Textile ERP (Enterprise Resource Planning)-based dynamic calculation method for yarn stock of yarn edge bin

Abstract

The invention relates to a dynamic calculation method for yarn stock of a yarn edge bin based on spinning ERP (Enterprise Resource Planning). The method comprises the following steps: S1, dynamically calculating yarn consumption data; and S2, dynamically calculating the yarn stock of the yarn edge bin according to the yarn consumption data. According to the invention, the dynamic calculation of the yarn consumption data is realized, and the yarn stock of the yarn edge bin is further dynamically calculated according to the data. According to the method, the yarn consumption condition is dynamically tracked in real time, and accurate adjustment is performed according to the bill of material of the gray fabric, the production process parameters of the production machine and the error parameter proportion, so that the calculated consumption value of the yarn can be tightly attached to the actual consumption quantity, and the purpose of accurately mastering the yarn stock of the yarn edge bin in real time is achieved; the problem that yarn stock quantity management is difficult is effectively solved.

Description

Technical Field

[0001] The invention belongs to the field of digital information technology, and in particular relates to a method for dynamically calculating yarn inventory in a line-side warehouse based on textile ERP. Background Art

[0002] In the field of textile industry, yarn is the core raw material, and its inventory management occupies a vital position in the operation of textile ERP system. Specifically, yarn inventory consists of two major components: warehouse and line warehouse. Inventory changes in the warehouse can be tracked and calculated in real time with the help of documents in the textile ERP system; while the line warehouse involves multiple links such as picking up materials, returning materials and weaving blanks, among which picking up materials and returning materials can also be recorded in detail through ERP documents. However, the amount of yarn consumed in the weaving stage cannot be accurately recorded directly through documents at present, and can only rely on specialized personnel to conduct regular inventory of yarn in the line warehouse. For example Figure 1 As shown in Figure 1, this process relies on regularly scheduled staff to update the inventory data of the line warehouse through their inventory counting work. It is worth noting that due to the high frequency of such inventory counting work, the corresponding labor cost is also relatively high.

[0003] However, this inventory-taking process faces two challenges in practice: On the one hand, setting the inventory-taking frequency too high will inevitably lead to excessive human resource consumption, thereby increasing the company's operating costs; on the other hand, setting the inventory-taking frequency too low can lead to significant deviations in lineside inventory data, negatively impacting the company's production planning, order acceptance, and procurement strategies. Therefore, how to efficiently and accurately manage lineside inventory has become a critical issue for modern manufacturing, especially for companies implementing lean production models.

[0004] Currently, the technologies related to lineside warehouse inventory management have the following significant shortcomings:

[0005] 1. The yarn inventory management of the textile industry's line-side warehouses faces severe challenges. It is difficult for companies to grasp the inventory status of yarn in real time, which poses a considerable problem for the company's operations and decision-making.

[0006] 2. Management costs remain high, and there is a significant lag in data updates, which makes it difficult to meet the company's high requirements for real-time decision-making information.

[0007] 3. Inventory data updates mainly rely on regularly scheduled personnel counts, which is inefficient and requires frequent human resource investment, thereby increasing overall costs. Summary of the Invention

[0008] In view of the shortcomings of the current relevant existing technologies, the present invention proposes a dynamic calculation method for yarn inventory in line-side warehouses based on textile ERP. This solution can accurately count the yarn inventory in line-side warehouses in real time, significantly improve the accuracy of yarn inventory data in line-side warehouses, and then optimize the management and utilization of yarn resources, effectively helping enterprises reduce operating costs.

[0009] To achieve the above object, the present invention provides a method for dynamically calculating yarn inventory in a line-side warehouse based on textile ERP, which comprises at least the following steps:

[0010] Step S1, dynamically calculate yarn consumption data; wherein, step S1 includes

[0011] S11. Create a grey fabric task order and enter the corresponding bill of materials into the textile ERP system;

[0012] S12. Collect materials from the line warehouse according to the bill of materials for the grey cloth and arrange machine production;

[0013] S13, when the production is finished, save the production data and material composition information at that moment;

[0014] S14. The consumption data formed by the saved production time and material group information is provided to the line side warehouse;

[0015] Step S2: dynamically calculating the yarn inventory in the outlet warehouse based on the yarn consumption data.

[0016] Furthermore, the information entered into the textile ERP system in step S11 includes at least one or more of the number of yarn heads, stretch coefficient, yarn D number and fancy yarn ratio.

[0017] Furthermore, in step S12 arranging the machine production process, the production density of the grey fabric and the warp let-off of the warp head are recorded.

[0018] Furthermore, when the fabric is produced in step S13, the production density of the grey fabric and the warp let-off data as well as the relationship with the bill of materials are recorded.

[0019] Furthermore, after weaving multiple batches, the dynamic consumption calculation value is compared with the actual line and side warehouse consumption data, and the error ratio parameter of the formula is adjusted to make the formula calculation consistent with the actual consumption.

[0020] Furthermore, the yarn consumption data of the grey cloth is dynamically calculated, and the yarn edge warehouse inventory data is obtained in real time.

[0021] Furthermore, the yarn consumption of the side warehouse is dynamically calculated as follows:

[0022] Ground card yarn consumption: Ln = fabric length (m) * [production density * Ln warp let-off / 9600 * (number of bobbins / stretch coefficient) * yarn D number / 9000] / 1000

[0023] Grey cloth length (m): the length of the grey cloth when it is laid, in meters;

[0024] Production density: the number of rows of yarn per unit length (cm), which is manually entered during production;

[0025] Ln let-off: Let-off refers to the length of the warp yarn delivered from the warp beam per unit time (mm / lact;

[0026] Production density*Ln let-off / 9600: represents how many meters of yarn need to be fed per meter of grey fabric;

[0027] Number of yarns in the warp: the number of yarns in the warp during warping, entered in the production BOM;

[0028] Stretch coefficient: the stretch rate of yarn, entered into production BOM;

[0029] Yarn D number: The weight of 9000m of yarn at the specified moisture regain, entered in the production BOM

[0030] 1000: Weight conversion, from g to kg;

[0031] Consumption of fancy yarn: (weight of grey fabric - ∑consumption of ground yarn) * ratio of fancy yarn / 100

[0032] Grey cloth weight: the weight of the grey cloth when it is dropped;

[0033] Spindle yarn ratio: the ratio of yarn to spindle yarn, entered in production BOM;

[0034] The consumption of each yarn in the grey fabric can be calculated through the corresponding production BOM.

[0035] Furthermore, the dynamic calculation method of yarn inventory in the line warehouse is:

[0036] Yarn A stock = ∑A material collection quantity - ∑A material return quantity - ∑[(bom1A consumption quantity * M1) + (bom2A consumption quantity * M2) + ...]

[0037] ∑A picking quantity: the total picking quantity of yarn A;

[0038] ∑A material return quantity: the total amount of all material returns for yarn A;

[0039] bomnA consumption*M1: Calculate the consumption of yarn A in all grey fabrics*Mn according to the formula;

[0040] Mn: Error ratio, entered into production BOM.

[0041] Furthermore, some yarn will be lost in the machine modification and weaving stages. The temperature difference between morning and evening will affect the physical properties of the yarn and thus affect the consumption calculation. Therefore, the dynamic consumption calculation value of the yarn will deviate from the actual yarn consumption value. When maintaining the production BOM, the error ratio value is also maintained to reduce the deviation between the dynamic consumption calculation and the actual consumption.

[0042] Furthermore, (1) the production department loads materials and produces according to the production BOM of the model number;

[0043] (2) Record the production data of the machine and the BOM information corresponding to the model number when the cloth is dropped;

[0044] (3) After production is completed, the line warehouse obtains the theoretical yarn consumption data of the grey cloth;

[0045] (4) Carry out inventory at the line warehouse to confirm the actual consumption of the grey fabric during production. By comparing the theoretical consumption with the actual consumption, the error ratio that needs to be adjusted is obtained;

[0046] (5) Maintain the error ratio in the production BOM so that the theoretical yarn consumption of the grey cloth is close to the actual yarn consumption.

[0047] The present invention adopts the above-mentioned technical solution to achieve dynamic calculation of yarn consumption data, and further dynamically calculate the yarn inventory in the side warehouse based on this. This invention tracks yarn consumption in real time and accurately adjusts it according to the bill of materials of the grey fabric, the production process parameters of the production machine, and the error parameter ratio, so that the calculated yarn consumption value can closely match the actual consumption quantity, thereby achieving the purpose of real-time and accurate grasp of the yarn inventory in the side warehouse, effectively solving the problem of difficult yarn inventory quantity management. Its significant advantages include but are not limited to the following:

[0048] 1. Simple configuration and easy to understand: The calculation formula of the present invention is clear and concise, which lowers the threshold for use and facilitates wide promotion and application.

[0049] 2. Combining with production data to effectively reduce the error between theory and practice. By closely combining with production data, the present invention can significantly reduce the error value in the calculation process and improve the accuracy of the calculation results.

[0050] 3. Detailed records of grey fabric production and bill of materials data are kept during the fabric drop. This is to prevent the adjustment of parameters during subsequent production processes from affecting the accuracy of historical consumption data calculations, ensuring data continuity and accuracy.

[0051] 4. By flexibly adjusting the error ratio parameter, the calculated consumption value is made consistent with the actual consumption value. This feature further improves the accuracy and reliability of the calculation formula of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0053] Figure 1 It is a schematic diagram of the architecture of the prior art;

[0054] Figure 2 It is a schematic diagram of the architecture of the present invention including the dynamic consumption data of yarn;

[0055] Figure 3 It is a consumption calculation flow chart of the present invention;

[0056] Figure 4 It is a schematic diagram of a scenario embodiment of the present invention. DETAILED DESCRIPTION

[0057] Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent like or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present invention, as detailed in the appended claims.

[0058] like Figure 1 and Figure 2 As shown, the first aspect of this embodiment provides that the present invention provides a method for dynamically calculating yarn inventory in a line-side warehouse based on textile ERP, comprising at least the following steps:

[0059] Step S1, dynamically calculate yarn consumption data; wherein, step S1 includes

[0060] S11. Create a grey fabric task order and enter the corresponding bill of materials into the textile ERP system;

[0061] S12. Collect materials from the line warehouse according to the bill of materials for the grey cloth and arrange machine production;

[0062] S13, when the production is finished, save the production data and material composition information at that moment;

[0063] S14. The consumption data formed by the saved production time and material group information is provided to the line side warehouse;

[0064] Step S2: dynamically calculating the yarn inventory in the outlet warehouse based on the yarn consumption data.

[0065] As a preferred embodiment, in this embodiment, the information entered into the textile ERP system in step S11 includes at least one or more of the number of yarn heads, stretch coefficient, yarn D number and fancy yarn ratio.

[0066] As a preferred implementation, in this embodiment, during the production process of the machine arranged in step S12, the production density of the grey cloth and the warp let-off amount of the warp head are recorded.

[0067] As a preferred embodiment, in this embodiment, the production density of the grey cloth and the warp let-off data as well as the relationship with the bill of materials are recorded when the cloth is produced in step S13.

[0068] As a preferred implementation, in this embodiment, after multiple batches of weaving are completed, the dynamic consumption calculation value is compared with the actual line and side warehouse consumption data, and the error ratio parameter of the formula is adjusted to make the formula calculation consistent with the actual consumption.

[0069] As a preferred implementation, in this embodiment, the yarn consumption data of the grey cloth is dynamically calculated, and the yarn edge warehouse inventory data is obtained in real time.

[0070] As a preferred embodiment, in this embodiment, the warp knitting machine mainly includes a guide bar, a jacquard bar, a pattern bar, a ground bar, a weft insertion bar, and a pressing bar. This patent mainly involves the pattern bar and the ground bar, so the pattern bar usage and the ground bar usage are used in the consumption calculation;

[0071] The dynamic calculation method of yarn consumption in the side warehouse is:

[0072] Ground card yarn consumption: Ln = fabric length (m) * [production density * Ln warp let-off / 9600 * (number of bobbins / stretch coefficient) * yarn D number / 9000] / 1000

[0073] Grey cloth length (m): the length of the grey cloth when it is laid, in meters;

[0074] Production density: the number of rows of yarn per unit length (cm), which is manually entered during production;

[0075] Ln let-off: Let-off refers to the length of the warp yarn delivered from the warp beam per unit time (mm / lact);

[0076] Production density*Ln let-off / 9600: represents how many meters of yarn need to be fed per meter of grey fabric;

[0077] Number of yarns in the warp: the number of yarns in the warp during warping, entered in the production BOM;

[0078] Stretch coefficient: the stretch rate of yarn, entered into production BOM;

[0079] Yarn D number: The weight of 9000m of yarn at the specified moisture regain, entered in the production BOM

[0080] 1000: Weight conversion, from g to kg;

[0081] Consumption of fancy yarn: (weight of grey fabric - ∑consumption of ground yarn) * ratio of fancy yarn / 100

[0082] Grey cloth weight: the weight of the grey cloth when it is dropped;

[0083] Spindle yarn ratio: the ratio of yarn to spindle yarn, entered in production BOM;

[0084] The consumption of each yarn in the grey fabric can be calculated through the corresponding production BOM.

[0085] As a preferred embodiment, the dynamic calculation method of yarn inventory in the side warehouse in this embodiment is:

[0086] Yarn A stock = ∑A material collection quantity - ∑A material return quantity - ∑[(bom1A consumption quantity * M1) + (bom2A consumption quantity * M2) + ...]

[0087] ∑A picking quantity: the total picking quantity of yarn A;

[0088] ∑A material return quantity: the total amount of all material returns for yarn A;

[0089] bomnA consumption*M1: The consumption of yarn A in all grey fabrics is calculated by the formula *Mn; n is a natural number greater than or equal to 1;

[0090] Mn: Error ratio, entered into production BOM.

[0091] As a preferred embodiment, in this embodiment, there will be some yarn loss in the machine modification stage and the weaving stage. Environmental factors such as the temperature difference between morning and evening will affect the physical properties of the yarn (such as elasticity and length) and thus affect the consumption calculation. Therefore, the dynamic consumption calculation value of the yarn and the actual yarn consumption value will deviate. When maintaining the production BOM, the error ratio value is also maintained to reduce the deviation between the dynamic consumption calculation and the actual consumption.

[0092] This example aims to explain in detail a material management method in a production process through a specific scenario case:

[0093] (1) First, the production department will load materials according to the production bill of materials (BOM) of a specific model number A to start the production process. This means that the production staff needs to prepare materials accurately according to the materials and quantities listed in the BOM to ensure that production activities can proceed smoothly.

[0094] (2) During the production process, when the grey fabric is dropped from the machine, the relevant personnel will record the production data of the machine in detail, including the production time, quantity and BOM information corresponding to the model number A. This data will be used for subsequent production management and quality control to ensure that each batch of products can be traced back to the specific production conditions and material usage.

[0095] (3) After production is completed, the staff in the line warehouse will obtain the theoretical yarn consumption data of the grey cloth. This step is to ensure that the theoretical material consumption can be compared with the material consumption in actual production, so as to evaluate the efficiency and accuracy of the production process.

[0096] (4) Next, the line warehouse will conduct an inventory to confirm the actual consumption of the grey fabric during production. By comparing the theoretical consumption with the actual consumption, the staff can calculate the difference between the two and derive the error ratio that needs to be adjusted. This error ratio reflects the possible waste or shortage of materials in the production process, which is of great significance for optimizing the production process and reducing costs.

[0097] (5) Finally, based on the calculated error ratio, the production department will maintain and adjust the production BOM accordingly. In this way, the theoretical yarn consumption of the grey fabric can be made closer to the actual yarn consumption, thereby improving the accuracy and efficiency of the production process. This continuous optimization process helps to reduce waste, improve product quality, and ultimately achieve reduced production costs and increased production efficiency.

[0098] The present invention utilizes the aforementioned technical solution to dynamically calculate yarn consumption data and, based on this, dynamically calculate yarn inventory in the side warehouse. This invention dynamically tracks yarn consumption in real time and makes precise adjustments based on the bill of materials for the grey fabric, the production process parameters of the production machine, and the error parameter ratio. This ensures that the calculated yarn consumption value closely matches the actual consumption quantity, thereby achieving real-time and accurate control of yarn inventory in the side warehouse, effectively solving the problem of difficult yarn inventory quantity management.

[0099] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A method for dynamically calculating yarn inventory in a line warehouse based on textile ERP, characterized in that: At least the following steps are included: Step S1, dynamically calculating yarn consumption data; wherein, step S1 includes S11. Create a grey fabric task order and enter the bill of materials corresponding to the grey fabric into the textile ERP system; S12. Collect materials from the line warehouse according to the bill of materials of the grey cloth and arrange the machine production; S13, when the production is finished, save the production data and material composition information at that moment; S14. The consumption data formed by the saved production time and material group information is provided to the line side warehouse; Step S2: dynamically calculate the yarn inventory in the outlet warehouse according to the yarn consumption data.

2. The method according to claim 1, characterized in that: The information entered into the textile ERP system in step S11 includes at least one or more of the comb type (pattern comb / ground comb), warp feed type, serial number, material code, batch number, number of warp ends, stretch coefficient, yarn D number and pattern yarn ratio; wherein the comb type includes pattern comb and / or ground comb.

3. The method according to claim 1, characterized in that: In step S12, during the machine production arrangement, the production density of the grey cloth and the warp let-off amount of the warp head are recorded.

4. The method according to claim 1, characterized in that: When the fabric is produced in step S13, the production density of the grey fabric and the warp let-off data as well as the relationship with the bill of materials are recorded.

5. The method according to claims 1 to 4, characterized in that: After weaving multiple batches, the dynamic consumption calculation value is compared with the actual line and side warehouse consumption data, and the error ratio parameter of the formula is adjusted to make the formula calculation consistent with the actual consumption.

6. The method according to claim 5, characterized in that: Dynamically calculate the yarn consumption data of the grey cloth and obtain the yarn warehouse inventory data in real time.

7. The method according to claim 6, characterized in that: The dynamic calculation method of yarn consumption in the side warehouse is: Ground card yarn consumption: Ln = grey cloth length (m) * [production density * Ln warp amount / 9600 * (number of discs / stretch coefficient) * yarn D number / 9000] / 1000 Grey cloth length (m): the length of the grey cloth when it is laid, in meters; Production density: the number of rows of yarn per unit length (cm), entered manually during production; Ln let-off: Let-off refers to the length of the warp yarn sent out from the warp beam per unit time (mm / lacquer; Production density*Ln warp feed / 9600: represents how many meters of yarn are needed to feed per meter of grey cloth; Number of yarns in the warp: the number of yarns in the warp during warping, entered in the production BOM; Stretch coefficient: the stretch rate of yarn, entered into production BOM; Yarn D number: The weight of 9000m of yarn at the specified moisture regain, entered in the production BOM 1000: weight conversion, from g to kg; Consumption of fancy yarn: (weight of grey fabric - ∑consumption of ground yarn)*proportion of fancy yarn / 100 Grey cloth weight: the weight of grey cloth when it is dropped; Fancy yarn ratio: the ratio of yarn to fancy yarn, entered in production BOM; The consumption of each yarn of the grey cloth can be calculated through the corresponding production BOM.

8. The method according to claim 7, characterized in that: The dynamic calculation method of yarn inventory in the line warehouse is: A yarn inventory = ∑A material collection quantity - ∑A material withdrawal quantity - ∑[(bom1A consumption quantity * M1) + (bom2A consumption quantity * M2) + ...] ∑A pick quantity: the total pick quantity of yarn A; ∑A material return quantity: the total amount of all material returns of yarn A; bomnA consumption*M1: The consumption of yarn A in all grey fabrics is calculated by the formula*Mn; n is a natural number greater than or equal to 1; Mn: Error ratio, entered into production BOM.

9. The method according to claim 8, characterized in that: There will be some yarn loss in the machine modification and weaving stages. The temperature difference between morning and evening will affect the physical properties of the yarn and thus affect the consumption calculation. Therefore, there will be a deviation between the dynamic consumption calculation value and the actual yarn consumption value. When maintaining the production BOM, the error ratio value is also maintained to reduce the deviation between the dynamic consumption calculation and the actual consumption.

10. The method according to any one of claims 1 to 9, characterized in that: (1) The production department loads materials and produces according to the production BOM of the model number; (2) When placing the cloth, record the production data of the machine and the BOM information corresponding to the model number; (3) After production is completed, the line warehouse obtains the theoretical yarn consumption data of the grey cloth; (4) Take inventory at the line warehouse to confirm the actual consumption of the grey cloth during production. By comparing the theoretical consumption with the actual consumption, the error ratio that needs to be adjusted is obtained. (5) Maintain the error ratio in the production BOM so that the theoretical yarn consumption of the grey cloth is close to the actual yarn consumption.

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