Cloud platform-based urgent order scheduling management method, device and equipment

Abstract

The present invention proposes a method, device and equipment for managing rush orders based on a cloud platform, wherein the method comprises the following steps: periodically obtaining order-related information; generating a rush order list based on the order-related information and preset rules; wherein the rush order list includes at least one rush order; determining the weight value of each rush order in the rush order list based on preset calculation rules, wherein the weight value is positively correlated with the urgency of each rush order; wherein the calculation rules for the weight value of each order are pre-set; and sorting the orders in the rush order list based on the calculated weight value. The present invention can automatically identify and judge risky orders and rush orders of the factory, realize order delivery warning management and priority processing, and reduce delays.

Description

Technical Field

[0001] The present invention relates to a method for scheduling urgent orders, and in particular to a method, device and equipment for managing urgent order scheduling based on a cloud platform. Background Art

[0002] Currently, dyeing factories generally use ERP systems to manage order production processes when doing production control. Dyeing process planners will open cards and follow up orders based on customers' product requirements and delivery dates. However, during the peak order season, urgent orders often appear. Urgent orders may include various types of orders such as customer returns, internal return orders, and customer special urgent orders. Urgent orders have a huge impact on the production plan of the dyeing process, which may cause it to be unable to operate normally and cause the delivery of other orders to be delayed. The current main solution is for the planning department to regularly prepare urgent order lists and send them to various department workshops. Each workshop needs to regularly check the current order progress one by one and handle it in a timely manner. However, this processing method is inefficient and will cause the actual production of the workshop to often exceed the order deadline, resulting in chaotic production plans, repeated adjustments to plan allocation, and extremely difficult order management. Summary of the Invention

[0003] In response to the shortcomings of the existing technology, the present invention proposes a cloud platform-based urgent order scheduling management method, device and equipment, which can automatically identify risky orders and urgent orders in the factory, realize order delivery warning management and priority processing, and reduce delays.

[0004] The technical solution of the present invention is achieved as follows:

[0005] The present invention discloses a method for managing urgent order scheduling based on a cloud platform, comprising the following steps:

[0006] Periodically obtain order-related information;

[0007] Generate an urgent order list according to the order-related information and preset rules; wherein the urgent order list includes at least one urgent order;

[0008] Determine the weight value of each urgent order in the urgent order list according to a preset calculation rule, wherein the weight value is positively correlated with the urgency of each urgent order; wherein the calculation rule of the weight value of each order is pre-set;

[0009] Sort the orders in the urgent order list according to the calculated weight values.

[0010] Furthermore, the order-related information includes order batch details; and the step of generating the urgent order list based on the order-related information and preset rules includes:

[0011] Classify the batch numbers corresponding to the order batch details according to preset batch classification rules to obtain the batch types corresponding to each order; wherein the batch types include normal batches, internal repairs, and customer returns for repairs;

[0012] According to preset rules and the batch types corresponding to each order, urgent orders are determined from all orders, and a urgent order list is generated based on the urgent orders.

[0013] Furthermore, the step of performing batch classification on the batch numbers corresponding to the batch details data according to a preset batch classification rule to obtain the batch type corresponding to each order includes:

[0014] Determining whether the batch number contains a first preset character;

[0015] If yes, the batch type marked with the batch number is internal repair;

[0016] Otherwise, determining whether the batch number contains a second preset character;

[0017] If so, the batch type marked with the batch number is customer return repair, otherwise the batch type marked with the batch number is normal batch.

[0018] Furthermore, the step of generating a rush order list based on the order-related information and preset rules includes:

[0019] By setting rules through Boolean operations, when the batch number meets the conditions preset in the corresponding batch type, the order corresponding to the batch number that meets the conditions will be regarded as a privileged order and added to the urgent order list.

[0020] Furthermore, the step of determining the weight value of each urgent order in the urgent order list according to the preset calculation rules specifically includes:

[0021] The weight value of each batch number in the urgent order list is calculated based on the corresponding scores in the predefined options; different batch types correspond to different predefined options.

[0022] Furthermore, the order-related information includes detailed information of the order production process; wherein the step of generating the urgent order list based on the order-related information and preset rules includes:

[0023] Determine the current process of the batch corresponding to the order based on the detailed information of the order production process; the system pre-sets and defines the production rhythm of each order; the production rhythm includes the process type information, production identification information, theoretical retention time and sluggish warning time of each process in the production process of each order;

[0024] Based on the current process of each batch, as well as the actual detention time, theoretical detention time and sluggish warning time of each process in the production process, determine whether the orders corresponding to each batch have overdue warnings, sluggish warnings or delivery overdue. If so, add them to the urgent order list.

[0025] Furthermore, the step of determining whether the orders corresponding to each batch have an overdue warning, a sluggish warning, or a delivery overdue warning based on the current process of each batch, as well as the actual detention time, theoretical detention time, and sluggish warning time of each process in the production process includes:

[0026] Based on the process and actual detention time of the current batch number, combined with the theoretical detention time and sluggish warning time of the unfinished processes of the batch number, determine whether the delivery date exceeds the preset delivery date. If so, an overdue warning is issued;

[0027] Determine whether the actual detention time in each process of the current batch number is greater than the stagnation warning time of the corresponding process. If so, a stagnation warning is issued;

[0028] Determine whether the batch number has exceeded the preset delivery date based on the process the batch number is in and the current time. If so, there is a delivery overdue.

[0029] Furthermore, the step of determining the weight value of each urgent order in the urgent order list according to the preset calculation rules includes:

[0030] Predefine the scores for each option in overdue warning, slow-moving warning, and delivery overdue;

[0031] The weight value of each batch number is determined based on the scores of the pre-defined options in overdue warning, slow-moving warning and delivery overdue.

[0032] On the other hand, the present invention also discloses a cloud platform-based urgent order scheduling management device, comprising:

[0033] Order information acquisition module, used to periodically obtain order-related information;

[0034] Urgent order list determination module, used to determine the urgent order list based on order-related information and preset rules;

[0035] A weight value determination module is used to determine the weight value of each urgent order in the urgent order list according to a preset calculation rule, wherein the weight value is positively correlated with the urgency of each urgent order; wherein the calculation rule of the weight value of each order is pre-set;

[0036] The scheduling determination module is used to sort the orders in the urgent order list according to the calculated weight values.

[0037] On the other hand, the present invention also discloses a cloud platform-based urgent order scheduling management device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above-mentioned cloud platform-based urgent order scheduling management method.

[0038] Compared with the existing technology, the present invention has the following advantages: the present invention periodically obtains order-related information from the ERP platform, and first determines the urgent order list based on the order-related information and preset rules, and then determines the weight value of each urgent order in the urgent order list based on the preset calculation rules, and finally sorts the orders in the urgent order list according to the size of the weight value, thereby realizing automatic judgment and identification of risky orders and urgent orders in the factory, realizing order delivery warning management and priority processing, and reducing delays. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1 An optional application environment diagram for inventing a cloud platform-based urgent order scheduling management device;

[0041] Figure 2 This is a flow chart of an embodiment of a method for managing urgent order scheduling based on a cloud platform according to the present invention;

[0042] Figure 3 This is a schematic diagram of order batch detailed data obtained in one embodiment;

[0043] Figure 4 A schematic diagram of pre-defining the types of each batch in one embodiment;

[0044] Figure 5 This is a schematic diagram of batch classification of batch detailed data acquired in one embodiment;

[0045] Figure 6 This is an interface diagram that meets the urgent order conditions in one embodiment;

[0046] Figure 7 This is a diagram of the urgent order configuration interface in one embodiment;

[0047] Figure 8This is a flow chart of another embodiment of the urgent order scheduling management method based on the cloud platform of the present invention;

[0048] Figure 9 A schematic diagram of production rhythm setting in one embodiment;

[0049] Figure 10 This is a system block diagram of the cloud platform-based urgent order scheduling management device of the present invention;

[0050] Figure 11 This is a system block diagram of the urgent order scheduling management device based on the cloud platform of the present invention. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solutions and advantages of the present invention clearer, specific embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all of the contents, are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0052] The urgent order scheduling management method based on the cloud platform provided in the embodiment of the present application is executed by a server, and the urgent order scheduling management device based on the cloud platform can be implemented by software and / or hardware. The urgent order scheduling management device based on the cloud platform can be composed of two or more physical entities, or it can be composed of one physical entity. For example, the urgent order scheduling management device based on the cloud platform is a device with strong computing power such as a server. For ease of understanding, this embodiment is described as an example of the server-side being the subject of the urgent order scheduling management method based on the cloud platform.

[0053] like Figure 1 As shown, Figure 1 An optional application environment diagram of a cloud platform-based urgent order scheduling management system provided by an embodiment of the present invention, including a client 2000 and a server 1000;

[0054] The client 2000 is an electronic device with communication and business processing functions. The client 2000 can be a PC, such as a desktop computer, or a mobile terminal, such as a mobile phone, laptop, tablet computer, PDA, etc. In one embodiment, the client 2000 is a device that receives urgent order scheduling notifications sent by the server 1000, such as a mobile phone installed with an application (APP), WeChat official account, or WeChat mini-program that receives information from the server 1000. There can be one or more clients 2000.

[0055] The client 2000 includes a processor 2100, a memory 2200, an interface device 2300, a communication device 2400, a display device 2500, an input device 2600, an output device 2700, and a camera device 2800. The processor 2100 may be a central processing unit (CPU), a microprocessor (MCU), or the like. The memory 2200 may include, for example, ROM (read-only memory), RAM (random access memory), or a non-volatile memory such as a hard disk. The interface device 2300 may include, for example, a USB port, a headphone jack, or a serial port. The communication device 2400 may be capable of wired or wireless communication. The display device 2500 may be, for example, an LCD display or a touchscreen display. The input device 2600 may include, for example, a touchscreen, a keyboard, or a microphone. The output device 2700 is used to output information and may, for example, be a speaker for outputting voice messages to the user. The camera device is used to capture information and may, for example, be a camera.

[0056] The server 1000 provides a business point for processing, database, and communication facilities. The server 1000 can be a monolithic server or a distributed server across multiple computers or computer data centers. The server 1000 can be of various types, such as but not limited to a web server, a news server, a mail server, a message server, an advertising server, a file server, an application server, an interactive server, a database server, or a proxy server. In some embodiments, each server can include hardware, software, or an embedded logic component or a combination of two or more such components for executing the appropriate functions supported or implemented by the server. For example, the server can be a blade server, a cloud server, etc., or can be a server group (1000-1) consisting of multiple servers, which can include one or more of the above-mentioned types of servers, etc.

[0057] The server 1000 may include a processor 1100 , a memory 1200 , an interface device 1300 , a communication device 1400 , a display device 1500 , and an input device 1600 .

[0058] like Figure 2 As shown, Figure 2This is a flow chart of an embodiment of a method for managing urgent order scheduling based on a cloud platform. In this embodiment, the method for managing urgent order scheduling based on a cloud platform includes the following steps:

[0059] Step 1: Periodically obtain order-related information from the ERP platform;

[0060] Among them, the ERP platform refers to an enterprise information management system that integrates material, financial, and information resources for the manufacturing industry; it includes placing sales orders, formulating rolling pre-plans, etc. Rolling pre-plans include material requirement plans, commissioned processing plans, and production plans. The ERP platform can divide orders into multiple batches, each of which includes batch information and order delivery dates, forming a batch number ID. In this embodiment, order-related information includes order batch details. For better explanation, Figure 3 A schematic diagram of order batch detail data obtained in one embodiment is provided.

[0061] Step 2: Generate a rush order list based on the order-related information and preset rules; wherein the rush order list includes at least one rush order;

[0062] Among them, order-related information includes order batch details, such as batch number, batch type, etc. At the same time, one or more screening rules are pre-set on the ERP platform, and only orders that meet the pre-set screening rules will be included in the urgent order list for urgent order scheduling management. In this embodiment, the urgent order list is generated based on the order batch details and one or more pre-set screening rules on the ERP platform; for example, when urgent order scheduling management is performed on batch numbers belonging to the same order, the relevant information of each batch number can be used to determine whether each batch number belongs to the same order, thereby generating an urgent order list that meets the requirements.

[0063] In one embodiment, specifically, step 2 includes the following sub-steps:

[0064] Step 201: classify the batch numbers corresponding to the order batch details according to a preset batch classification rule to obtain the batch type corresponding to each order; wherein the batch type includes normal batch, internal repair, and customer return repair;

[0065] Step 202: Determine urgent orders from all orders according to preset rules and the batch types corresponding to each order, and generate an urgent order list based on the urgent orders.

[0066] In step 201, the types of each batch have been pre-defined on the ERP platform. For example, if the batch number contains A, B, or C, it is an internal repair. Figure 4Therefore, according to the relevant information of the batch number and the predefined rules, the batch number corresponding to the batch detail data can be classified into batches to obtain the batch type corresponding to each order. Figure 5 A schematic diagram of batch classification of batch detailed data acquired in one embodiment is provided.

[0067] Specifically, in step 201, the batch number corresponding to the order batch details data is batch classified according to a preset batch classification rule to obtain the batch type corresponding to each order, including:

[0068] Determining whether the batch number contains a first preset character;

[0069] If yes, the batch type marked with the batch number is internal repair;

[0070] Otherwise, determining whether the batch number contains a second preset character;

[0071] If so, the batch type marked with the batch number is customer return repair, otherwise the batch type marked with the batch number is normal batch.

[0072] For example, the first preset character is preset as A, B, and C in the system, and the second preset character is preset as H; if it is determined that the batch number contains A, B, or C, the category of the batch number is marked as internal repair; if it is determined that the batch number contains H, the category of the batch number is marked as customer return repair; if it is determined that the batch number does not contain A, B, C and H, the category of the batch number is marked as normal batch.

[0073] In step 202, after the batch classification is determined, a list of urgent orders, i.e., privileged orders or orders requiring expedited processing, needs to be determined from the batch details. In this embodiment, the step of determining the urgent order list from the classified batch numbers according to pre-set rules includes:

[0074] Rules are set through Boolean operations. When the batch number meets the preset conditions in the corresponding batch type, the order corresponding to the batch number that meets the conditions will be regarded as a privileged order and added to the urgent order list; for example: the color number contains TC177138 or the grey cloth number contains 01839, 02283, 02098, the batch number that meets these conditions will be regarded as a privileged order and added to the urgent order list.

[0075] Step 3: Determine the weight of each urgent order in the urgent order list according to a preset calculation rule, wherein the weight is positively correlated with the urgency of each urgent order; wherein the calculation rule for the weight of each order is preset;

[0076] In this embodiment, the ERP platform also pre-sets weight calculation rules for each type of order. These weight calculation rules are used to calculate the weight of each urgent order in each urgent order list. The weight calculation rules for orders of the same type are the same. For example, if both batches are under internal repair, their weight calculation rules are the same.

[0077] In one embodiment, in step 3, after determining the urgent order list, the weight value of each order in the urgent order list is determined according to a preset weight value calculation rule, specifically including:

[0078] The weight value of each batch number in the urgent order list is calculated based on the corresponding scores in the predefined options; different batch types correspond to different predefined options.

[0079] For example, Figure 6 and Figure 7 As shown in the figure, the urgency weights set for the urgent order tags are: Customer Reminder = 40, Return Repair = 60, Customer Return = 100, and Privileged Order = 30. Batch A is marked as Customer Reminder and Return Repair; Batch B is marked as Return Repair; and Batch C is marked as Privileged Order and Return Repair. Based on the above conditions, the urgency weights for the following corresponding batches are as follows:

[0080] Batch A = 40 + 100 = 140;

[0081] Batch B = 60;

[0082] Batch C = 60 + 30 = 90;

[0083] Final ranking = Batch A > Batch C > Batch B.

[0084] Step 4: Sort the orders in the urgent order list according to the calculated weight values.

[0085] In this embodiment, the orders or batch numbers in the urgent order list are finally sorted according to the calculated weight value. Since the weight value is positively correlated with the urgency of the order, this sorting also represents an urgency sorting of each order.

[0086] To summarize, this embodiment obtains order batch detail data, and batch-classifies the order batch detail data according to the order batch detail data and preset batch classification rules; then determines the urgent order list from the classified batch numbers according to the pre-set rules in each batch classification, and then determines the weight value of each urgent order in the urgent order list according to the pre-calculated rules, and finally determines the urgent order schedule according to the weight value, so that workers can see it at a glance, thereby realizing automatic judgment and identification of risky orders and urgent orders in the factory, realizing order delivery warning management and priority processing, and reducing delays.

[0087] This embodiment can sort the batches according to the priority of each batch by selecting the type in the batch, which is simple and clear.

[0088] See also Figure 8 Another embodiment of the present invention further discloses a method for managing urgent order scheduling based on a cloud platform, comprising the following steps:

[0089] Step 1a: Periodically obtain detailed information about the order production process from the ERP platform;

[0090] Similarly, an ERP platform refers to an enterprise information management system for the manufacturing industry that integrates and manages material, financial, and information resources. This includes placing sales orders and developing rolling budget plans. Rolling budget plans include material requirements planning, contract processing planning, and production planning. The ERP platform can divide orders into multiple batches, each of which includes batch information and order delivery dates, forming a batch ID. In this embodiment, order-related information includes detailed information about the order production process.

[0091] Step 2a: Generate a rush order list based on the order production process details and preset rules; wherein the rush order list includes at least one rush order;

[0092] In this embodiment, similarly, one or more screening rules are pre-set on the ERP platform; only orders that meet the preset screening rules will be included in the urgent order list for urgent order scheduling management; in addition, order-related information includes detailed information on the order production process. It can be seen that the order information, batch information, etc. of each batch number id can be known based on the order-related information. In this embodiment, the urgent order list is generated based on the order-related information and one or more screening rules pre-set on the ERP platform; for example, when urgent order scheduling management is performed on batch numbers that belong to the same order and have the risk of overdue delivery, it can be known whether each batch number belongs to the same order based on the relevant information of each batch number, and then the batch numbers with the risk of overdue delivery are screened out from these orders, thereby generating an urgent order list that meets the requirements.

[0093] In one embodiment, specifically, step 2a includes the following sub-steps:

[0094] Step 201a, based on the detailed information of the order production process, determine the current process of the batch corresponding to the order; wherein, the system pre-sets and defines the production rhythm of each order; the production rhythm includes the process type information, production identification information, theoretical retention time and sluggish warning time of each process in the production process of each order. The setting of the production rhythm refers to setting the area, department, theoretical retention time, sluggish warning time and production status for the key processes of the factory. For details, please refer to Figure 9 The interface diagram of production rhythm settings.

[0095] During actual production, when the planning department receives an order, that is, when it receives the order voucher from the factory's customer, the planning department will split the order into multiple batches based on the order quantity and the factory's actual production situation (such as the production volume of each production line), and put them into production one by one; and for each batch under the same order, the production rhythm is set to be consistent, such as distributing->dyeing->setting->warehousing->shipping; and for each step of the process, the ERP platform is pre-set with the process type information, production identification information, theoretical retention time and stagnation warning time of each process, and the time the batch number reaches a certain process and stays in the process is recorded on the ERP platform, or marked on the batch number; therefore, in this embodiment, the process in which the batch number corresponding to the order is currently located can be determined based on the detailed information of the order production process of each batch number.

[0096] Step 202a, based on the current process of each batch, as well as the actual detention time, theoretical detention time and stagnation warning time of each process in the production process, determine whether the orders corresponding to each batch have overdue warnings, stagnation warnings or delivery overdues, and if so, add them to the urgent order list.

[0097] In this embodiment, the current process of the batch number corresponding to the order can be determined based on the detailed information of the order production process of each batch number, and then the actual detention time of each process of the batch number is calculated and compared with the actual detention time, theoretical detention time and stagnation warning time of the process pre-set on the ERP platform, so as to determine whether the orders corresponding to each batch have overdue warnings, stagnation warnings or delivery overdue, so as to generate a list of urgent orders.

[0098] Specifically, step 202a includes:

[0099] Based on the process and actual detention time of the current batch number, combined with the theoretical detention time and sluggish warning time of the unfinished processes of the batch number, determine whether the delivery date exceeds the preset delivery date. If so, an overdue warning is issued;

[0100] Check whether the actual detention time in each process of the current batch number is greater than the stagnation warning time of the corresponding process. If so, a stagnation warning is issued.

[0101] Determine whether the batch number has exceeded the preset delivery date based on the process the batch number is in and the current time. If so, there is a delivery overdue.

[0102] For details, please refer to Figure 9 And an example provided in the following table:

[0103]

[0104] In one of the batches, the preset production cycle corresponding to the batch is shown in the table above. Assuming that the order date of the batch number (DP220401010) is April 1, 2022, 10:00:00, and the preset delivery date is April 3, 2022, then:

[0105] Assuming that the current time is 18:00:00 on April 2, 2022, it is determined that the process of the batch number stays in the dyeing cycle. The theoretical retention time of the subsequent processes is added together to calculate whether it exceeds the delivery date. If the theoretical retention time exceeds the delivery date after adding together, the batch number is marked as "overdue warning".

[0106] The calculation starts from the time when the process flows to the dyeing cycle to determine the cumulative residence time of the current process. If the cumulative residence time of the batch number in the current process exceeds 50 hours, that is, it is greater than the stagnation warning time in the dyeing cycle (50 hours), then the batch number will be marked as a "stagnation warning" icon.

[0107] If the current time is April 4, 2022, and the batch number is still in a certain cycle process in the above table; it can be seen that the batch number has exceeded the preset delivery date (April 3, 2022), so the batch number will be marked as "delivery overdue".

[0108] In step 3, the weight value of each urgent order in the urgent order list is determined according to a preset calculation rule, wherein the weight value is positively correlated with the urgency of each urgent order; wherein the calculation rule of the weight value of each order is preset;

[0109] In this embodiment, similarly, the ERP platform pre-sets the weight value calculation rules for each type of order, and the weight value of each urgent order in each urgent order list can be calculated based on the weight value calculation rules for each type of order.

[0110] In one embodiment, in step 3, after determining the urgent order list, the step of determining the weight value of each order in the urgent order list according to a preset weight value calculation rule specifically includes:

[0111] Step 301: pre-define the scores for each of the following options: overdue warning, sluggish warning, and delivery overdue;

[0112] Step 302: Determine the weight value of each batch number based on the scores of each predefined option in overdue warning, slow-moving warning and delivery overdue.

[0113] Step 4: Sort the orders in the urgent order list according to the calculated weight values.

[0114] In this embodiment, the orders in the urgent order list are finally sorted according to the calculated weight value. Since the weight value is positively correlated with the urgency of the order, this sorting also represents an urgency sorting of each order, allowing workers to adjust batches according to the schedule to avoid delays in the construction period.

[0115] For example, Figure 7 As shown, it is assumed that the scores for each of the overdue warning, obsolete warning, and delivery overdue options are pre-set on the ERP platform's urgent order label: delivery overdue = 20, overdue warning = 10, and obsolete warning = 10. In one embodiment, batch a is marked with overdue warning and obsolete warning, batch b is marked with delivery overdue and obsolete warning, and batch c is marked with overdue warning. Batches a, b, and c all belong to the same order. Based on the above conditions, the urgency weights of the corresponding batches are as follows:

[0116] Batch a = 10 + 10 = 20;

[0117] Batch b = 20 + 10 = 30;

[0118] batch c = 10;

[0119] Final ranking = batch b > batch a > batch c.

[0120] In addition, since the priorities of different order types are different, the scores corresponding to each batch type can be added to the pre-defined scores for each option in the overdue warning, stale warning, and delivery overdue. For example, assuming that the scores for each option in the urgent order label on the ERP platform are pre-set as follows: delivery overdue = 20, overdue warning = 10, stale warning = 10; in addition, the scores corresponding to the batch types are pre-set as follows: urgent order = 100, customer return = 30, repair order = 20, customer reminder = 20; in one embodiment, batch a is marked as overdue warning, stale warning, and customer return, batch b is marked as delivery overdue, stale warning, and urgent order, and batch c is marked as overdue warning, customer return, and customer reminder. Based on the above conditions, the urgency weights of the following corresponding batches are as follows:

[0121] Batch aa = 10 + 10 + 30 = 50;

[0122] Batch bb = 20 + 10 + 100 = 130;

[0123] Batch cc = 10 + 30 + 20 = 60;

[0124] Final sorting = batch bb > batch cc > batch aa.

[0125] In this embodiment, detailed information on the order production process is obtained, and the current process of the batch corresponding to the order is determined based on the detailed information on the order production process, wherein the production rhythm of each order is pre-defined in the system; then, based on the process of each batch, as well as the actual detention time, theoretical detention time and sluggish warning time of each process in the production process, it is determined whether each batch has an overdue warning, sluggish warning or delivery overdue, and a list of urgent orders is determined. Then, the weight value of each urgent order in the urgent order list is determined according to the pre-calculated rules, and finally the urgent order scheduling is determined according to the weight value, so that workers can see it at a glance, thereby realizing automatic judgment and identification of risky orders and urgent orders in the factory, realizing order delivery warning management and priority processing, and reducing delays.

[0126] This embodiment can compare the actual consumption time of each process in the production process with the theoretical time to determine whether there is a process delay, so as to dynamically adjust the batch sorting, thereby realizing order delivery warning management and priority processing, and reducing delays.

[0127] On the other hand, see Figure 10 The embodiment of the present invention further discloses a cloud platform-based urgent order scheduling management device, comprising:

[0128] The order information acquisition module is used to periodically obtain order-related information from the ERP platform;

[0129] Urgent order list determination module, used to determine the urgent order list based on order-related information and preset rules;

[0130] A weight value determination module is used to determine the weight value of each urgent order in the urgent order list according to a preset calculation rule, wherein the weight value is positively correlated with the urgency of each urgent order; wherein the calculation rule of the weight value of each order is pre-set;

[0131] The scheduling determination module is used to sort the orders in the urgent order list according to the calculated weight values.

[0132] In this embodiment, the cloud-based urgent order scheduling management method uses the cloud-based urgent order scheduling management device as the execution object of the steps. Specifically, step 1 uses the order information acquisition module as the execution object, step 2 uses the urgent order list determination module as the execution object, step 3 uses the weight value determination module as the execution object, and step 4 uses the schedule determination module as the execution object.

[0133] In this embodiment, the order information acquisition module periodically obtains order-related information from the ERP platform, and the urgent order list determination module first determines the urgent order list based on the order-related information and preset rules, and then the weight value determination module determines the weight value of each urgent order in the urgent order list based on the preset rules. Finally, the scheduling determination module sorts the urgent order list according to the size of the weight value, thereby realizing automatic judgment and identification of risky orders and urgent orders in the factory, realizing order delivery warning management and priority processing, and reducing delays.

[0134] On the other hand, Figure 11 As shown, an embodiment of the present invention also discloses a cloud platform-based urgent order scheduling management device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above-mentioned cloud platform-based urgent order scheduling management method.

[0135] In summary, the present invention periodically obtains order-related information from the ERP platform, and first determines the urgent order list based on the order-related information and preset rules, and then determines the weight value of each urgent order in the urgent order list based on the preset rules, and finally sorts the urgent order list according to the size of the weight value, thereby realizing automatic judgment and identification of risky orders and urgent orders in the factory, realizing order delivery warning management and priority processing, and reducing delays.

[0136] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for managing urgent order scheduling based on a cloud platform, characterized in that: The following steps are involved: Periodically obtain order-related information; Generate an urgent order list based on the order-related information and preset rules; wherein the urgent order list includes at least one urgent order, and the order-related information includes order batch details; Determine the weight value of each urgent order in the urgent order list according to a preset calculation rule, wherein the weight value is positively correlated with the urgency of each urgent order; wherein the calculation rule of the weight value of each order is pre-set; Sort the orders in the urgent order list according to the calculated weight values; The step of generating a rush order list based on the order-related information and preset rules includes: Classify the batch numbers corresponding to the order batch details according to preset batch classification rules to obtain the batch types corresponding to each order; wherein the batch types include normal batches, internal repairs, and customer returns for repairs; By setting rules through Boolean operations, when the batch number meets the preset conditions of the corresponding batch type, the order corresponding to the batch number that meets the conditions will be regarded as a privileged order and added to the urgent order list; The step of classifying the batch numbers corresponding to the batch details data according to a preset batch classification rule to obtain the batch types corresponding to each order includes: Determining whether the batch number contains a first preset character; If yes, the batch type marked with the batch number is internal repair; Otherwise, determining whether the batch number contains a second preset character; If yes, the batch type marked with the batch number is customer return repair, otherwise the batch type marked with the batch number is normal batch; In addition, the step of determining the weight value of each urgent order in the urgent order list according to the preset calculation rules specifically includes: The weight value of each batch number in the urgent order list is calculated based on the corresponding scores in the predefined options; different batch types correspond to different predefined options.

2. The cloud platform-based urgent order scheduling management method according to claim 1 is characterized in that: The order-related information includes detailed information about the order production process; wherein the step of generating a rush order list based on the order-related information and preset rules includes: Determine the current process of the batch corresponding to the order based on the detailed information of the order production process; the system pre-sets and defines the production rhythm of each order; the production rhythm includes the process type information, production identification information, theoretical retention time and sluggish warning time of each process in the production process of each order; Based on the current process of each batch, as well as the actual detention time, theoretical detention time and sluggish warning time of each process in the production process, determine whether the orders corresponding to each batch have overdue warnings, sluggish warnings or delivery overdue. If so, add them to the urgent order list.

3. The cloud platform-based urgent order scheduling management method according to claim 2 is characterized in that: The step of determining whether there is an overdue warning, a sluggish warning, or a delivery overdue for an order corresponding to each batch based on the current process of each batch, as well as the actual detention time, theoretical detention time, and sluggish warning time of each process in the production process includes: Based on the process and actual detention time of the current batch number, combined with the theoretical detention time and sluggish warning time of the unfinished processes of the batch number, determine whether the delivery date exceeds the preset delivery date. If so, an overdue warning is issued; Determine whether the actual detention time in each process of the current batch number is greater than the stagnation warning time of the corresponding process. If so, a stagnation warning is issued; Determine whether the batch number has exceeded the preset delivery date based on the process the batch number is in and the current time. If so, there is a delivery overdue.

4. The cloud platform-based urgent order scheduling management method according to claim 3 is characterized in that: The step of determining the weight value of each urgent order in the urgent order list according to the preset calculation rules includes: Predefine the scores for each option in overdue warning, slow-moving warning, and delivery overdue; The weight value of each batch number is determined based on the scores of the pre-defined options in overdue warning, slow-moving warning and delivery overdue.

5. A cloud-based urgent order scheduling management device, characterized in that: include: Order information acquisition module, used to periodically obtain order-related information; Urgent order list determination module, used to determine the urgent order list based on order-related information and preset rules; A weight value determination module is used to determine the weight value of each urgent order in the urgent order list according to a preset calculation rule, wherein the weight value is positively correlated with the urgency of each urgent order; wherein the calculation rule of the weight value of each order is pre-set; The scheduling determination module is used to sort the orders in the urgent order list according to the calculated weight values.

6. A cloud-based urgent order scheduling management device, characterized in that: include: at least one processor; And, a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the cloud platform-based urgent order scheduling management method as described in any one of claims 1-4.

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