CN117875081A - Digital production simulation method and system for jeans wear - Google Patents
Digital production simulation method and system for jeans wear Download PDFInfo
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Abstract
The invention relates to the technical field of production data processing, in particular to a digital production simulation method and system of jeans wear, wherein the method comprises the following steps: determining a delivery pressure threshold for the garment style based on the production quantity and the delivery time of the garment style; obtaining a current production pressure threshold value of each station in the station group based on the unit speed and the processing speed; determining redundancy of each station in the station group according to the delivery pressure threshold of the clothing style and the current production pressure threshold of each station in the station group, and respectively selecting a plurality of stations with front redundancy from the station groups corresponding to each procedure to form a station cluster; establishing an objective function for minimizing the production balance degree according to the processing parameters of the station clusters and the production quantity of the garment styles, and solving the objective function by adopting a genetic annealing algorithm to obtain a digital simulation result of the garment styles; the invention can improve the production efficiency and meet the time requirement of production and delivery.
Description
Technical Field
The invention relates to the technical field of production data processing, in particular to a digital production simulation method and system for jeans wear.
Background
The charm of jeans wear is derived from a vast variety of water washing processes, so that a great deal of creative designs can be stimulated, and the jeans wear is a personalized wear, and is particularly suitable for the production mode of C2M (Customer to Manufactory, customer to factory). Therefore, there is a need to provide customers with a rich jeans garment design style.
However, most of the existing jeans wear designs adopt a semi-automatic production mode, the procedures are complicated, the efficiency is low, and due to the processing speed difference of personnel, the production consistency is difficult to achieve, the problem of non-uniform production progress occurs, and the production delivery time is influenced.
Therefore, digital simulation is necessary for the production of jeans wear, and the time requirement of production delivery is met through reasonable production task allocation.
Disclosure of Invention
The invention aims to provide a digital production simulation method and system for jeans wear, which are used for meeting the time requirement of production delivery by reasonably distributing production tasks.
In order to achieve the above object, the present invention provides the following technical solutions:
in one aspect, the invention provides a simulation method for digital production of jeans wear, the method comprising the steps of:
acquiring a clothing style of jeans clothing, and setting production quantity and delivery time for the clothing style, and determining a delivery pressure threshold of the clothing style based on the production quantity and the delivery time; the delivery pressure threshold value characterizes the urgency of delivery;
acquiring working procedures for processing the clothing patterns, matching all working stations to obtain working station groups corresponding to all working procedures, acquiring unit speeds and current processing speeds of all working stations in the working station groups, and obtaining current production pressure thresholds of all working stations in the working station groups based on the unit speeds and the processing speeds; the unit speed is the maximum processing speed of the station; the production pressure threshold characterizes the degree of yield improvement;
according to the delivery pressure threshold of the clothing style and the current production pressure threshold of each station in the station group, respectively selecting a plurality of stations from the station group corresponding to each procedure, and forming a station cluster by the selected stations according to the corresponding procedures;
acquiring processing parameters of a station cluster, establishing an objective function for minimizing production balance according to the processing parameters of the station cluster and the production quantity of the clothing style, and solving the objective function by adopting a genetic annealing algorithm to obtain a digital simulation result of the clothing style; wherein, the processing parameters comprise the number and working procedures of each station in the station cluster; the production balance represents the processing time length of the clothing style and the load ratio of the station clusters; the digital simulation result comprises the load ratio of each station in the station cluster and the processing time length for processing the clothing style.
Further, the determining a delivery pressure threshold for the garment style based on the production quantity and delivery time includes:
acquiring current time, and taking the duration of the current time distance delivery time as time redundancy;
calculating to obtain a delivery pressure threshold of the clothing style according to the following formula;
wherein T is 0 Representing the time redundancy of the clothing style, K representing the total batch of the clothing style, K representing the batch number of the clothing style, B representing the batch number of the jeans clothing, B representing the total batch of the jeans clothing processed in the past time period, bp representing the p-th jeans in the B-th batch, K b Represents the total number of jeans wear in lot b, n bp Representing the number of parts used to manufacture the p-th jeans in the b-th lot, T bp Representing the processing time of the p-th jeans in the b-th batch, m representing the total number of parts used to process the fashion of the garment, avg n Representing the average number of parts used to manufacture a jeans garment.
Further, the step of obtaining the clothing style, obtaining the work station group corresponding to each step from all the work stations in a matching way, obtaining the unit speed and the current processing speed of each work station in the work station group, and obtaining the current production pressure threshold of each work station in the work station group based on the unit speed and the processing speed, including:
obtaining a design model of the clothing style, and analyzing a data packet of the jeans clothing according to the design model; wherein the design model comprises a design drawing, a clothing component and a clothing component; the data packet comprises geometric parameters of each clothing component and each stitch in jeans wear;
based on the corresponding working procedures of each clothing component in the data packet, matching a plurality of work groups from all work stations; each working procedure is provided with a corresponding station group, and the station group comprises a plurality of stations;
acquiring unit speeds of all stations in a station group, and generating production process parameters of the station group based on the data packet and the unit speeds; the production process parameters comprise unit speeds corresponding to all stations in the station group;
the current processing speed of each station in the station group is obtained, and the current production pressure threshold of the station is obtained based on the current processing speed and the unit speed of each station.
Further, the current production pressure threshold of the station is calculated by the following formula:
wherein De gu Representing the current production pressure threshold, n, of a station gu in a group of stations group Indicating the total number of stations in the group of stations, gu group Is the number of the station in the station group, s group Indicating station u group Is(s) is (are) a unit speed gu Indicating the current processing speed of the station gu,indicating station gu group Current processing speed.
Further, according to the delivery pressure threshold of the clothing style and the current production pressure threshold of each working position in the working position group, respectively selecting a plurality of working positions from the working position group corresponding to each working procedure, including:
if it isThe stations selected from the group of stations satisfy:
otherwise, the stations selected from the station group satisfy:
wherein P is k Representing the number of clothing styles produced in the kth batch, and Group represents the total number of work groups, that is, the total number of procedures; p (P) k Indicating the number of clothing items produced in the kth batch, gi indicating the number of stations selected from the group of stations, de gi Representing the current production pressure threshold for station gi; max () represents maximum value, min () represents minimum value, mean () represents average value.
Further, the expression of the objective function is:
wherein F is 1 Representing an objective function that minimizes production balance, N is the total number of stations in the station cluster, i is the station number, Q i Indicating the duty ratio of station i, PT i Representing the sum of the processing time length of the working procedure completed by the station i; beta and gamma are weights, beta is used to adjust the importance of the station load, and gamma is used to adjustImportance of processing duration; k represents the batch number of the clothing style, mk is the production quantity of the kth batch of the clothing style, n i The total number of working procedures for the clothing style in the working position i, j is the number of the working procedures, q ij The j-th working procedure for clothing style occupies the load ratio of the working position i, t ij The processing time of the j-th procedure of the clothing style in the station i is shown.
In another aspect, the present invention provides a digital production simulation system for jeans wear, comprising:
at least one processor;
at least one memory for storing at least one program;
the at least one program, when executed by the at least one processor, causes the at least one processor to implement the digital production simulation method of jeans wear of any one of the above.
The beneficial effects of the invention are as follows: the invention discloses a digitalized production simulation method and system for jeans wear, wherein a plurality of stations are respectively selected from work station groups corresponding to each process according to a delivery pressure threshold value of a wear style and a current production pressure threshold value of each station in the work station groups, and the selected stations form station clusters according to the corresponding process; and establishing an objective function for minimizing the production balance degree according to the processing parameters of the station clusters and the production quantity of the clothing styles, and solving the objective function by adopting a genetic annealing algorithm to obtain a digital simulation result of the clothing styles. According to the invention, the production tasks are reasonably distributed through the digital simulation of the jeans wear production process, so that the production efficiency is improved, and the time requirement of production delivery is met.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a digital production simulation method of jeans wear in an embodiment of the invention;
fig. 2 is a schematic structural diagram of a digital production simulation system of jeans wear in an embodiment of the present invention.
Detailed Description
The conception, specific structure, and technical effects produced by the present invention will be clearly and completely described below with reference to the embodiments and the drawings to fully understand the objects, aspects, and effects of the present invention. It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.
Referring to fig. 1, fig. 1 is a schematic flow chart of a digital production simulation method for jeans wear, which includes the following steps:
s100, acquiring a clothing style of jeans clothing, and the production quantity and delivery time set for the clothing style, and determining a delivery pressure threshold of the clothing style based on the production quantity and the delivery time; the delivery pressure threshold value characterizes the urgency of delivery;
s200, acquiring working procedures for processing the clothing patterns, matching all working stations to obtain working station groups corresponding to all working procedures, acquiring unit speeds and current processing speeds of all working stations in the working station groups, and acquiring current production pressure thresholds of all working stations in the working station groups based on the unit speeds and the processing speeds; the unit speed is the maximum processing speed of the station; the production pressure threshold characterizes the degree of yield improvement;
s300, respectively selecting a plurality of stations from the work station group corresponding to each working procedure according to the delivery pressure threshold of the clothing style and the current production pressure threshold of each station in the work station group, and forming station clusters by the selected stations according to the corresponding working procedures;
s400, acquiring processing parameters of a station cluster, establishing an objective function for minimizing production balance degree according to the processing parameters of the station cluster and the production quantity of the clothing style, and solving the objective function by adopting a genetic annealing algorithm to obtain a digital simulation result of the clothing style; wherein, the processing parameters comprise the number and working procedures of each station in the station cluster; the production balance represents the processing time length of the clothing style and the load ratio of the station clusters; the digital simulation result comprises the load ratio of each station in the station cluster and the processing time length for processing the clothing style.
In the embodiment provided by the invention, according to the delivery pressure threshold of the clothing style and the current production pressure threshold of each station in the station group, a plurality of stations are respectively selected from the station groups corresponding to each procedure, and the selected stations form a station cluster according to the corresponding procedures. And then, establishing an objective function for minimizing the production balance degree according to the processing parameters of the station clusters and the production quantity of the clothing styles, and solving the objective function by adopting a genetic annealing algorithm to obtain a digital simulation result of the clothing styles. After the digital simulation result is obtained, the garment style can be produced based on the digital simulation result. According to the invention, the production tasks are reasonably distributed through the digital simulation of the jeans wear production process, so that the production efficiency is improved, and the time requirement of production delivery is met.
As a modification of the above embodiment, in S100, the determining a delivery pressure threshold for the garment style based on the production quantity and delivery time includes:
acquiring current time, and taking the duration of the current time distance delivery time as time redundancy;
calculating to obtain a delivery pressure threshold of the clothing style according to the following formula;
wherein T is 0 The time redundancy amount of the clothing style is represented by K, the total batch of the clothing style is represented by K, the batch number of the clothing style is represented by K, the batch number of the jeans is represented by B, the total batch of the jeans processed in the past time period is represented by B, and the p-th jeans in the B-th batch is represented by bpDress, k b Represents the total number of jeans wear in lot b, n bp Representing the number of parts used to manufacture the p-th jeans in the b-th lot, T bp Representing the processing time of the p-th jeans in the b-th batch, m representing the total number of parts used to process the fashion of the garment, avg n Representing the average number of parts used to manufacture a jeans garment.
The parameters K, bp, K b 、n bp 、T bp 、Avg n The jeans wear-resistant fabric is obtained by selecting production records in a past time period, and the corresponding production quantity of jeans wear in each batch is set.The maximum value of the processing time length of the jeans in the b-th batch is represented, and the maximum value of the processing time length is taken as the processing time length of each jeans in the batch, so that the reasonable time can be reserved for the styles of the jeans.
As an improvement of the foregoing embodiment, in S200, the step of obtaining the garment style, obtaining, by matching, from all the stations, a work station group corresponding to each of the steps, obtaining a unit speed and a current processing speed of each of the work stations in the work station group, and obtaining, based on the unit speed and the processing speed, a current production pressure threshold of each of the work stations in the work station group, including:
s210, acquiring a design model of the clothing style, and analyzing a data packet of the jeans clothing according to the design model; wherein the design model comprises a design drawing, a clothing component and a clothing component; the data packet comprises geometric parameters of each clothing component and each stitch in jeans wear;
specifically, the lines in the design drawing are used as the sutures, so that the geometric parameters of each suture are obtained.
S220, based on the corresponding working procedures of each clothing component in the data packet, matching a plurality of work station groups from all the work stations; each working procedure is provided with a corresponding station group, and the station group comprises a plurality of stations;
specifically, the components of the jeans wear comprise fabric, zippers, rivets, buttons and the like, different components have corresponding working procedures, different stations have corresponding processing technologies, the components are used for completing the processing procedures of the corresponding components, and each working procedure has a plurality of corresponding stations. For example, during the sewing phase, the panels are individually sent to designated stations of a sewing line. Then the process of making front piece, top fly and zipper, back piece, assembling and sewing, hitching and button sewing is completed.
S230, obtaining unit speeds of all stations in a station group, and generating production process parameters of the station group based on the data packet and the unit speeds; the production process parameters comprise unit speeds corresponding to all stations in the station group;
in this embodiment, assuming that each station has a constant unit speed (for example, a sewing speed), the length of the thread to be sewn can be predicted according to the geometric parameters of each thread in the jeans wear, so as to estimate the unit speed of the thread; the unit speed of each garment component is empirically set.
S240, acquiring the current processing speed of each station in the station group, and obtaining the current production pressure threshold of the station based on the current processing speed and the unit speed of each station.
The current processing speed of each station is an actual measurement value, the unit speed is a theoretical value, and the current processing speed and the unit speed of each station are comprehensively evaluated to obtain the processing amount which can be continuously carried by the station group and the processing efficiency of the station group after the production task of the clothing style is newly added as the current production pressure threshold.
As a modification of the above embodiment, in S240, the current production pressure threshold of the station is calculated by the following formula:
wherein De gu Representing the current production pressure threshold, n, of a station gu in a group of stations group Representing a set of stationsTotal number of stations in group, gu group Is the number of the station in the station group, s group Indicating station u group Is(s) is (are) a unit speed gu Indicating the current processing speed of the station gu,indicating station gu group Current processing speed.
Because the number of the working procedures born by each working station is different, each working procedure comprises a plurality of working stations working simultaneously, for example, the working procedures of singeing, desizing, preshrinking and the like are involved in the post-finishing of denim, when the semi-mechanized production is carried out manually, the unit speeds of different working stations are different, the current production pressure threshold value of each working station in the working group is different, the efficiency of a single working station and the efficiency of the whole working group are comprehensively considered, the influence of the reaction working station with more accurate production pressure threshold value in the working group is obtained, and in the formula, gu group As a variable, gu is also the number of the stations in the station group, and the production pressure threshold is calculated for the station gu in the formula.Representing the maximum unit speed in the group of stations.
As an improvement of the foregoing embodiment, in S300, the selecting, according to the delivery pressure threshold of the garment style and the current production pressure threshold of each station in the station group, a plurality of stations from the station groups corresponding to each process includes:
if it isThe stations selected from the group of stations satisfy:
otherwise, the stations selected from the station group satisfy:
wherein P is b Indicating the production quantity of jeans wear in the b-th batch, and Group indicating the total number of work groups, that is, the total number of processes; p (P) k Indicating the number of clothing items produced in the kth batch, gi indicating the number of stations selected from the group of stations, de gi Representing the current production pressure threshold for station gi; max () represents maximum value, min () represents minimum value, mean () represents average value.
It should be noted that the number of the substrates,indicating the production time of jeans wear of the b-th batch produced by the station gu in the station group,/->The average production time of producing jeans in each batch by the stations gu in the station group is shown; />Representing the estimated production time of the garment pattern at the kth lot for the station gu in the station group due to De gu Is a theoretical value, obtained->Is a predicted value; />Representing minimum production time of each batch in the clothing style produced by the station gu in the station group; />The maximum production time for each batch in the garment pattern produced by the stations gu in the station group is shown.
As a modification of the above embodiment, the expression of the objective function is:
wherein F is 1 Representing an objective function that minimizes production balance, N is the total number of stations in the station cluster, i is the station number, Q i Indicating the duty ratio of station i, PT i Representing the sum of the processing time length of the working procedure completed by the station i; beta and gamma are weights, beta is used for adjusting the importance of station load, and gamma is used for adjusting the importance of processing time length; k represents the batch number of the clothing style, mk is the production quantity of the kth batch of the clothing style, n i The total number of working procedures for the clothing style in the working position i, j is the number of the working procedures, q ij The j-th working procedure for clothing style occupies the load ratio of the working position i, t ij The processing time of the j-th procedure of the clothing style in the station i is shown.
The load ratio of the station i is the ratio of the processing speed to the unit speed after the garment pattern is processed by the station, and the ratio of the throughput and the maximum yield of the station is represented; the j-th process of the clothing style occupies the load ratio q of the station i ij The greater the processing time t of station i ij The larger the weight gamma can be adjusted according to the delivery emergency degree, the load ratio of each station can be balanced by adjusting the weight beta on the premise of meeting the delivery time, the whole production efficiency is improved, and the proper station is selected for each procedure by the genetic annealing algorithm, so that the production balance degree is minimum.
As a modification of the above embodiment, before S100, the method further includes:
s101, responding to style design operation, and displaying a style design interface of jeans wear; the design interface comprises a design material library and a design style library, wherein the design material library comprises a plurality of design materials, the design style library comprises a plurality of basic design styles, the basic design styles are formed by combining and configuring a plurality of design materials in advance, and the design materials comprise at least one single-pixel outline drawing;
s102, responding to the design operation of carrying out combined design on a design material library and a design style library in a style design interface, and generating a designed jean clothing style chart; wherein the design operation includes: selecting a basic design style from the design style library, adding design materials in the design material library to the basic design style, and deleting and modifying the design materials in the basic design style;
in some embodiments, the basic design style provides basic style design elements of the jeans wear, the design material library comprises design materials in the basic design style, and the design materials form the jeans wear style by matching with the basic design style; the user selects a basic design style from the style design interface, and adjusts and/or supplements design materials in the basic design style to form a final jean clothing style. And disassembling the basic design style into a plurality of design materials after the jeans wear style is configured, wherein each design material corresponds to one part of the jeans wear.
In step S102, the user selects a basic design style from the design style library in the style design interface, adjusts and combines design materials in the basic design style to form a jean garment style with personalized features, the designed jean garment style drawing includes a plurality of single-pixel contour drawings, and the user can identify each design material in the jean garment style drawing based on the single-pixel contour drawings.
S103, corresponding procedures are set on each design material in the jean clothing style graph in response to the setting operation in the production parameter interface, so that the designed clothing style is obtained, and the production quantity and the delivery time of the clothing style are set.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a digital production simulation system for jeans wear provided by the present invention, corresponding to the method of fig. 1, the system includes:
at least one processor;
at least one memory for storing at least one program;
the at least one program, when executed by the at least one processor, causes the at least one processor to implement the digital production simulation method for jeans wear as described in any one of the above embodiments.
The content in the method embodiment is applicable to the system embodiment, the functions specifically realized by the system embodiment are the same as those of the method embodiment, and the achieved beneficial effects are the same as those of the method embodiment.
The Processor may be a Central-Processing Unit (CPU), other general-purpose Processor, digital-Signal-Processor (DSP), application-Specific-Integrated-Circuit (ASIC), field-Programmable-Gate array (FPGA), or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is a control center of the digital production simulation system of the jeans wear, and connects various parts of the digital production simulation system operable devices of the entire jeans wear using various interfaces and lines.
The memory may be used to store the computer program and/or module, and the processor may implement various functions of the digital production simulation system of the jeans wear by running or executing the computer program and/or module stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart-Media-Card (SMC), secure-digital (SD) Card, flash Card (Flash-Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
While the present invention has been described in considerable detail and with particularity with respect to several described embodiments, it is not intended to be limited to any such detail or embodiments or any particular embodiment, but is to be considered as providing a broad interpretation of such claims by reference to the appended claims in light of the prior art and thus effectively covering the intended scope of the invention. Furthermore, the foregoing description of the invention has been presented in its embodiments contemplated by the inventors for the purpose of providing a useful description, and for the purposes of providing a non-essential modification of the invention that may not be presently contemplated, may represent an equivalent modification of the invention.
Claims (7)
1. A method for simulating the digital production of jeans wear, said method comprising the steps of:
acquiring a clothing style of jeans clothing, and setting production quantity and delivery time for the clothing style, and determining a delivery pressure threshold of the clothing style based on the production quantity and the delivery time; the delivery pressure threshold value characterizes the urgency of delivery;
acquiring working procedures for processing the clothing patterns, matching all working stations to obtain working station groups corresponding to all working procedures, acquiring unit speeds and current processing speeds of all working stations in the working station groups, and obtaining current production pressure thresholds of all working stations in the working station groups based on the unit speeds and the processing speeds; the unit speed is the maximum processing speed of the station; the production pressure threshold characterizes the degree of yield improvement;
according to the delivery pressure threshold of the clothing style and the current production pressure threshold of each station in the station group, respectively selecting a plurality of stations from the station group corresponding to each procedure, and forming a station cluster by the selected stations according to the corresponding procedures;
acquiring processing parameters of a station cluster, establishing an objective function for minimizing production balance according to the processing parameters of the station cluster and the production quantity of the clothing style, and solving the objective function by adopting a genetic annealing algorithm to obtain a digital simulation result of the clothing style; wherein, the processing parameters comprise the number and working procedures of each station in the station cluster; the production balance represents the processing time length of the clothing style and the load ratio of the station clusters; the digital simulation result comprises the load ratio of each station in the station cluster and the processing time length for processing the clothing style.
2. The method of simulating digital production of jeans wear according to claim 1, wherein said determining a delivery pressure threshold for the wear style based on the production quantity and delivery time comprises:
acquiring current time, and taking the duration of the current time distance delivery time as time redundancy;
calculating to obtain a delivery pressure threshold of the clothing style according to the following formula;
wherein T is 0 Representing the time redundancy of the clothing style, K representing the total batch of the clothing style, K representing the batch number of the clothing style, B representing the batch number of the jeans clothing, B representing the total batch of the jeans clothing processed in the past time period, bp representing the p-th jeans in the B-th batch, K b Represents the total number of jeans wear in lot b, n bp Representing the number of parts used to manufacture the p-th jeans in the b-th lot, T bp Representing the processing time of the p-th jeans in the b-th batch, m representing the total number of parts used to process the fashion of the garment, avg n Representing the average number of parts used to manufacture a jeans garment.
3. The method for simulating digital production of jeans wear according to claim 2, wherein the step of obtaining the clothing style, obtaining the work station group corresponding to each step from all the work stations, obtaining the unit speed and the current processing speed of each work station in the work station group, and obtaining the current production pressure threshold of each work station in the work station group based on the unit speed and the processing speed comprises the steps of:
obtaining a design model of the clothing style, and analyzing a data packet of the jeans clothing according to the design model; wherein the design model comprises a design drawing, a clothing component and a clothing component; the data packet comprises geometric parameters of each clothing component and each stitch in jeans wear;
based on the corresponding working procedures of each clothing component in the data packet, matching a plurality of work groups from all work stations; each working procedure is provided with a corresponding station group, and the station group comprises a plurality of stations;
acquiring unit speeds of all stations in a station group, and generating production process parameters of the station group based on the data packet and the unit speeds; the production process parameters comprise unit speeds corresponding to all stations in the station group;
the current processing speed of each station in the station group is obtained, and the current production pressure threshold of the station is obtained based on the current processing speed and the unit speed of each station.
4. A digital production simulation method of jeans wear according to claim 3, wherein the current production pressure threshold of the workstation is calculated by the following formula:
wherein De gu Representing the current production pressure threshold, n, of a station gu in a group of stations group Indicating the total number of stations in the group of stations, gu group Is the number of the station in the station group, s group Indicating station u group Is(s) is (are) a unit speed gu Indicating the current processing speed of the station gu,indicating station gu group Current processing speed.
5. The simulation method for digital production of jeans wear according to claim 4, wherein the selecting a plurality of stations from the station group corresponding to each process according to the delivery pressure threshold of the wear style and the current production pressure threshold of each station in the station group respectively comprises:
if it isThe stations selected from the group of stations satisfy:
otherwise, the stations selected from the station group satisfy:
wherein P is k Representing the number of clothing styles produced in the kth batch, and Group represents the total number of work groups, that is, the total number of procedures; p (P) k Indicating the number of clothing items produced in the kth batch, gi indicating the number of stations selected from the group of stations, de gi Representing the current production pressure threshold for station gi; max () represents maximum value, min () represents minimum value, mean () represents average value.
6. The simulation method for the digital production of jeans wear according to claim 5, wherein the expression of the objective function is:
wherein F is 1 Representing an objective function that minimizes production balance, N is the total number of stations in the station cluster, i is the station number, Q i Indicating the duty ratio of station i, PT i Representing the sum of the processing time length of the working procedure completed by the station i; beta and gamma are weights, beta is used for adjusting the importance of station load, and gamma is used for adjusting the importance of processing time length; k represents the batch number of the clothing style, mk is the production quantity of the kth batch of the clothing style, n i The total number of working procedures for the clothing style in the working position i, j is the number of the working procedures, q ij The j-th working procedure for clothing style occupies the load ratio of the working position i, t ij The processing time of the j-th procedure of the clothing style in the station i is shown.
7. A digital production simulation system for jeans wear, comprising:
at least one processor;
at least one memory for storing at least one program;
when the at least one program is executed by the at least one processor, the at least one processor implements the digital production simulation method of jeans wear as claimed in any one of claims 1 to 6.
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20060085291A1 (en) * | 2002-10-11 | 2006-04-20 | Tdk Corporation | Inventory management method, inventory management system, and inventory management program |
CN103679310A (en) * | 2012-09-12 | 2014-03-26 | 广州春晓信息科技有限公司 | Method and device for simulating production line |
CN114687078A (en) * | 2020-12-31 | 2022-07-01 | 杰克科技股份有限公司 | Sewing process parameter control system and method |
US20220317644A1 (en) * | 2020-02-28 | 2022-10-06 | Boe Technology Group Co., Ltd. | Production programming system and method based on nonlinear program model, and computer-readable storage medium |
CN115757582A (en) * | 2022-11-25 | 2023-03-07 | 浙江理工大学 | Multi-station working hour data acquisition method and system for garment assembly line |
CN117151448A (en) * | 2023-10-26 | 2023-12-01 | 合肥新振智能科技有限公司 | Intelligent workshop management system based on digital production platform |
-
2024
- 2024-02-05 CN CN202410161265.3A patent/CN117875081B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20060085291A1 (en) * | 2002-10-11 | 2006-04-20 | Tdk Corporation | Inventory management method, inventory management system, and inventory management program |
CN103679310A (en) * | 2012-09-12 | 2014-03-26 | 广州春晓信息科技有限公司 | Method and device for simulating production line |
US20220317644A1 (en) * | 2020-02-28 | 2022-10-06 | Boe Technology Group Co., Ltd. | Production programming system and method based on nonlinear program model, and computer-readable storage medium |
CN114687078A (en) * | 2020-12-31 | 2022-07-01 | 杰克科技股份有限公司 | Sewing process parameter control system and method |
CN115757582A (en) * | 2022-11-25 | 2023-03-07 | 浙江理工大学 | Multi-station working hour data acquisition method and system for garment assembly line |
CN117151448A (en) * | 2023-10-26 | 2023-12-01 | 合肥新振智能科技有限公司 | Intelligent workshop management system based on digital production platform |
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