Delivery time delay early warning device and method

Abstract

The invention discloses a delivery time delay early warning device and method. The apparatus inputs order information corresponding to a target product to a prediction model to determine a time point corresponding to a risk threshold. The apparatus calculates a first time interval based on the time point, where the first time interval is composed of a time interval from an initial delivery time point to the time point. The apparatus calculates an estimated delivery volume corresponding to the order information based on a completed quantity corresponding to the first time interval. The device determines whether to generate a delivery delay warning signal based on the completed quantity and the estimated delivery quantity. The delivery delay early warning technology provided by the invention can solve the problem of delivery delay of the original supplier, and reduces the risk that the target product cannot be completed as required.

Description

Technical Field

[0001] The present disclosure relates to a delivery delay warning device and method. Specifically, the present invention relates to a delivery delay warning device and method that can provide an early warning for a delivery deadline. Background Art

[0002] In general dyeing and finishing processes, corporate customers in the textile industry will place different orders for the processing specifications required for different textile products, and require the suppliers responsible for shipment in the supply chain to complete the shipment within a deadline.

[0003] However, in the prior art, since there are many suppliers corresponding to an order and the processing specifications are complex (for example, dyeing and finishing methods such as embryo setting, shaping, and dyeing), it is difficult for managers to manage the delivery status of orders, and there is a lack of an early warning mechanism for analyzing and evaluating the delivery status of suppliers.

[0004] In view of this, how to provide a delivery delay warning technology that can provide early warning of the delivery deadline is a goal that the industry urgently needs to work on. Summary of the invention

[0005] The present invention provides a delivery delay warning device, comprising a transceiver interface, a memory and a processor; the memory is used to store a prediction model, wherein the prediction model corresponds to a first supplier, and the prediction model is generated by multiple historical cooperation records corresponding to the first supplier; the processor is electrically connected to the transceiver interface and the memory, and is used to perform the following operations: inputting an order information corresponding to a target product into the prediction model to determine a time point corresponding to a risk threshold; based on the time point, calculating a first time interval, wherein the first time interval is composed of a time interval from an initial delivery time point to the time point; based on a completed quantity corresponding to the first time interval, calculating an estimated delivery quantity corresponding to the order information; and based on the completed quantity and the estimated delivery quantity, determining whether to generate a delivery delay warning signal.

[0006] In one embodiment of the present invention, determining the time point corresponding to the risk threshold further includes the following operations: inputting the order information corresponding to the target product into the prediction model to generate a predicted delay result corresponding to the target product; and determining the time point corresponding to the risk threshold based on the predicted delay result and the risk threshold.

[0007] In one embodiment of the present invention, the order information includes a target quantity and a processing specification corresponding to the target product.

[0008] In one embodiment of the present invention, the delivery delay warning signal is used to indicate that the first supplier is unable to complete the target quantity of the target product in the order information within an order period corresponding to the order information.

[0009] In one embodiment of the present invention, the calculation of the estimated delivery quantity corresponding to the order information also includes the following operations: calculating an average daily delivery quantity based on the first time interval and a completed quantity corresponding to the first time interval; and calculating the estimated delivery quantity corresponding to the order information based on the average daily delivery quantity and a second time interval, wherein the second time interval is composed of the time interval from the time point to a last delivery time point of the order information.

[0010] In one embodiment of the present invention, the prediction model is generated by the following operations: receiving the multiple historical cooperation records corresponding to the first supplier, wherein each of the multiple historical cooperation records includes a historical order information and a historical delivery time; inputting the multiple historical cooperation records into an initial prediction model to train the initial prediction model; and setting the trained initial prediction model as the prediction model.

[0011] In one embodiment of the present invention, the processor further performs the following operation: adding the order information and an actual delivery time corresponding to the first supplier to the multiple historical cooperation records to update the prediction model.

[0012] In one embodiment of the present invention, the processor further performs the following operations: in response to generating the delivery delay warning signal, based on a processing specification included in the order information, selecting multiple alternative suppliers from multiple suppliers, wherein the multiple alternative suppliers have multiple historical cooperation records corresponding to the processing specification; and selecting at least one second supplier from the multiple alternative suppliers based on the multiple historical cooperation records of the multiple alternative suppliers corresponding to the processing specification.

[0013] In one embodiment of the present invention, selecting the at least one second supplier from the multiple alternative suppliers further includes the following operations: calculating a unit average processing days for each of the multiple alternative suppliers corresponding to the processing specifications based on the multiple historical cooperation records of the multiple alternative suppliers corresponding to the processing specifications; and selecting the at least one second supplier based on the unit average processing days corresponding to each of the multiple alternative suppliers.

[0014] The present invention provides a delivery delay warning method for an electronic device, wherein the delivery delay warning method includes the following steps: inputting order information corresponding to a target product into a prediction model to determine a time point corresponding to a risk threshold, wherein the prediction model corresponds to a first supplier, and the prediction model is generated by multiple historical cooperation records corresponding to the first supplier; based on the time point, calculating a first time interval, wherein the first time interval is composed of a time interval from an initial delivery time point to the time point; based on a completed quantity corresponding to the first time interval, calculating an estimated delivery quantity corresponding to the order information; and based on the completed quantity and the estimated delivery quantity, determining whether to generate a delivery delay warning signal.

[0015] The delivery delay warning technology provided by the present invention can estimate the daily delivery volume of the target product with specific processing specifications. Compared with the prior art, the present invention combines the supplier's historical records and machine learning algorithms to estimate the production volume of the target product, which can further improve the accuracy of delivery prediction. In addition, based on the learning results of the model, the present invention can select an alternative supplier when it is determined that the supplier has a delivery delay, so as to solve the delivery delay problem of the original supplier and reduce the risk of the target product not being completed on time.

[0016] The detailed technology and implementation methods of the present invention are described below in conjunction with the accompanying drawings so that a person having ordinary knowledge in the technical field to which the present invention belongs can understand the technical features of the invention for which protection is sought. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to make the above and other objects, features and implementation methods of the present disclosure more clearly understood, the attached drawings are described as follows:

[0018] Figure 1 A schematic diagram of a delivery delay warning device according to some embodiments of the present disclosure is shown;

[0019] Figure 2 A schematic diagram illustrating a predicted delay result according to some embodiments of the present disclosure; and

[0020] Figure 3 A flow chart of a delivery delay warning method in some embodiments of the present disclosure is shown.

[0021]

Explanation of symbols

[0022] 100: Delivery delay warning device

[0023] 110: Transceiver interface

[0024] 120: Memory

[0025] M: Prediction Model

[0026] 130: Processor

[0027] T: Risk level

[0028] 200: Predicted delay results

[0029] P: Intersection point

[0030] S1: Prediction curve

[0031] S310, S320, S330, S340: Steps DETAILED DESCRIPTION

[0032] The following disclosure provides many different embodiments or examples for implementing different features of the present disclosure. The components and configurations in the specific examples are used to simplify the present disclosure in the following discussion. Any examples discussed are used for illustrative purposes only and do not limit the scope and significance of the present disclosure or its examples in any way. Where appropriate, the same reference numerals are used between the drawings and in the corresponding text descriptions to represent the same or similar components.

[0033] The first embodiment of the present invention is a delivery delay warning device 100. Figure 1 , which illustrates a schematic diagram of a delivery delay warning device 100 according to some embodiments of the present disclosure. Figure 1 As shown, the delivery delay warning device 100 includes a transceiver interface 110, a memory 120 and a processor 130, and the processor 130 is electrically connected to the transceiver interface 110 and the memory 120. The delivery delay warning device 100 can be used by an enterprise customer to remind and warn of possible delivery delays of products when the enterprise customer entrusts a supplier to process.

[0034] It should be noted that the transceiver interface 110 is an interface that can receive and transmit data. The storage 120 can be a memory, a USB disk, a hard disk, an optical disk, a flash drive, or any other storage medium or circuit known to a person skilled in the art and having the same function. The processor 130 can be various processing units, a central processing unit (CPU), a microprocessor, or other computing devices known to a person skilled in the art, but the present invention is not limited thereto.

[0035] In this embodiment, the memory 120 is used to store a prediction model M. For example, the prediction model M corresponds to a first supplier (eg, a fabric supplier), and the prediction model M is generated from a plurality of historical cooperation records corresponding to the first supplier.

[0036] In some embodiments, the prediction model M is a prediction model corresponding to a supplier's product for a certain processing specification, and the prediction model M is generated by multiple historical cooperation records corresponding to the supplier for the processing specification (for example: historical cooperation records with the supplier in the past three years).

[0037] In some embodiments, the processor 130 of the delivery delay warning device 100 may generate the prediction model M and the initial prediction model for predicting the model M by using a variety of machine learning models and related algorithms. For example, the processor 130 may use multi-task logistic regression (MTLR) and neural MTLR model, but the present invention is not limited thereto.

[0038] In some embodiments, the prediction model M is generated by the following operation: the processor 130 receives the plurality of historical cooperation records corresponding to the first supplier (e.g., historical cooperation records with the supplier in the past three years), wherein each of the plurality of historical cooperation records includes a historical order information and a historical delivery time. Then, the processor 130 inputs the plurality of historical cooperation records into an initial prediction model to train the initial prediction model. Then, the processor 130 sets the trained initial prediction model as the prediction model M.

[0039] In some embodiments, the present invention may include multiple prediction models. The processor 130 inputs the multiple historical cooperation records into multiple initial prediction models to train the multiple initial prediction models. Then, the processor 130 sets the multiple initial prediction models that have been trained as the multiple prediction models.

[0040] It should be noted that the multiple prediction models of the present invention can correspond to different processing specifications of different suppliers and predict their supply quantities. For ease of explanation, the present invention will be described with a single prediction model M. Those with ordinary knowledge in the art should be able to understand the operation of the present invention including multiple prediction models from the following content, so it is not repeated.

[0041] In addition, it should be noted that the prediction model M can be generated by the delivery delay warning device 100 through self-training, or the delivery delay warning device 100 can directly receive a trained prediction model from an external device as the prediction model in this case. Figure 1 The prediction model M, but the present invention is not limited to this.

[0042] In this embodiment, the processor 130 inputs order information corresponding to a target product into the prediction model to determine a time point corresponding to a risk threshold.

[0043] In some embodiments, the order information includes a target quantity and a processing specification corresponding to the target product. For example, the order information may correspond to a sweater product (ie, the target product) with a quantity of 1,000 pieces (ie, the target quantity) and dyeing processing (ie, the processing specification).

[0044] It should be noted that the target product can be any one of the textile process products in the conventional technology (for example: tops, pants, hats, etc.), and the processing specifications can be the continuous processes used in the conventional technology for further processing on these textile process products (for example: dyeing, embryo setting, printing, dyeing, shaping, sanding, repairing, shrinkage prevention or a combination thereof, etc.), but the present invention is not limited to this.

[0045] In some embodiments, the processor 130 inputs the order information corresponding to the target product into the prediction model to generate a predicted delay result corresponding to the target product. Then, the processor 130 determines the time point corresponding to the risk threshold based on the predicted delay result and a risk threshold.

[0046] In some embodiments, the processor 130 may set the risk threshold, which may be 25% to 75% (e.g., 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%) to determine the timing of initiating the risk warning. The risk threshold is the probability that the prediction model predicts that the first supplier can successfully complete the delivery by the delivery date.

[0047] For easier understanding, see Figure 2 , which is a schematic diagram of the predicted delay results according to some embodiments of the present disclosure. Please refer to Figure 2 The predicted delay result 200 in the figure is generated by a prediction model corresponding to a first supplier according to an order information, and includes a prediction curve S1 generated by the prediction model. In this coordinate graph, the X-axis represents the corresponding multiple time points, that is, the time after an order of the order information is established (unit: days), and the maximum number of days is the order deadline of the order information. In addition, the Y-axis represents the probability (i.e., the risk threshold) that the first supplier will complete the target quantity of the target product within the order deadline of the order information.

[0048] Based on this, according to the values ​​corresponding to the prediction curve S1 on the X-axis and the Y-axis, the probability that the supplier can complete the target quantity of the target product within the order period when producing the target product at different time points can be known. Figure 2As shown, if the risk threshold is set to 40%, it can be indicated on the Y-axis by a risk horizontal line T corresponding to the position of the risk threshold of 40%. From the intersection point P where the risk horizontal line T intersects with the prediction curve S1, it can be vertically extended downward from the intersection point P to the vertical intersection point with the X-axis position (i.e., the time point). In this example, it can be known that when the risk threshold of the prediction model of the first supplier is 40%, the time point for producing the processing specification is the 50th day. In other words, when the first supplier processes to the 50th day after the order is established, the prediction model predicts that the probability of the first supplier successfully completing the delivery by the delivery date has been reduced to 40%. Based on this, the processor 130 determines that the time point when the probability of completing the delivery is reduced to 40% is a time point with a higher risk of delivery delays.

[0049] In this embodiment, the processor 130 calculates a first time interval based on the time point, wherein the first time interval is composed of a time interval from an initial delivery time point when the supplier produces the target product to the time point.

[0050] In this embodiment, the processor 130 calculates an estimated delivery quantity corresponding to the order information based on a completed quantity of the processing specification of the target product produced by the supplier in the first time interval, that is, the predicted completion quantity within the future production days of the target product.

[0051] In some embodiments, calculating the estimated delivery quantity further includes the following operations: the processor 130 calculates an average daily delivery quantity based on the first time interval and a completed quantity corresponding to the first time interval. Then, the processor 130 calculates the estimated delivery quantity corresponding to the order information based on the average daily delivery quantity and a second time interval, wherein the second time interval is composed of the time interval from the time point to a last delivery time point of the order information.

[0052] by Figure 2 For example, the start time point of the order period when a first supplier produces a target product is day 1, and the end time point of the order period is day 125. Please refer to Figure 2 If the risk threshold is set to 40%, the prediction curve S1 can be extended vertically downward from the intersection point P to the vertical intersection point (i.e., time point) of the X-axis position, and the time point is the 50th day. In other words, in this example, the prediction curve S1 indicates that on the 50th day after the order is established, the probability that the first supplier can successfully complete the delivery on the delivery date has been reduced to 40%. Therefore, the 1st day to the 50th day is a first time interval, and the 51st day to the 125th day is a second time interval. It should be noted that although Figure 2The starting value of the X-axis of the coordinate axis is 0, but in order to conform to the actual processing situation, the initial delivery time point is calculated from 1 (i.e., the 1st day).

[0053] Next, the processor 130 calculates the average daily delivery quantity (i.e., 4 pieces per day) for the past 50 days based on the total completed quantity (e.g., 200 pieces) of the supplier from the 1st day to the 50th day (i.e., the first time interval). Furthermore, the processor 130 calculates an estimated delivery quantity from the 51st day to the 125th day (i.e., the second time interval) based on the average daily delivery quantity. In other words, the processor 130 calculates the estimated delivery quantity for the remaining 75 days to be 4*75=300 pieces based on the production capacity of 4 pieces per day (i.e., the average daily delivery quantity) (i.e., if the supplier still maintains the average delivery quantity of the first 50 days, the estimated delivery quantity that can be provided for the remaining 75 days will be 300 pieces).

[0054] In this embodiment, the processor 130 determines whether to generate a delivery delay warning signal based on the completed quantity and the estimated delivery quantity.

[0055] In some embodiments, the processor 130 may generate the delivery delay warning signal to warn of possible delay risks in advance at the time point when it is determined that the probability of completing the delivery is reduced to a risk threshold.

[0056] In some embodiments, the delivery delay warning signal is used to indicate that the first supplier cannot complete the target quantity of the target product in the order information within an order period corresponding to the order information. In other words, the processor 130 determines that the sum of a completed quantity and an estimated delivery quantity is less than the target quantity of the target product in the order information.

[0057] For example, the target quantity of the target product in the order information is 2000 pieces, but the processor 130 knows based on the prediction model of the present invention that the completed quantity and the estimated delivery quantity at a time point are 200 pieces and 300 pieces respectively. Therefore, the processor 130 can judge and point out that the first supplier cannot complete the target quantity of the target product in the order information within an order period corresponding to the order information based on the calculation result (200+300<1000), and generate a delivery delay warning signal.

[0058] It is worth noting that from Figure 2From the intersection point P where the risk level line T intersects with the prediction curve S1, it can be learned that for a prediction delay result 200 displayed by a prediction model, the timing of generating a delivery delay warning signal is related to the risk threshold. Specifically, if the value of the risk threshold is increased, the Y-axis days corresponding to the intersection point P will be advanced, that is, the time point when the delivery delay warning signal is generated will be closer to the initial delivery time point; on the contrary, if the value of the risk threshold is reduced, the Y-axis days corresponding to the intersection point P will be postponed, that is, the time point when the delivery delay warning signal is generated will be closer to the final delivery time point.

[0059] In some embodiments, the memory 120 may store a notification list, which includes multiple suppliers and corresponding multiple contact information. Each of the multiple suppliers has at least one past cooperation record, and each of the multiple contact information includes at least one external device that can be contacted. The processor 130 may send a message to an external device used by the supplier in the notification list that has a delivery delay through the transceiver interface 110.

[0060] In some embodiments, in response to generating the delivery delay warning signal, the processor 130 may select multiple alternative suppliers from multiple suppliers based on a processing specification included in the order information, wherein the multiple alternative suppliers can also be used to produce the processing specification and have the multiple historical cooperation records corresponding to the processing specification. In addition, the processor 130 selects at least one second supplier from the multiple alternative suppliers based on the multiple historical cooperation records of the multiple alternative suppliers corresponding to the processing specification as a backup for a possible delivery delay of a first supplier.

[0061] Specifically, the processor 130 calculates an average processing time per unit of each of the plurality of alternative suppliers corresponding to the processing specification based on the plurality of historical cooperation records of the plurality of alternative suppliers corresponding to the processing specification. Furthermore, the processor 130 selects the at least one second supplier based on the average processing time per unit of each of the plurality of alternative suppliers.

[0062] For example, the processor 130 calculates the average processing days per unit for the processing specification of "re-dyeing" from the historical cooperation records of alternative suppliers A, B, and C, which are 6.8 days, 4.5 days, and 8 days, respectively. The processor 130 can select alternative supplier B as the second supplier based on the average processing days per unit of alternative suppliers A, B, and C (i.e., select the alternative supplier with the lowest average processing days).

[0063] Further, the processor 130 calculates an estimated delivery quantity required by the first supplier to produce the processing specification, and can obtain a first actual completion day required by the first supplier to complete the estimated delivery quantity (for example, the first supplier needs 75 days to complete the estimated delivery quantity). On the other hand, the processor 130 can obtain a second actual completion day required by each of the multiple alternative suppliers to complete the estimated delivery quantity (for example, one of the alternative suppliers only needs 60 days to complete the estimated delivery quantity) through an average processing day per unit of each of the multiple alternative suppliers corresponding to the processing specification. Based on this, the processor 130 can compare the first actual completion day and the second actual completion day, and select one of the alternative suppliers as the second supplier.

[0064] Based on the above, the processor 130 of the delivery delay warning device 100 of the first embodiment of the present invention can determine whether a delivery delay of a processing specification will occur to the first supplier based on a prediction curve corresponding to a first supplier for a certain processing specification provided by a prediction model, and generate a corresponding delivery delay warning signal. In addition, the processor 130 can select a second supplier as a replacement supplier for the first supplier's production in response to the processor 130 generating the delivery delay warning signal.

[0065] The second embodiment of the present invention is a delivery delay warning method 300. Figure 3 , which illustrates a flow chart of a delivery delay warning method 300 in some embodiments of the present disclosure. The delivery delay warning method 300 is applicable to an electronic device including a delivery delay warning device, such as the delivery delay warning device 100 described in the first embodiment. The delivery delay warning method 300 determines whether a delivery delay warning signal is generated through steps S310 to S340.

[0066] Please refer to Figure 1 as well as Figure 3 In step S310, a processor 130 of the delivery delay warning device 100 inputs an order information corresponding to a target product into the prediction model M to determine a time point corresponding to a risk threshold. In step S320, the processor 130 calculates a first time interval based on the time point, wherein the first time interval is composed of a time interval from an initial delivery time point to the time point. In step S330, the processor 130 calculates an estimated delivery quantity corresponding to the order information based on a completed quantity corresponding to the first time interval, wherein the estimated delivery quantity is an unstocked quantity of the target product, that is, the result of subtracting the completed quantity from the target quantity of the target product. In step S340, the processor 130 determines whether to generate a delivery delay warning signal based on the completed quantity and the estimated delivery quantity.

[0067] In some embodiments, the processor may add the order information and an actual delivery time corresponding to the first supplier to the plurality of historical cooperation records to update the prediction model. Specifically, the processor may update the prediction model to adjust the processing specification of the supplier for the target product based on the actual delivery time. For example, if the supplier completes the processing specification on the 10th day from the initial delivery time point in this order, then for the prediction model, the probability of the next prediction that the supplier will complete the processing specification on the 10th day will increase.

[0068] It should be noted that in the patent specification and claims of the present invention, some terms (including: supplier, time interval, etc.) are preceded by "first", "second" or "third". These "first", "second" or "third" are only used to distinguish different terms. For example, the "first" and "second" in the first time interval and the second time interval are only used to indicate the time intervals used in different operations.

[0069] In summary, the delivery delay warning technology provided by the present invention can estimate the daily delivery volume of the target product with specific processing specifications. Compared with the prior art, the present invention combines the supplier's historical records and machine learning algorithms to estimate the production of the target product, which can further improve the accuracy of delivery prediction. In addition, based on the learning results of the model, the present invention can select an alternative supplier when it is determined that the supplier has a delivery delay, so as to solve the delivery delay problem of the original supplier and reduce the risk of the target product not being completed on schedule.

[0070] The above embodiments are only used to illustrate some embodiments of the present invention and to explain the technical features of the present invention, and are not used to limit the protection category and scope of the present invention. Any changes or equivalent arrangements that can be easily completed by a person with ordinary knowledge in the technical field to which the present invention belongs are within the scope claimed by the present invention, and the scope of protection of the present invention is subject to the claims.

Claims

1. A delivery delay warning device, It is characterized in that Include: A transceiver interface; a memory for storing a prediction model, wherein the prediction model corresponds to a first supplier and the prediction model is generated by a plurality of historical cooperation records corresponding to the first supplier; and A processor is electrically connected to the transceiver interface and the memory and is used to perform the following operations: Inputting order information corresponding to a target product into the prediction model to determine a time point corresponding to a risk threshold; Based on the time point, calculating a first time interval, wherein the first time interval is composed of a time interval from an initial delivery time point to the time point; Calculating an estimated delivery quantity corresponding to the order information based on a completed quantity corresponding to the first time interval; and Based on the completed quantity and the estimated delivery quantity, it is determined whether to generate a delivery delay warning signal.

2. The delivery delay warning device according to claim 1, It is characterized in that The time point for determining the corresponding risk threshold also includes the following operations: Inputting the order information corresponding to the target product into the prediction model to generate a predicted delay result corresponding to the target product; as well as Based on the predicted delay result and the risk threshold, the time point corresponding to the risk threshold is determined.

3. The delivery delay warning device according to claim 1, It is characterized in that The order information includes a target quantity and a processing specification corresponding to the target product.

4. The delivery delay warning device according to claim 3, It is characterized in that The delivery delay warning signal is used to indicate that the first supplier is unable to complete the target quantity of the target product in the order information within an order period corresponding to the order information.

5. The delivery delay warning device according to claim 1, It is characterized in that The calculation of the estimated delivery quantity corresponding to the order information also includes the following operations: Calculating an average daily delivery quantity based on the first time interval and a completed quantity corresponding to the first time interval; and The estimated delivery volume corresponding to the order information is calculated based on the average daily delivery volume and a second time interval, wherein the second time interval is composed of the time interval from the time point to a last delivery time point of the order information.

6. The delivery delay warning device according to claim 1, It is characterized in that The prediction model is generated by the following operations: Receiving the plurality of historical cooperation records corresponding to the first supplier, wherein each of the plurality of historical cooperation records comprises a historical order information and a historical delivery time; Inputting the plurality of historical cooperation records into an initial prediction model to train the initial prediction model; and The trained initial prediction model is set as the prediction model.

7. The delivery delay warning device according to claim 1, It is characterized in that The processor further performs the following operations: The order information and an actual delivery time corresponding to the first supplier are added to the plurality of historical cooperation records to update the prediction model.

8. The delivery delay warning device according to claim 1, It is characterized in that The processor further performs the following operations: In response to generating the delivery delay warning signal, selecting a plurality of substitute suppliers from a plurality of suppliers based on a processing specification included in the order information, wherein the plurality of substitute suppliers have the plurality of historical cooperation records corresponding to the processing specification; as well as At least one second supplier is selected from the plurality of alternative suppliers based on the plurality of historical cooperation records of the plurality of alternative suppliers corresponding to the processing specification.

9. The delivery delay warning device according to claim 8, It is characterized in that Wherein selecting the at least one second supplier from the plurality of alternative suppliers further comprises the following operations: Calculating a unit average processing time of each of the plurality of alternative suppliers corresponding to the processing specification based on the plurality of historical cooperation records of the plurality of alternative suppliers corresponding to the processing specification; as well as The at least one second supplier is selected based on the unit average processing days corresponding to each of the plurality of alternative suppliers.

10. A delivery delay warning method, It is characterized in that For an electronic device, the delivery delay warning method comprises the following steps: Inputting order information corresponding to a target product into a prediction model to determine a time point corresponding to a risk threshold, wherein the prediction model corresponds to a first supplier and the prediction model is generated by a plurality of historical cooperation records corresponding to the first supplier; Based on the time point, calculating a first time interval, wherein the first time interval is composed of a time interval from an initial delivery time point to the time point; Calculating an estimated delivery quantity corresponding to the order information based on a completed quantity corresponding to the first time interval; and Based on the completed quantity and the estimated delivery quantity, it is determined whether to generate a delivery delay warning signal.

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