CN112613774A - MRP algorithm based on data feedback - Google Patents
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Abstract
The invention provides a data feedback-based MRP algorithm, which comprises the following steps: extracting a production product code according to the production task; acquiring a BOM list according to the product code; acquiring the current stock, the reservation quantity and the stock in-transit quantity according to the material codes; calculating a preliminary MRP demand; extracting the yield of each product according to the product code; adjusting the primary MRP demand according to the yield of each product to obtain the primary calibrated MRP demand; extracting the actual material demand and the planned material usage of each product produced n years before the current year serving as a reference according to the material codes; calculating the actual planned quantity ratio of the demands of the products in n years according to the actual material demand of the products and the planned material usage; calculating the actual planned quantity ratio of the demands of the current year according to the actual planned quantity ratio of the demands of each product in n years; and acquiring the final MRP demand according to the actual plan quantity ratio of the demand in the current year, so that the acquired MRP value is close to the actual material demand, and the purchasing plan can be optimized.
Description
Technical Field
The invention relates to the technical field of material plan management, in particular to a MRP algorithm based on data feedback.
Background
The material demand plan (MRP) refers to the order of the planned time of each item according to the relationship between the membership and quantity of each layer of the item in the product structure, taking each item as the plan object, taking the completion period as the time reference, and distinguishing the order of the planned time of each item according to the length of the lead period, and is a material plan management mode in the industrial manufacturing enterprise. MRP is a practical technique for making a production plan of a product according to market demand prediction and a customer order, then generating a schedule plan based on the product, composing a material structure table and an inventory condition of the product, and calculating a required amount and a required time of a required material by a computer, thereby determining a processing schedule and an ordering schedule of the material.
The data of the inventory state file in the MRP mainly comprises two parts, wherein one part is static data, and the data is determined before the MRP is operated, such as the serial number, description, lead time, safety inventory and the like of materials; the other part is dynamic data such as total demand, inventory, net demand, and planned delivery (order) volume. MRPs continuously update changing dynamic data at runtime. In MRP, several main dynamic data include: total demand (gross demands), which is determined by MPS (production plan) if it is a product-grade material, and which comes from a planned order volume of an upper-layer material (parent) if it is a part-grade material; estimated quantity of goods (scheduled receipts), which can also be called as in-transit quantity, namely planned to be put in storage at a certain moment but still in production or purchase, can be used as MRP; the existing number (OnHand) represents the inventory available at the beginning of the period from the end of the last period, and the formula can be represented as the existing number, namely the existing number at the end of the last period plus the predicted quantity of goods in the period-the total demand of the period; net demand (NetRequirements), which results when the current number plus the predicted arrival cannot meet the demand, can be expressed as a formula, where the net demand is the current number plus the predicted arrival-total demand; planned order take (planendorderreceipts), when the net demand is positive, an order quantity is required to be taken to make up for the net demand, the planned order quantity depends on the consideration of order lot, and if a batch-by-batch order mode is adopted, the planned order quantity is the net demand quantity; planned order delivery (planendorder Release) which is equal to the planned order receiving amount but is advanced in time by a time period, namely the order lead, and the order date is the planned order receiving date minus the order lead.
The conventional MRP is generally obtained by simply calculating the total demand, the predicted goods quantity and the net demand, but the calculated value is greatly different from the value required in the actual production demand, and meanwhile, the production loss among different products in the production process is not considered.
Disclosure of Invention
The invention provides an MRP algorithm based on data feedback, which solves the problem that the existing MRP is obtained by simply calculating the total demand, the predicted goods quantity and the net demand, so that the difference between the calculated value and the value required in the actual production demand is large, the obtained MRP value is close to the actual material demand, and the purchasing plan can be optimized.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
the invention discloses a data feedback-based MRP algorithm, which comprises the following steps: extracting a production product code according to the production task; acquiring a BOM list according to the product codes, and extracting material codes, quantity and units of all materials in the BOM list; acquiring the current stock, the reservation quantity and the stock in-transit quantity according to the material codes; calculating a preliminary MRP demand according to an MRP calculation formula; extracting the yield of each product according to the product code; adjusting the primary MRP demand according to the yield of each product to obtain a primary calibration MRP demand; extracting the actual material demand and the planned material usage of each product produced n years before the current year serving as a reference according to the material codes; calculating the actual planned quantity ratio of the demands of the products in n years according to the actual material demand and the planned material usage of the products; calculating the actual planned quantity ratio of the demands of the current year according to the actual planned quantity ratio of the demands of each product in n years; and acquiring the final MRP demand according to the actual planned demand ratio of the current year.
Further, the preliminary MRP demand is calculated by the formula:
further, the calculation formula of the first-time calibration MRP demand is as follows:
wherein INT is an upward rounding function, and yieldikThe yield of k products in the ith year.
Further, the calculation formula of the demand actual planning quantity ratio is as follows:
further, the final MRP demand is calculated by the following formula:
final MRP demand-first calibrated MRP demand-current year demand actual projected volume ratio.
Further, n is more than or equal to 5.
The beneficial technical effects are as follows:
the invention discloses a data feedback-based MRP algorithm, which comprises the following steps of extracting a product code according to a production task; acquiring a BOM list according to the product codes, and extracting material codes, quantity and units of all materials in the BOM list; acquiring the current stock, the reservation quantity and the stock in-transit quantity according to the material codes; calculating a preliminary MRP demand according to an MRP calculation formula; extracting the yield of each product according to the product code; adjusting the primary MRP demand according to the yield of each product to obtain a primary calibration MRP demand; extracting the actual material demand and the planned material usage of each product produced n years before the current year serving as a reference according to the material codes; calculating the actual planned quantity ratio of the demands of the products in n years according to the actual material demand and the planned material usage of the products; calculating the actual planned quantity ratio of the demands of the current year according to the actual planned quantity ratio of the demands of each product in n years; and obtaining the final MRP demand according to the actual demand plan quantity ratio of the current year, solving the problem that the difference between the calculated numerical value and the required numerical value in the actual production demand is large because the existing MRP is obtained by simply calculating the total demand quantity, the predicted arrived quantity and the net demand quantity, ensuring that the obtained MRP numerical value is closer to the actual material demand, and optimizing the purchasing plan.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a flowchart of an MRP algorithm based on data feedback according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
The preparation of the MRP (material demand plan) requires three key information, MPS (main production plan), BOM (bill of material) and inventory records, and the calculation method of the inventory records constitutes a basic calculation model of the MRP, the inventory records in the MRP are also called MRP tables, and the MRP tables generally include planning factors, rough demand, predicted warehousing quantity, existing inventory quantity, planned order warehousing quantity, and planned order sending quantity.
The invention obtains a more practical MRP value according to MPS (Main production plan), BOM (bill of materials) and inventory records and by combining the product yield and the historical actual usage.
The invention discloses a data feedback-based MRP algorithm, which comprises the following steps:
s1: extracting a production product code according to the production task;
in the embodiment of the invention, according to the production task, the code of the produced product is extracted, and the extraction data is shown in the table 1;
TABLE 1
| Production task numbering | Product coding | Production quantity of products |
| A001 | X001 | 20 |
| A001 | X002 | 10 |
As can be seen from Table 1, two product codes, including X001 and X002, were extracted according to production task A001.
S2: acquiring a BOM list according to the product code, and extracting the material code, the quantity and the unit of each material in the BOM list;
in the embodiment of the invention, according to the product code, the material codes, the quantities and the units of all the materials in the extracted BOM list are as follows:
each product code is X001 and comprises 4P 00101, 2P 00102 and 1P 00103 components, and each product code is X002 and comprises 1P 00201 and 1P 00202 components, and the specific data are shown in Table 2;
TABLE 2
| Product coding | Material coding | Number of BOMs | Production quantity of products | Reservation of parts | Unit of |
| X001 | P00101 | 4 | 20 | 80 | An |
| X001 | P00102 | 2 | 20 | 40 | An |
| X001 | P00103 | 1 | 20 | 20 | Piece |
| X002 | P00201 | 1 | 10 | 10 | Sheet of paper |
| X002 | P00202 | 1 | 10 | 10 | Branch stand |
As can be seen from table 2, the product with product code X001 includes three materials with material codes P00101, P00102 and P00103, and the product with product code X002 includes two materials with material codes P00201 and P00202.
S3: acquiring the current stock, the reservation quantity and the stock in-transit quantity according to the material codes;
in the embodiment of the invention, the current stock quantity, the reservation quantity and the stock in-transit quantity of each material are extracted according to the product code as shown in the table 3,
TABLE 3
| Material coding | Current amount of stock | Number of reservations | In-transit amount of stock preparation |
| P00101 | 23 | 80 | 50 |
| P00102 | 10 | 40 | 50 |
| P00103 | 10 | 20 | 0 |
| P00201 | 0 | 10 | 0 |
| P00202 | 0 | 10 | 0 |
As can be seen from table 3, the current stock of the material with the material code P00101 is 23, the predetermined amount is 80, and the stock quantity in transit is 50; the current stock of the materials with the material codes of P00102 is 10, the preset quantity is 40, and the stock in-transit quantity is 50; the current stock of the material with the material code of P00103 is 10 pieces, the preset quantity is 29 pieces, and the stock preparation quantity is a part in transit; the current stock quantity of the material with the material code of P00201 is zero, the reservation quantity is 10, and the stock in-transit quantity is zero; the current stock of the material with the material code of P00202 is zero, the reservation quantity is 10, and the stock in-transit quantity is zero.
S4: calculating a preliminary MRP demand according to an MRP calculation formula;
the preliminary MRP demand of each material is obtained by using a calculation formula of the preliminary MRP demand, as shown in Table 4,
TABLE 4
| Material coding | Current amount of stock | Number of reservations | Number of prepared materials | Preliminary MRP demand quantity (and calculation) |
| P00101 | 23 | 20 | 50 | 27(＝80-23+20-50) |
| P00102 | 10 | 20 | 50 | 0(＝40-10+20-50) |
| P00103 | 10 | 20 | 0 | 10(20-10+20-0) |
| P00201 | 0 | 10 | 0 | 20(＝10-0+10-0) |
| P00202 | 0 | 10 | 0 | 20(＝10-0+10-0) |
Calculating a formula according to the primary MRP demand to obtain 27 primary MRP demands of the material with the material code of P00101; the primary MRP demand of the material with the material code of P00102 is 0; the primary MRP demand of the material with the material code of P00103 is 10 pieces; the primary MRP demand of the material with the material code of P00201 is 20 sheets; the preliminary MRP requirement for material with material code P00202 was 20.
S5: extracting the yield of each product according to the product code;
in the embodiment of the invention, the yield of each extracted product is shown in the table 5,
TABLE 5
| Production task numbering | Product coding | Yield of good products |
| A001 | X001 | 98.54％ |
| A001 | X002 | 89.72％ |
As can be seen from table 5, the yield of the product with the product code X001 is 98.54%; the yield of the product with the product code of X002 is 89.72%.
S6: adjusting the primary MRP demand according to the yield of each product to obtain a primary calibration MRP demand;
the first calibration MRP demand is calculated as:
wherein INT is an upward rounding function, and ik is the yield of k products in the ith year.
In the embodiment of the invention, the first calibration MRP demand of each material in each product is obtained according to the calculation formula of the first calibration MRP demand, as shown in Table 5,
TABLE 5
Respectively obtaining 28 first calibration MRP demand quantities with material codes of P00101 according to a calculation formula of the first calibration MRP demand quantities; the first calibration MRP demand with the material code of P00102 is 0; the first calibration MRP demand with the material code of P00103 is 11 pieces; the first calibration MRP demand with material code P00201 is 21; the first calibration MRP requirement for material code P00202 is 21.
S7: extracting the actual material demand and the planned material usage of each product produced n years before the current year serving as a reference according to the material codes;
the embodiment of the invention takes the current 2020 years as a reference, and generally takes n to be more than or equal to 5 to ensure the accuracy, so that the embodiment of the invention extracts the actual material demand and the planned material usage of the product produced in the previous 5 years, as shown in table 6,
TABLE 6
And taking 2020 in the current year as a reference, extracting the actual material demand and the planned material usage of the material in the previous 5 years including 2016, 2017, 2018 and 2019, wherein the material code is P00101, the material code is P00102, the material code is P00103, the material code is P00201 and the material code is P00202.
S8: calculating the actual planned quantity ratio of the demands of the products in n years according to the actual material demand and the planned material usage of the products;
the calculation formula of the demand actual planning quantity ratio is as follows:
s9: calculating the actual planned quantity ratio of the demands of the current year according to the actual planned quantity ratio of the demands of each product in n years;
in the embodiment of the invention, the actual planned quantity ratio of the demands in the current year is calculated by using a moving average method according to the actual planned quantity ratio of the demands of each material in 5 years.
S10: and acquiring the final MRP demand according to the actual planned demand ratio of the current year.
The final MRP demand is calculated as:
final MRP demand-first calibrated MRP demand-current year demand actual projected volume ratio.
The MRP value required by production is obtained through the steps, but in order to reuse the method later, the final MRP demand obtained through calculation needs to be accumulated in the planned material usage statistical data of the current year, meanwhile, in the production process, the usage condition of the material needs to be recorded in various modes such as manual recording or only equipment collection, and the actual material demand accumulated in the current year is recorded and stored for later use.
The MRP algorithm based on data feedback disclosed by the invention is used for calculating MRP data according to the past historical actual consumption change, so that a purchasing plan is more suitable for the actual material consumption requirement, and the yield of different products is considered when the MRP value is calculated, so that the MRP value is closer to the actual material consumption requirement in the production process.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above examples are only for describing the preferred embodiments of the present invention, and are not intended to limit the scope of the present invention, and various modifications and improvements made to the technical solution of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.
Claims (6)
1. An MRP algorithm based on data feedback is characterized by comprising the following steps:
extracting a production product code according to the production task;
acquiring a BOM list according to the product codes, and extracting material codes, quantity and units of all materials in the BOM list;
acquiring the current stock, the reservation quantity and the stock in-transit quantity according to the material codes;
calculating a preliminary MRP demand according to an MRP calculation formula;
extracting the yield of each product according to the product code;
adjusting the primary MRP demand according to the yield of each product to obtain a primary calibration MRP demand;
extracting the actual material demand and the planned material usage of each product produced n years before the current year serving as a reference according to the material codes;
calculating the actual planned quantity ratio of the demands of the products in n years according to the actual material demand and the planned material usage of the products;
calculating the actual planned quantity ratio of the demands of the current year according to the actual planned quantity ratio of the demands of each product in n years;
and acquiring the final MRP demand according to the actual planned demand ratio of the current year.
2. The data feedback-based MRP algorithm of claim 1, wherein the preliminary MRP requirement is calculated by the formula:
3. the data feedback-based MRP algorithm as claimed in claim 2, wherein the first-time calibration MRP requirement is calculated by the formula:
wherein INT is an upward rounding function, and yieldikThe yield of k products in the ith year.
4. The MRP algorithm based on data feedback as claimed in claim 3, wherein the calculation formula of the demand-to-actual-plan-quantity ratio is:
5. the MRP algorithm based on data feedback as claimed in claim 4, wherein the final MRP demand is calculated by the formula:
final MRP demand-first calibrated MRP demand-current year demand actual projected volume ratio.
6. A data feedback-based MRP algorithm according to any of claims 1-5, wherein n ≧ 5.
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| CN114565340A (en) * | 2022-02-28 | 2022-05-31 | 苏州慧工云信息科技有限公司 | MRP operation verification test method, device, equipment and storage medium |
| CN114677046A (en) * | 2022-04-20 | 2022-06-28 | 武汉易特兰瑞科技有限公司 | Industrial production data resource processing method, system and storage medium |
| CN116071003A (en) * | 2023-01-28 | 2023-05-05 | 广州智造家网络科技有限公司 | Material demand plan calculation method, device, electronic equipment and storage medium |
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