing, a multi-process collaborative production mode with a three-dimensional warehouse as the transfer center has gradually become the mainstream choice for enterprises to build new factories or renovate and expand existing ones. The automated production units of such enterprises (such as processes like procurement in rows, welded pipe production, cold drawing, heat treatment, finishing, etc.) achieve material flow connection through the three-dimensional warehouse, forming a production layout of "warehouse as the core, process linkage". Each process not only needs to independently complete professional processing tasks but also depends on the material supply and quality output of upstream and downstream processes, presenting the characteristics of "asynchronous production, synchronous linkage", that is, the downstream process needs to dynamically adjust the production plan according to the real-time output status of the upstream process (such as material specifications, quality grades, output rhythms) to ensure the coordination and unity of the production rhythm of the entire process.

[0003] Traditional production control modes, such as relying heavily on manual professional judgment or setting production intervals on equipment, although they can ensure production, also have obvious deficiencies: Insufficient adaptability of static duration setting. The current solutions mostly preset fixed waiting times based on historical experience. Although it can be used as a reference for production capacity analysis, it is difficult to cope with real-time production fluctuations. For example, when the output rhythm of the upstream cold drawing process slows down temporarily due to equipment failures, pipe jams, etc., if the downstream heat treatment process still operates at full load according to the static rhythm, it is extremely easy to cause backlogs of materials to be processed or idling of processing equipment, forming a production fault of "loose in the front and tight in the back", and it will also lead to ineffective occupation of the RGV cart by the downstream system. When there is a lag, this lagging manual intervention or system rigid execution mode is particularly inefficient in flexible production scenarios with small batches and multiple varieties.

[0004] Lack of a collaborative mechanism driven by a single parameter. Traditional systems only focus on the production capacity parameters of a single process (such as equipment operation, remaining pipes to be processed, processing duration, RGV cart status, etc.), lacking a coupled analysis of the overall production status of all elements, resulting in vertical collaborative faults (upstream and downstream processes), horizontal linkage lags (processes and three-dimensional warehouses), and disconnection of equipment status. At the same time, changes in processes will inevitably affect the mobilization of materials. How to minimize material losses and the regulation of storage equipment is also one of the problems existing in the current collaborative system. Summary of the Invention

[0005] The purpose of the present invention is to provide an intelligent regulation system and method for the waiting time of steel pipe processes based on the industrial Internet of Things to solve the problems proposed in the prior art.

[0006] To achieve the above object, the present invention provides the following technical solutions: An intelligent regulation method for the waiting time of steel pipe processes based on the industrial Internet of Things, the method comprising: Form an industrial data combination through a collection device, specifically including process plan data issued by the upper-level system, material data corresponding to each process, and storage data corresponding to each material data; After preprocessing based on the industrial data combination, construct a steel pipe transportation execution knowledge base, and form several groups of underlying data based on the steel pipe transportation execution knowledge base; Based on several groups of underlying data, determine whether the transportation decision of the RGV vehicle is executed. During the execution of the transportation decision of the RGV vehicle, real-time monitor whether there are changes in the process plan data issued by the upper-level system; When there are changes in the process plan data, form an intelligent regulation decision for the automated storage and retrieval system shelves based on the material data corresponding to each process and the storage data corresponding to each material data.

[0007] According to the above technical solution, the process plan data issued by the upper-level system includes processing parameters of each process, real-time status data of process supporting equipment, and material application data configured for the process; The storage data corresponding to each material data includes the specific shelf type and shelf number of each material data in the automated storage and retrieval system.

[0008] According to the above technical solution, the steel pipe transportation execution knowledge base includes a waiting time knowledge base, upstream and downstream process inbound and outbound, a process time constraint library, and a historical production execution library; The waiting time knowledge base is used to store production equipment status data and logistics equipment status data. The production equipment status data includes the production status of each process, the waiting status of each process, and the waiting duration of each process; the logistics equipment status data includes the RGV vehicle number, the sending time of the RGV vehicle application, the arrival time of the RGV vehicle, and the waiting duration of the RGV vehicle; The upstream and downstream process inbound and outbound is used to store the contract numbers and plan numbers of upstream and downstream processes, the real-time inbound and outbound quantity under a certain process, and the remaining pipe row quantity; The process time constraint library is used to constrain the production situation, specifically including time constraint and capacity constraint, for determining the maximum waiting duration of the RGV vehicle and the minimum waiting number of downstream production processes; The historical production execution library is used to store the historical records of upstream and downstream process specification matching, record the equipment parameter configuration cases of different specification pipe rows in each process, form a mapping table between specifications and equipment parameters; mark the waiting duration caused by specification mismatch under each process.

[0009] According to the above technical solution, the determination of whether the transportation decision of the RGV vehicle is executed based on several groups of underlying data includes: Determine the maximum waiting duration for the RGV cart to operate, determine the optimal time to request the RGV cart based on the maximum waiting duration for the RGV cart to operate, and determine whether to execute the transportation decision of the RGV cart, specifically including: Define the completion time of the current process as:

[0010] wherein, is the current system time; is the production time of the current process; is the standard production time of a single row of pipes, which is the sum of the products of the unit production time of each specification of pipe row required in the current process and the required quantity; Construct the state function of the RGV cart:

[0011] wherein, is the estimated departure time of the RGV cart; is the remaining transportation time of the RGV cart; Construct the two-way time constraint for the moment when the Internet of Things system applies for the RGV cart :

[0012] wherein, is the execution loss duration of the RGV cart, specifically including the path travel time and the loading and unloading time. The path travel time is calculated based on the average speed under historical data, and the loading and unloading time is determined based on the average loading and unloading time under historical data; If there exists , determine to execute the transportation decision of the RGV cart and mark its transportation; if there exists , do not execute the transportation decision of the RGV cart; Under the condition of determining to execute the transportation decision of the RGV cart, form the request time of the RGV cart based on the maximum waiting duration for the RGV cart to operate.

[0013] According to the above technical solution, when the process plan data changes, the intelligent regulation and control decision of the automated storage and retrieval system shelves based on the material data corresponding to each process and the storage data corresponding to each material data includes: The change of the process plan data includes: a failure occurs in the current process, resulting in a delay, and the delay time is recorded; the system actively adjusts, changes the planned time of the next process, and records the difference between the change time and the original planned time; Set the change time value. When a fault occurs in the current process, a delay is generated, and the change time value is equal to the delay time. When the system makes an active adjustment, if the change time is earlier than the original planned time, the change time value is equal to the absolute value of the difference between the change time and the original planned time. If the change time is later than the original planned time, the change time value is equal to the negative value of the absolute value of the difference between the change time and the original planned time. Obtain the delay time of the downstream process when the change time value appears in the upstream process under historical data, and form a record data group. , where refers to the change time value that appears in the upstream process; refers to the delay time of the downstream process; the delay time of the downstream process refers to the absolute value of the difference between the originally scheduled completion time and the actual completion time of the downstream process. Based on several groups of record data groups Form a linear fitting function to construct the functional relationship between the change time value that appears in the upstream process and the delay time of the downstream process. Obtain the material data corresponding to the current process and the next process, as well as the storage data corresponding to each material data. If there is material data corresponding to the current process and the next process under the same shelf, based on the change time value of the current process, output the delay time of the downstream process, form a new call time for the material shelf required in the downstream process based on the delay time of the downstream process, obtain the time difference between the required material shelf and the new call time, compare it with the shelf call threshold set in the system. If it is less than the shelf call threshold set in the system, mark the currently required material shelf and do not execute the shelf return decision.

[0014] An intelligent control system for the waiting time of the steel pipe process based on the industrial Internet of Things. The system includes: A data acquisition and processing module, which is used to form an industrial data combination through an acquisition device, specifically including the process plan data issued by the upper-level system, the material data corresponding to each process, and the storage data corresponding to each material data; A steel pipe transportation execution module, which constructs a steel pipe transportation execution knowledge base after preprocessing the industrial data combination, and forms several groups of underlying data based on the steel pipe transportation execution knowledge base; An RGV car decision-making module, which determines whether to execute the transportation decision of the RGV car based on several groups of underlying data, and during the execution of the transportation decision of the RGV car, monitors in real time whether there are changes in the process plan data issued by the upper-level system; An intelligent control module, which forms a three-dimensional library shelf intelligent control decision based on the material data corresponding to each process and the storage data corresponding to each material data when there are changes in the process plan data.

[0015] According to the above technical solution, the process plan data issued by the upper-layer system includes processing parameters of each process, real-time status data of process supporting equipment, and material application data configured for the process; The stored data corresponding to each material data includes the specific shelf type and shelf number of each material data in the automated storage and retrieval system.

[0016] According to the above technical solution, the steel pipe transportation execution knowledge base includes a waiting time knowledge base, upstream and downstream process inbound and outbound, process time constraint library, and historical production execution library; The waiting time knowledge base is used to store production equipment status data and logistics equipment status data. The production equipment status data includes the production status of each process, the waiting status of each process, and the waiting duration of each process; the logistics equipment status data includes the RGV car number, the sending time of the requested RGV car, the arrival time of the RGV car, and the waiting duration of the RGV car; The upstream and downstream process inbound and outbound is used to store the upstream and downstream process contract numbers, plan numbers, real-time inbound and outbound quantities under a certain process, and the remaining pipe row quantities; The process time constraint library is used to constrain the production situation, specifically including time constraint and capacity constraint, to determine the maximum waiting duration of the RGV car and the minimum waiting number of pipes for the downstream production process; The historical production execution library is used to store the historical records of the specification matching of upstream and downstream processes, record the equipment parameter configuration cases of different specification pipe rows in each process, and form a mapping table between the specifications and equipment parameters; mark the waiting duration caused by specification mismatch under each process.

[0017] According to the above technical solution, determining whether to execute the transportation decision of the RGV car based on several groups of underlying data includes: Determining the maximum waiting duration of the RGV car operation, determining the best time to request the RGV car based on the maximum waiting duration of the RGV car operation, and determining whether to execute the transportation decision of the RGV car, including: Obtaining the time when the process has been produced And the standard production time of a single row of pipes , combined with the current system time , determining the completion time of the current process ; Real-time obtaining the status of the RGV car; Determining the two-way time constraint at the moment when the Internet of Things system process requests the RGV car ; If there is , determining to execute the transportation decision of the RGV car and marking its transportation; if there is , not executing the transportation decision of the RGV car; Among them, is the estimated departure time of the RGV cart; is the execution loss duration of the RGV cart, specifically including the path travel time and the loading and unloading time. The path travel time is calculated based on the average speed in historical data, and the loading and unloading time is determined based on the average loading and unloading time in historical data; Under the transportation decision of the RGV cart, the request time of the RGV cart is formed based on the maximum waiting duration of the RGV cart operation.

[0018] According to the above technical solution, the intelligent regulation module includes: A change time analysis unit for setting a change time value. When a failure occurs in the current process and a delay is generated, the change time value is equal to the delay time; when the system makes an active adjustment, if the change time is earlier than the original planned time, the change time value is equal to the absolute value of the difference between the change time and the original planned time; if the change time is later than the original planned time, the change time value is equal to the negative value of the absolute value of the difference between the change time and the original planned time; An intelligent regulation unit that outputs the delay time of the downstream process based on the change time value of the current process, forms a new call time for the required material shelf in the downstream process based on the delay time of the downstream process, obtains the time difference between the required material shelf and the new call time, compares it with the shelf call threshold set in the system, and if it is less than the shelf call threshold set in the system, marks the current required material shelf and does not execute the shelf repositioning decision.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows: In the construction process of the steel pipe production Internet of Things system, based on the interconnection of processes, real-time perception of the situation, and control of key processes of equipment, by introducing the concept of dynamic rhythm, through learning and analysis based on historical data and cross-process data, the dynamic adjustment of waiting time is realized, the production material transfer efficiency is improved, the maximum efficiency of equipment is exerted, the "bottlenecks" are reduced, and finally the production rhythm is ensured to be controllable. Among them, the dynamic optimization method of waiting time based on cross-process data replaces the traditional static time setting, and through integrating historical production data and real-time production status, the intelligent adjustment of waiting time between processes is realized, significantly improving the production material transfer efficiency, effectively coping with real-time production anomalies such as equipment failures and output fluctuations, and reducing the risk of production faults with "unequal tightness". A coupling analysis mechanism for the production status of all elements is constructed, breaking through the coordination limitations driven by single parameters, eliminating the longitudinal process coordination faults and the lag in the linkage between horizontal processes and the three-dimensional warehouse, realizing the real-time linkage and global optimization of upstream and downstream processes and warehousing logistics, and reducing the consumption of materials and equipment and the waste of time resources. It is applicable to steel pipe manufacturing enterprises that build a production control system with the Internet of Things as the hub, especially to steel pipe manufacturing enterprises with a multi-process collaborative production layout, new factories or renovated and expanded production lines presenting the characteristics of "asynchronous production and synchronous linkage", and can effectively solve the problems of full-process rhythm coordination and resource optimization in multi-variety flexible production scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the steps of the intelligent control method for the waiting time of steel pipe processes based on the industrial Internet of Things of the present invention; Figure 2 It is a schematic diagram of the structure of the intelligent control system for the waiting time of steel pipe processes based on the industrial Internet of Things of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0022] Embodiment: As Figure 1 shown, the present invention provides an intelligent control method for the waiting time of steel pipe processes based on the industrial Internet of Things, and the method includes: Form an industrial data combination through a collection device, specifically including process plan data issued by the upper-level system, material data corresponding to each process, and storage data corresponding to each material data; After preprocessing based on the industrial data combination, construct a steel pipe transportation execution knowledge base, and form several groups of underlying data based on the steel pipe transportation execution knowledge base; Based on several groups of underlying data, determine whether to execute the transportation decision of the RGV cart. During the execution of the transportation decision of the RGV cart, monitor in real time whether there are changes in the process plan data issued by the upper-level system; When there are changes in the process plan data, form an intelligent regulation decision for the stereoscopic warehouse shelves based on the material data corresponding to each process and the storage data corresponding to each material data.

[0023] The process plan data issued by the upper-level system includes the processing parameters of each process, the real-time status data of the process supporting equipment, and the material application data configured for the process; the storage data corresponding to each material data includes the specific shelf type and shelf number of each material data in the stereoscopic warehouse.

[0024] Specifically, the acquisition device can refer to collecting the real-time status of equipment such as cold drawing machines, heat treatment furnaces, finishing (straightening, flaw detection, sawing, flat laying chain), auxiliary machines, and RGVs through IoT sensors, such as temperature, operation status, rack status, working status, occupancy status, etc.; by obtaining the plan information issued by the upper-level system, obtain the processing parameters of each current process, such as specifications, number of rows, steel grades, contracts, orders, process requirements, packaging requirements, planned number of pieces, and at the same time obtain the material data corresponding to each process; obtain the processing rhythm of the current system, such as the time to apply for materials, execution information, etc. At the same time, in data preprocessing, in order to eliminate the dimensional influence between parameters and make the data on a small specific measurement scale, data standardization processing is required. What can be adopted is to normalize the input parameters and target parameters, which can help improve the convergence speed and accuracy of the model, and the administrator can set and select by himself.

[0025] The steel pipe transportation execution knowledge base includes a waiting time knowledge base, upstream and downstream process inbound and outbound, a process time constraint library, and a historical production execution library; The waiting time knowledge base is used to store the production equipment status data and the logistics equipment status data. The production equipment status data includes the production status of each process, the waiting status of each process, and the waiting duration of each process; the logistics equipment status data includes the RGV cart number, the sending time of the application for the RGV cart, the arrival time of the RGV cart, and the waiting duration of the RGV cart; The upstream and downstream process inbound and outbound is used to store the contract numbers, plan numbers, real-time inbound and outbound quantities under a certain process, and the remaining number of pipe rows of the upstream and downstream processes; The process time constraint library is used to constrain the production situation, specifically including time constraints and capacity constraints, and is used to determine the maximum waiting duration of the RGV cart and the minimum number of waiting roots in the downstream production process; The historical production execution library is used to store the historical records of the specification matching of upstream and downstream processes, record the equipment parameter configuration cases of different specification pipe rows in each process, form a mapping table between specifications and equipment parameters, and mark the waiting time caused by specification mismatch in each process.

[0026] Determining whether to execute the transportation decision of the RGV cart based on several groups of underlying data includes: Determining the maximum waiting time for the RGV cart to operate, determining the optimal time to request the RGV cart based on the maximum waiting time for the RGV cart to operate, and determining whether to execute the transportation decision of the RGV cart, specifically including: Defining the completion time of the current process as:

[0027] where is the current system time; is the production time of the current process; is the standard production time of a single row of pipes, which is the sum of the products of the unit production time and the required quantity of each specification of pipe row required in the current process; that is, during the execution of the algorithm, according to the quantity and execution time of each pipe row of the same specification, calculate the production time of each pipe, and obtain it according to the product of the quantity and the unit time when obtaining materials; Constructing the state function of the RGV cart:

[0028] where is the estimated departure time of the RGV cart; is the remaining transportation time of the RGV cart; that is, if the RGV cart is in an idle state, , ; if it is in transportation, is the remaining transportation time, ; Constructing the two-way time constraint of the moment when the Internet of Things system process applies for the RGV cart:

[0029] where is the execution loss time of the RGV cart, which specifically includes the path driving time and the loading and unloading time. The path driving time is calculated based on the average speed under historical data, and the loading and unloading time is determined based on the average loading and unloading time under historical data; If there is , determine to execute the transportation decision of the RGV cart and mark its transportation; if there is , do not execute the transportation decision of the RGV cart; When determining the transportation decision of the RGV cart, the request time of the RGV cart is formed based on the maximum waiting duration of the RGV cart operation.

[0030] When the process plan data changes, the intelligent control decision of the automated storage and retrieval system shelf based on the material data corresponding to each process and the storage data corresponding to each material data includes: Specifically, generally speaking, an automated storage and retrieval system includes structural parts such as an inbound temporary storage area, an inspection area, a palletizing area, a storage area, an outbound temporary storage area, a pallet temporary storage area, a non-conforming product temporary storage area, and a sundries area. When planning, it is not necessary to plan every above-mentioned area in the automated storage and retrieval system. Each area can be reasonably divided and the areas can be increased or decreased according to the process characteristics and requirements of the user. In terms of shelf design, due to the need to consider the utilization rate of the area and space of the automated storage and retrieval system, a large number of different forms of shelves will be set, such as beam shelves, bracket shelves, flow shelves, etc. They are reasonably selected according to the external dimensions, weight and other relevant factors of the cargo unit. When the RGV cart picks up goods, the shelf moves down to dock with the RGV cart to form material transfer; after the docking is completed, the shelf moves up to return to its original position and waits for the next RGV cart to pick up goods. Therefore, during the movement of the shelf, the shelf call threshold set in the system is generally set based on the up and down time of the shelf.

[0031] The changes in the process plan data include: a fault occurs in the current process, resulting in a delay, and the delay time is recorded; the system actively adjusts and changes the planned time of the next process, and the difference between the changed time and the original planned time is recorded; Set the change time value. When a fault occurs in the current process and a delay occurs, the change time value is equal to the delay time; when the system actively adjusts, if the changed time is earlier than the original planned time, the change time value is equal to the absolute value of the difference between the changed time and the original planned time; if the changed time is later than the original planned time, the change time value is equal to the negative value of the absolute value of the difference between the changed time and the original planned time. Obtain the delay time of the downstream process when the change time value of the upstream process appears in the historical data to form a record data group , where refers to the change time value that appears in the upstream process; refers to the delay time of the downstream process; the delay time of the downstream process refers to the absolute value of the difference between the originally scheduled completion time of the downstream process and the actual completion time of the downstream process; based on several groups of record data groups Form a linear fitting function to construct the functional relationship between the change time value that appears in the upstream process and the delay time of the downstream process; Obtain the material data corresponding to the current process and the next process, as well as the storage data corresponding to each material data. If the material data corresponding to the current process and the next process are in the same shelf, output the delay time of the downstream process based on the change time value of the current process, form a new call time for the material shelf required in the downstream process based on the delay time of the downstream process, obtain the time difference between the required material shelf and the new call time, compare it with the shelf call threshold set in the system. If it is less than the shelf call threshold set in the system, mark the currently required material shelf and do not execute the shelf reset decision.

[0032] As Figure 2 shown, there is also provided an intelligent regulation system for the waiting time of steel pipe processes based on the industrial Internet of Things. The system includes: An acquisition and processing module 101, which is used to form an industrial data combination through an acquisition device, specifically including process plan data issued by the upper-layer system, material data corresponding to each process, and storage data corresponding to each material data; A steel pipe transportation execution module 102, after preprocessing based on the industrial data combination, constructs a steel pipe transportation execution knowledge base, and forms several groups of underlying data based on the steel pipe transportation execution knowledge base; An RGV trolley decision module 103, which determines whether to execute the transportation decision of the RGV trolley based on several groups of underlying data, and during the execution of the transportation decision of the RGV trolley, monitors in real time whether there are changes in the process plan data issued by the upper-layer system; An intelligent regulation module 104, when there are changes in the process plan data, forms a three-dimensional library shelf intelligent regulation decision based on the material data corresponding to each process and the storage data corresponding to each material data.

[0033] The process plan data issued by the upper-layer system includes processing parameters of each process, real-time status data of process supporting equipment, and material application data configured for the process; The storage data corresponding to each material data includes the specific shelf type and shelf number of each material data in the three-dimensional library.

[0034] The steel pipe transportation execution knowledge base includes a waiting time knowledge base, upstream and downstream process inbound and outbound, process time constraint library, and historical production execution library; The waiting time knowledge base is used to store production equipment status data and logistics equipment status data. The production equipment status data includes the production status of each process, the waiting status of each process, and the waiting duration of each process; the logistics equipment status data includes the RGV trolley number, the sending time of the RGV trolley application, the arrival time of the RGV trolley, and the waiting duration of the RGV trolley; The upstream and downstream process inbound and outbound is used to store the contract number, plan number of the upstream and downstream processes, the real-time inbound and outbound quantity under a certain process, and the remaining pipe row quantity; The process time constraint library is used to constrain the production situation, specifically including time constraints and capacity constraints, and is used to determine the maximum waiting duration of the RGV cart and the minimum waiting number of downstream production processes; The historical production execution library is used to store the historical records of the specification matching of upstream and downstream processes, record the equipment parameter configuration cases of different specification pipe rows in each process, and form a mapping table between the specifications and equipment parameters; mark the waiting duration caused by specification mismatch in each process.

[0035] Determining whether to execute the transportation decision of the RGV cart based on several groups of underlying data includes: Determine the maximum waiting duration of the RGV cart operation, determine the optimal time to request the RGV cart based on the maximum waiting duration of the RGV cart operation, and determine whether to execute the transportation decision of the RGV cart, including: Obtain the time when the process has been produced And the standard production time of a single row of pipes , combined with the current system time , determine the completion time of the current process ; Obtain the status of the RGV cart in real time; Determine the two-way time constraint at the moment when the Internet of Things system process requests the RGV cart ; If there is , determine to execute the transportation decision of the RGV cart and mark its transportation; if there is , do not execute the transportation decision of the RGV cart; Among them, is the estimated departure time of the RGV cart; is the execution loss duration of the RGV cart, specifically including the path driving time and the loading and unloading time. Calculate the path driving time based on the average speed under historical data, and determine the loading and unloading time based on the average loading and unloading time under historical data; Under the condition of determining to execute the transportation decision of the RGV cart, form the request time of the RGV cart based on the maximum waiting duration of the RGV cart operation.

[0036] The intelligent regulation module includes: The variable time analysis unit is used to set the variable time value. When a failure occurs in the current process and causes a delay, the variable time value is equal to the delay time; when the system actively adjusts, if the change time is earlier than the original planned time, the variable time value is equal to the absolute value of the difference between the change time and the original planned time; if the change time is later than the original planned time, the variable time value is equal to the negative value of the absolute value of the difference between the change time and the original planned time; The intelligent control unit outputs the delay time of the downstream process based on the change time value of the current process, forms a new call time for the required material shelf in the downstream process based on the delay time of the downstream process, obtains the time difference between the required material shelf and the new call time, compares it with the shelf call threshold set in the system. If it is less than the shelf call threshold set in the system, the current required material shelf is marked and the shelf reset decision is not executed.

[0037] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An intelligent regulation method for the waiting time of steel pipe processes based on the industrial Internet of Things, characterized in that: The method includes: forming an industrial data combination through a collection device, specifically including process plan data issued by an upper-layer system, material data corresponding to each process, and storage data corresponding to each material data; after preprocessing based on the industrial data combination, constructing a steel pipe transportation execution knowledge base, and forming several groups of underlying data based on the steel pipe transportation execution knowledge base; judging whether to execute the transportation decision of the RGV cart based on several groups of underlying data, and during the execution of the transportation decision of the RGV cart, real-time monitoring whether there are changes in the process plan data issued by the upper-layer system; when there are changes in the process plan data, forming an intelligent control decision for the stereoscopic warehouse shelves based on the material data corresponding to each process and the storage data corresponding to each material data.

2. The intelligent regulation method for the waiting time of steel pipe processes based on the industrial Internet of Things according to claim 1, wherein: The process plan data issued by the upper-layer system includes processing parameters of each process, real-time status data of process supporting equipment, and material application data configured for the process; The storage data corresponding to each material data includes the specific shelf type and shelf number of each material data in the stereoscopic warehouse; 3. The intelligent regulation method for the waiting time of steel pipe processes based on the industrial Internet of Things according to claim 2, wherein: The steel pipe transportation execution knowledge base includes a waiting time knowledge base, upstream and downstream process inbound and outbound, a process time constraint library, and a historical production execution library; The waiting time knowledge base is used to store production equipment status data and logistics equipment status data. The production equipment status data includes the production status of each process, the waiting status of each process, and the waiting duration of each process; the logistics equipment status data includes the RGV cart number, the sending time of the requested RGV cart, the arrival time of the RGV cart, and the waiting duration of the RGV cart; The upstream and downstream process inbound and outbound is used to store the contract number and plan number of upstream and downstream processes, the real-time inbound and outbound quantity under a certain process, and the remaining number of pipe rows; The process time constraint library is used to constrain the production situation, specifically including time constraint and capacity constraint, for determining the maximum waiting duration of the RGV cart and the minimum waiting number of downstream production processes; The historical production execution library is used to store the historical records of upstream and downstream process specification matching, record the equipment parameter configuration cases of different specification pipe rows in each process, form a mapping table between specifications and equipment parameters; mark the waiting duration caused by specification mismatch in each process.

4. The intelligent regulation method for the waiting time of steel pipe processes based on the industrial Internet of Things according to claim 3, wherein: The judging whether to execute the transportation decision of the RGV cart based on several groups of underlying data includes: determining the maximum waiting duration of the RGV cart operation, determining the best time to request the RGV cart based on the maximum waiting duration of the RGV cart operation, and determining whether to execute the transportation decision of the RGV cart, specifically including: Define the completion time of the current process as follows: ； Among them, is the current system time; is the production time of the current process; is the standard production time of single-row pipes, which is the sum of the products of the unit production time and the required quantity of each specification of pipe row required in the current process. constructing a state function of the RGV cart; ； Among them, is the expected departure time of the RGV vehicle; is the remaining transportation time of the RGV vehicle; RGV cart time for applying procedures to build an IoT system Two-way time constraints: ； Among them, is the execution loss duration of the RGV vehicle, specifically including the path travel time and the loading / unloading time. The path travel time is calculated based on the average speed in historical data, and the loading / unloading time is determined based on the average loading / unloading time in historical data; If there exists , determine the transportation decision of the RGV cart and mark its transportation; if there exists , do not execute the transportation decision of the RGV cart; determining the request time of the RGV cart based on the maximum waiting duration of the RGV cart operation under the condition of executing the transportation decision of the RGV cart.

5. The intelligent regulation method for the waiting time of steel pipe processes based on the industrial Internet of Things according to claim 4, characterized in that: The forming of an intelligent control decision for the stereoscopic warehouse shelves based on the material data corresponding to each process and the storage data corresponding to each material data when there are changes in the process plan data includes: The changes in the process plan data include: a fault occurs in the current process, resulting in a delay, and the delay time is recorded; the system actively adjusts, changes the planned time of the next process, and records the difference between the change time and the original planned time; Set the change time value. When a fault occurs in the current process, a delay is generated, and the change time value is equal to the delay time. When the system makes an active adjustment, if the change time is earlier than the original planned time, the change time value is equal to the absolute value of the difference between the change time and the original planned time. If the change time is later than the original planned time, the change time value is equal to the negative of the absolute value of the difference between the change time and the original planned time. Obtain the delay time of the downstream process when there is a change time value in the upstream and downstream processes under historical data, and form a recorded data group , where refers to the change time value that occurs in the upstream process; refers to the delay time of the downstream process; the delay time of the downstream process refers to the difference between the originally scheduled completion time and the actual completion time of the downstream process, taking the absolute value; based on several groups of recorded data groups Form a linear fitting function to construct the functional relationship between the change time value that occurs in the upstream process and the delay time of the downstream process Obtain the material data corresponding to the current process and the next process, as well as the storage data corresponding to each material data. If there is material data corresponding to the current process and the next process under the same shelf, based on the change time value of the current process, output the delay time of the downstream process, form a new call time for the required material shelf in the downstream process based on the delay time of the downstream process, obtain the time difference between the required material shelf and the new call time, and compare it with the shelf call threshold set in the system. If it is less than the shelf call threshold set in the system, mark the currently required material shelf and do not execute the shelf reset decision.

6. An intelligent regulation system for the waiting time of steel pipe processes based on the industrial Internet of Things, characterized in that: The system includes: A collection and processing module, which is used to form an industrial data combination through a collection device, specifically including the process plan data issued by the upper-level system, the material data corresponding to each process, and the storage data corresponding to each material data; A steel pipe transportation execution module, which, after preprocessing based on the industrial data combination, constructs a steel pipe transportation execution knowledge base and forms several groups of underlying data based on the steel pipe transportation execution knowledge base; An RGV trolley decision module, which determines whether to execute the transportation decision of the RGV trolley based on several groups of underlying data, and during the execution of the transportation decision of the RGV trolley, monitors in real time whether there are changes in the process plan data issued by the upper-level system; An intelligent control module, when there are changes in the process plan data, forms an intelligent control decision for the three-dimensional library shelf based on the material data corresponding to each process and the storage data corresponding to each material data.

7. The intelligent regulation system for the waiting time of steel pipe processes based on the industrial Internet of Things according to claim 6, characterized in that: The process plan data issued by the upper-level system includes the processing parameters of each process, the real-time status data of the process supporting equipment, and the material application data configured for the process; The storage data corresponding to each material data includes the specific shelf type and shelf number of each material data in the three-dimensional library.

8. The intelligent regulation system for the waiting time of steel pipe processes based on the industrial Internet of Things according to claim 6, characterized in that: The steel pipe transportation execution knowledge base includes a waiting time knowledge base, upstream and downstream process inbound and outbound, a process time constraint library, and a historical production execution library; The waiting time knowledge base is used to store the production equipment status data and the logistics equipment status data. The production equipment status data includes the production status of each process, the waiting status of each process, and the waiting duration of each process. The logistics equipment status data includes the RGV trolley number, the sending time of the RGV trolley application, the arrival time of the RGV trolley, and the waiting duration of the RGV trolley; The upstream and downstream process inbound and outbound is used to store the upstream and downstream process contract numbers, plan numbers, the real-time inbound and outbound quantity under a certain process, and the remaining pipe row quantity; The process time constraint library is used to constrain the production situation, specifically including time constraint and capacity constraint, and is used to determine the maximum waiting duration of the RGV trolley and the minimum waiting number of the downstream production process; The historical production execution library is used to store the historical records of the specification matching of upstream and downstream processes, record the equipment parameter configuration cases of different specification pipe racks in each process, form a mapping table between specifications and equipment parameters, and mark the waiting duration caused by specification mismatch in each process.

9. The intelligent regulation system for waiting time of steel pipe processes based on industrial Internet of Things according to claim 8, characterized in that: The determination of whether to execute the transportation decision of the RGV cart based on several groups of underlying data includes: Determining the maximum waiting duration of the RGV cart operation, determining the optimal time to request the RGV cart based on the maximum waiting duration of the RGV cart operation, and determining whether to execute the transportation decision of the RGV cart, including: Obtain the production time of the process and the standard production time of the single-row pipe , combined with the current system time , determine the completion time of the current process ; Obtaining the status of the RGV cart in real time; Determine the time for the RGV cart to apply for the process of building the Internet of Things system Two-way time constraints; If there exists , determine the transportation decision of the RGV cart and mark its transportation; if there exists , do not execute the transportation decision of the RGV cart; Among them, is the estimated departure time of the RGV cart; is the execution loss duration of the RGV cart, specifically including the path travel time and the loading and unloading time. The path travel time is calculated based on the average speed under historical data, and the loading and unloading time is determined based on the average loading and unloading time under historical data; Determining the request time of the RGV cart based on the maximum waiting duration of the RGV cart operation under the condition of executing the transportation decision of the RGV cart.

10. The intelligent regulation method for the waiting time of steel pipe processes based on the industrial Internet of Things according to claim 9, characterized in that: The intelligent regulation module includes: A change time analysis unit, which is used to set the change time value. When a failure occurs in the current process and causes a delay, the change time value is equal to the delay time; when the system makes an active adjustment, if the change time is earlier than the original planned time, the change time value is equal to the absolute value of the difference between the change time and the original planned time; if the change time is later than the original planned time, the change time value is equal to the negative value of the absolute value of the difference between the change time and the original planned time. An intelligent regulation unit, which outputs the delay time of the downstream process based on the change time value of the current process, forms a new call time for the required material shelf in the downstream process based on the delay time of the downstream process, obtains the time difference between the required material shelf and the new call time, compares it with the shelf call threshold set in the system, and if it is less than the shelf call threshold set in the system, marks the current required material shelf and does not execute the shelf return decision.

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