Garment order flow intelligent management method and system

Abstract

The invention discloses a clothing order flow intelligent management method and system, and the method comprises the steps: obtaining to-be-processed orders in a period of time, presetting a search target and a sorting mode, searching all orders meeting a search condition according to the search condition, and displaying the searched search result, the search results are arranged and displayed in the sorting mode; performing priority ranking on the searched unprocessed orders and submitting the orders to re-order planning, wherein the priority ranking is performed according to a preset priority degree parameter; and ordering the orders according to the re-ordering plan, and processing the orders according to the order ordering. According to the method, through production scheduling management of the production orders in the garment order process, optimal configuration of the production orders and the assembly line is realized, scientific management in garment production is realized, and the management efficiency and the production processing efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the field of logistics technology, and in particular to an intelligent management method and system for clothing order processes. Background Art

[0002] As a traditional manufacturing industry in my country, the clothing industry occupies an important position in the development of my country's light industry. In recent years, with the development of intelligent and automated technologies, the production and manufacturing fields of the clothing industry have gradually realized automated and mechanized production, greatly improving production efficiency. However, in the existing clothing production process, there are still many problems in intelligent production management, especially in order scheduling management.

[0003] At present, most clothing companies use manual reports and Excel tools, relying on human experience and planning ability to schedule orders, and the scheduling process is highly subjective. Manual scheduling has a long cycle and is difficult to modify, which is suitable for large-scale production. However, with the emergence of a large number of small-batch, multi-variety, multi-style, and multi-specification orders, manual scheduling that relies on experience cannot ensure the rationality of the scheduling plan and is not competent for the task of order scheduling. Summary of the invention

[0004] The purpose of the present invention is to provide a method for intelligent management of clothing order processes to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: A clothing order process intelligent management method, comprising: Obtain the pending orders within a period of time, preset the search target and sorting method, search for all orders that meet the search conditions according to the search conditions and display the search results, which are arranged and displayed in the preset sorting method; Prioritize the unprocessed orders found and submit a rescheduling plan, wherein the priority is sorted according to a preset priority parameter; Orders are sorted according to the rescheduling plan, and the sorted orders are processed according to the order sorting.

[0006] Furthermore, obtaining the pending orders within a period of time specifically includes: The period set by the user is taken as a period of time; All recorded orders that are confirmed to be processed within this period are obtained as pending orders; The orders that are confirmed to be processed include orders for which contracts have been signed, orders for which deposits have been paid, and orders confirmed by relevant persons in charge.

[0007] Furthermore, order sorting includes unscheduled order sorting and scheduled order sorting.

[0008] Furthermore, the production order sorting specifically includes: counting the load of each assembly line, where the load is the number of processing orders currently executed by the assembly line and the delivery cycle deadline; According to the current load of the assembly line, select the processing orders that meet the set conditions from the unscheduled order sequence and insert them into the current processing queue. The number of processing orders that meet the set conditions is determined according to the current load of the assembly line; Determine whether the planned number of the processing queue of the current assembly line exceeds the set critical value of the scheduled processing quantity; If the set processing quantity threshold is exceeded, a plan is taken out from the processing queue and the plan is reordered; If the set processing quantity threshold is not exceeded, it is determined whether there are any unscheduled processing plans in the current unscheduled order sorting; If there are any unscheduled processing plans, re-arrange them.

[0009] Furthermore, the sorting of unscheduled orders specifically includes: Select the processing order with the shortest delivery cycle. The processing order with the shortest delivery cycle is the processing order that is completed earliest within the planned time and has the earliest delivery cycle among the scheduled orders. Calculate the delay time of the normal processing line. The delay days are the time difference between the current estimated completion time of the processing order and the estimated completion time when the processing order is scheduled; Select an assembly line based on the number of days of delay and schedule the processing orders to the assembly line. The assembly line scheduled this time is the one with the least number of days of delay and the shortest delivery time for processing orders. Determine whether the processing order has been scheduled; If the production scheduling is completed, the sorting of the unscheduled orders will be ended. If it is not completed, the sorting task of the unscheduled orders will continue.

[0010] Furthermore, the conditions are set based on the current order quantity, the current delivery time, and the current order delay.

[0011] Furthermore, the preset priority parameters specifically include: customer priority, order priority and order item priority.

[0012] To achieve the above object, the present invention also provides the following technical solutions: An intelligent management system for clothing order process, comprising: The acquisition unit is used to acquire the orders to be processed within a period of time, preset the search target and sorting method, search all orders that meet the search conditions according to the search conditions and display the search results, and the search results are arranged and displayed in a preset sorting method; A sorting unit, used to prioritize the unprocessed orders found and submit a rescheduling plan, wherein the priority sorting is performed according to a preset priority parameter; Orders are sorted according to the rescheduling plan, and the sorted orders are processed according to the order sorting.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The method of the present invention realizes the optimal configuration of production orders and assembly lines through the production scheduling management of production orders in the clothing order process, realizes scientific management in clothing production, and improves management efficiency and production and processing efficiency.

[0014] The method of the present invention optimizes the production and processing schedule of the assembly line by studying the assembly line scheduling problem, and solves the problem of how to allocate limited resources in time to complete different production tasks and optimize the predetermined goals.

[0015] The method of the present invention solves the problem that traditional scheduling such as manual scheduling cannot be optimized due to inflexibility and cannot coordinate the overall situation, resulting in frequent insertion of orders and modification of scheduling, making the scheduling of clothing assembly line production and processing simpler, faster and more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of the intelligent management method of clothing order process of the present invention.

[0017] Figure 2 This is a block diagram of the clothing order process intelligent management system of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] See also Figure 1 to Figure 2 , the present invention provides a technical solution: like Figure 1 As shown, a method for intelligent management of clothing order process includes: Obtaining orders to be processed within a period of time, presetting a search target and a sorting method, searching for all orders that meet the search conditions according to the search conditions and displaying the search results, which are arranged and displayed in the sorting method; Prioritize the unprocessed orders found and submit a rescheduling plan, wherein the priority is sorted according to a preset priority parameter; Orders are sorted according to the rescheduling plan, and the corresponding orders are processed according to the order sorting.

[0020] Specifically, obtaining the pending orders within a period of time includes: The period set by the user is taken as a period of time; All recorded orders that are confirmed to be processed within this period are obtained as pending orders; The orders that are confirmed to be processed include orders for which contracts have been signed, orders for which deposits have been paid, and orders confirmed by relevant persons in charge.

[0021] Specifically, order sorting includes unscheduled order sorting and scheduled order sorting.

[0022] The production order sorting specifically includes: counting the load of each assembly line, which is the number of processing orders currently executed by the assembly line and the delivery cycle deadline; According to the current load of the assembly line, select the processing orders that meet the set conditions from the unscheduled order sequence and insert them into the current processing queue. The number of processing orders that meet the set conditions is determined according to the current load of the assembly line; Determine whether the planned number of the processing queue of the current assembly line exceeds the set critical value of the scheduled processing quantity; If the set processing quantity threshold is exceeded, a plan is taken out from the processing queue and the plan is reordered; If the set processing quantity threshold is not exceeded, it is determined whether there are any unscheduled processing plans in the current unscheduled order sorting; If there are any unscheduled processing plans, re-arrange them.

[0023] Specifically, the sorting of unscheduled orders includes: Select the processing order with the shortest delivery cycle. The processing order with the shortest delivery cycle is the processing order that is completed earliest within the planned time and has the earliest delivery cycle among the scheduled orders. Calculate the delay time of the normal processing line. The delay days are the time difference between the current estimated completion time of the processing order and the estimated completion time when the processing order is scheduled; Select an assembly line based on the number of days of delay and schedule the processing orders to the assembly line. The assembly line scheduled this time is the one with the least number of days of delay and the shortest delivery time for processing orders. Determine whether the processing order has been scheduled; If the production scheduling is completed, the sorting of the unscheduled orders will be ended. If it is not completed, the sorting task of the unscheduled orders will continue.

[0024] Specifically, the conditions are set based on the current order quantity, the current delivery time, and the current order delay situation.

[0025] Specifically, the preset priority parameters include: customer priority, order priority and order item priority.

[0026] In the present invention, as an optional but not necessary embodiment: the search target is the orders placed by the customer, including large orders, medium orders and small orders, wherein the number of pieces to be processed for large orders is not less than M, the number of pieces for medium orders is between M and N, M is greater than N, and the number of pieces for small orders is less than N.

[0027] In the present invention, the sorting method can be classified by order amount, order time, or estimated completion time.

[0028] In the present invention, the search condition is to search all orders that meet the search condition according to similarity. Specifically, similarity is: setting the search keyword for this time, using the weight of the search keyword for this time and the historical keyword to reflect the similarity value, and selecting the order with the highest similarity value. The historical search order is used as the search order for this time. The specific expression is as follows:

[0029] ; in, is the similarity function between this order search and the historical order search. is the weight of this search order and the historical search order, , Respectively i Of all orders m The weight of the first keyword is j Of all orders m The weight of the keywords, n Represents all orders.

[0030] In the present invention, , One way to calculate it is as follows: , ; in: ; ; ; ; ; tf-idf (Term Frequency-Inverse Document Frequency) is term frequency-inverse document frequency, tf ( t m , l i ), tf ( t m , l j ) is the word frequency, respectively representing the m Keywords in i and j The frequency of occurrence in all orders. The more frequent the word, the more t m The more important in all orders. idf ( t m ) is the inverse document frequency, word t m The fewer orders it is included in, the more important it is.

[0031] In the present invention, there are multiple orders for one production schedule, and the delivery dates of different orders are different. Each order contains many order items (including the processing quantity of each code of the finished product style). The assembly line scheduling problem is described as: n line items in m Processing on 1 machine, one order item is divided into k Each process requires different machine processing. n line items in m The processing order on the same machine is the same, the order items i 1 in the machine j The processing time on 1 can be calculated based on the production capacity and is set as t i1j1 ( i 1=1, 2, …, n ; j 1=1, 2, …, m 1). The objective function of the scheduling problem is to find n The optimal processing sequence for each order item minimizes the maximum process time.

[0032] In the assembly line scheduling problem, it includes: the processing order of each order item on the machine is the same and certain; each machine can only process a certain process of a certain order item at each moment; an order item cannot be processed on different machines at the same time; the preparation time of the process is independent of the sequence and is included in the processing time.

[0033] by C ( j i1 , k 1) Indicates an order item j i1 In the machine k 1 processing completion time, j 1, j 2, ..., j n} represents the scheduling of order items, t ji1，k1 For orders j i1 Item in the machine k 1, then n line items m The order item completion time for the assembly line scheduling problem with 10 machines is: C ( j i1 ,1)= t ji1，1 ; C ( j i1 , k 1)= C ( j i1 ,1)+ t ji1， k 1, k 1=2,… m ; C ( j i1 , k 1)= C ( j i1-1 , k 1)+ t ji1， k 1, k 1=2,… n ; C ( j i1 , k 1)= max {C ( j i1-1 , k 1); C ( j i1 ,1)}+ t ji1， k 1, i =2, …, n ; k 1=2,… m .

[0034] Therefore, the maximum completion time is: C max = C ( j n , m ).

[0035] Since processing manufacturers often encounter situations where orders within a certain period of time cannot be completed within the existing production capacity, especially under manual scheduling, in order to meet the requirements of processing manufacturers to ensure the satisfaction of important customers, priority sorting is used to ensure that orders from important customers can receive relatively high priority.

[0036] The present invention prioritizes the unprocessed orders found and submits the rescheduling plan. The priority ranking is based on the preset priority parameters, and the preset priority parameters specifically include: customer priority, order priority and order item priority. A weighted method is adopted to assign weights to customer priority, order priority and order item priority respectively. avgd , and satisfies α + β + c + d =1.

[0037] Among them, customer priority IM c The calculation formula is as follows: ; The weights are as follows: , α =0.3; annual trade volume , β =0.2; monthly trade volume , d =0.3; Credit rating of processing manufacturer ,δ=0.2 Order priority IM rc The calculation formula is as follows: ; The weights are assigned as follows: IM c The weight of α =0.4; total order quantity QU rc The weight of , β = 0.3; the total amount of the order AM rc The weight of c =0.3; Line item priority IM irc The calculation formula is as follows: ; The weights are assigned as follows: Order priority IM rc The weight of α =0.4; total order quantity QU rc The weight of β =0.3; total order amount AM rc The weight of c =0.3.

[0038] by DJ To complete the line item i The cost spent. t i To complete the order i The processing time required, AV is the average daily cost of the processing factory (a constant). B i for i The default cost is 10% of the order amount; IM i For line items i Importance, D i for i The default days, the objective function is expressed as follows:

[0039] .

[0040] As an optional but not essential embodiment, order sorting according to the order rescheduling plan specifically includes the following steps: (a) The order of joining the schedule is used as the initial solution; (b) Initialize the parameters of the frog leaping algorithm; (c) The frog leaps to the regional node according to a certain probabilistic decision rule; (d) The pheromone trajectory is updated; (e) Repeat steps (c) and (d) until a solution is constructed; (f) If it is less than the predetermined number of iterations, continue to iterate and update all route pheromones; (g) Compare the new solution with the initial solution and record the better solution; (h) Output the optimal solution.

[0041] The specific method of searching the area is as follows: the probability of frog jumping to choose a certain route is equal to the pheromone on the route divided by the sum of the pheromones of all the optional routes. i point, p ( i , j ) indicates the next arrival j The probability of a point, t ( i , j )express ij The pheromone between two points, If the sum of pheromones of all optional routes moves t ( i )=0, that is, there has been no frog jump before, and the probability is a random value on [0,1], that is, a route is randomly selected.

[0042] Update pheromones are as follows: The pheromone volatilization factor is designed as the number of iterations k Function 2 p ( k 2)=1-ln( k 2+2) / ln( k 2+3). Initially set the pheromone of each path t ( i , j ,0) are the same value.

[0043] Volatile pheromone function: t ( i , j , k 2+1)= (1- p ( k 2)) t ( i , j , k 2); Enhanced pheromone function: t ( i , j , k 2+1)= (1- p ( k 2)) t ( i , j , k 2)+ p ( k 2) / |T|, T is the processing time of the point.

[0044] The present invention, as Figure 2 As shown, an intelligent management system for clothing order process includes: An acquisition unit is used to acquire orders to be processed within a period of time, preset a search target and a sorting method, search for all orders that meet the search conditions according to the search conditions and display the search results, and the search results are arranged and displayed in the sorting method; A sorting unit, used to prioritize the unprocessed orders found and submit a rescheduling plan, wherein the priority sorting is performed according to a preset priority parameter; The processing unit sorts the orders according to the rescheduling plan and processes the sorted orders according to the order sorting.

[0045] The method of the present invention realizes the optimal configuration of production orders and assembly lines through the production scheduling management of production orders in the clothing order process, realizes scientific management in clothing production, and improves management efficiency and production and processing efficiency.

[0046] The method of the present invention optimizes the production and processing schedule of the assembly line by studying the assembly line scheduling problem, and solves the problem of how to allocate limited resources in time to complete different production tasks and optimize the predetermined goals.

[0047] The method of the present invention solves the problem that traditional manual scheduling cannot optimize scheduling due to its inflexibility and cannot coordinate the overall situation, resulting in frequent insertion of orders and modification of scheduling, making the scheduling of clothing assembly line production and processing simpler, faster and more accurate.

[0048] The present invention, the undescribed parts are prior art.

[0049] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A clothing order process intelligent management method, characterized in that: include: Obtain the pending orders within a period of time, preset the search target and sorting method, search for all orders that meet the search conditions according to the search conditions and display the search results, which are arranged and displayed in the preset sorting method; Prioritize the unprocessed orders found and submit a rescheduling plan, wherein the priority is sorted according to a preset priority parameter; Sort the orders according to the rescheduling plan, and process the sorted orders according to the order sorting; Obtaining pending orders within a period of time specifically includes: The period set by the user is taken as a period of time; All recorded orders that are confirmed to be processed within this period are obtained as pending orders; The orders that are confirmed to be processed include orders for which contracts have been signed, orders for which deposits have been paid, and orders confirmed by relevant persons in charge.

2. A clothing order process intelligent management method as claimed in claim 1, characterized in that: Order sorting includes unscheduled order sorting and scheduled order sorting.

3. A clothing order process intelligent management method as claimed in claim 2, characterized in that: The production order sorting specifically includes: counting the load of each assembly line, which is the number of processing orders currently executed by the assembly line and the delivery cycle deadline; According to the current load of the assembly line, select the processing orders that meet the set conditions from the unscheduled order sequence and insert them into the current processing queue. The number of processing orders that meet the set conditions is determined according to the current load of the assembly line; Determine whether the planned number of the processing queue of the current assembly line exceeds the set critical value of the scheduled processing quantity; If the set processing quantity threshold is exceeded, a plan is taken out from the processing queue and the plan is reordered; If the set processing quantity threshold is not exceeded, it is determined whether there are any unscheduled processing plans in the current unscheduled order sorting; If there are any unscheduled processing plans, re-arrange them.

4. A clothing order process intelligent management method as claimed in claim 2, characterized in that: The sorting of unscheduled orders specifically includes: Select the processing order with the shortest delivery cycle. The processing order with the shortest delivery cycle is the processing order that is completed earliest within the planned time and has the earliest delivery cycle among the scheduled orders. Calculate the delay time of the normal processing line. The delay days are the time difference between the current estimated completion time of the processing order and the estimated completion time when the processing order is scheduled; Select an assembly line based on the number of days of delay and schedule the processing orders to the assembly line. The assembly line scheduled this time is the one with the least number of days of delay and the shortest delivery time for processing orders. Determine whether the processing order has been scheduled; If the production scheduling is completed, the sorting of the unscheduled orders will be ended. If it is not completed, the sorting task of the unscheduled orders will continue.

5. The intelligent management method for clothing order process according to claim 3, characterized in that: The conditions are set based on the current order quantity, current delivery time, and current order delays.

6. The intelligent management method for clothing order process according to claim 1, characterized in that: The preset priority parameters specifically include: customer priority, order priority, and order item priority.

7. An intelligent management system for clothing order process, characterized in that: include: The acquisition unit is used to acquire the orders to be processed within a period of time, preset the search target and sorting method, search all orders that meet the search conditions according to the search conditions and display the search results, and the search results are arranged and displayed in a preset sorting method; A sorting unit, used to prioritize the unprocessed orders found and submit a rescheduling plan, wherein the priority sorting is performed according to a preset priority parameter; The processing unit sorts the orders according to the rescheduling plan and processes the sorted orders according to the order sorting; Obtaining pending orders within a period of time specifically includes: The period set by the user is taken as a period of time; All recorded orders that are confirmed to be processed within this period are obtained as pending orders; The orders that are confirmed to be processed include orders for which contracts have been signed, orders for which deposits have been paid, and orders confirmed by relevant persons in charge.

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