Raw material management method and system for vegetable protein beverage

Abstract

The invention discloses a raw material management method and system for a vegetable protein beverage, belongs to the technical field of raw material data management, and aims at solving the problems that an existing raw material management method for the vegetable protein beverage does not form a set of unified and efficient management method, many manual participation links still exist in the management process, management vulnerabilities are likely to occur, and the management efficiency is high. And the product quality is influenced. The method comprises the following steps: constructing a raw material management risk influence index system based on raw material requirements of the vegetable protein beverage; analyzing the intra-layer weight of each index in the index layer; determining the comprehensive matching degree of each raw material supplier according to the weight in the layer, and selecting a final raw material supplier; determining material levels of various raw materials based on a fuzzy comprehensive evaluation algorithm, and performing quality inspection on the purchased raw materials by adopting a corresponding quality inspection method according to the material levels to obtain a quality inspection result; and according to the material level and the quality inspection result, performing adaptive storage on the raw materials, and performing ex-warehouse batch recommendation based on the raw material data.

Description

Technical Field

[0001] The present invention relates to the technical field of raw material data management, and in particular to a raw material management method and system for plant protein beverages. Background Art

[0002] Plant protein beverages are made from plant kernels or seeds, such as peanuts, walnuts, almonds, soybeans, coconuts, etc., after raw material pretreatment, soaking, grinding, filtering, homogenization, sterilization and other processes. Compared with animal protein foods, they are low in saturated fatty acids and cholesterol, which has a positive significance in preventing vascular sclerosis and diabetes. In recent years, with the continuous improvement of people's health awareness, plant protein beverages have become more and more popular among consumers.

[0003] However, with the increasing number of such products on the market, the quality of plant protein beverages can no longer meet the requirements of consumers for product quality. Especially in the raw material management stage of plant protein beverages, whether it is raw material procurement, quality inspection, storage or use, each manufacturer has its own set of standards, and has not formed a unified and efficient management method. In addition, most management nodes still need to be managed manually based on experience. For example, the procurement stage requires manual comparison and selection of suppliers, and the quality inspection stage requires manual formulation of quality inspection standards and acceptance of quality inspection results. These operations are prone to management loopholes and quality problems in raw materials, which in turn affect the quality of the final product. Summary of the invention

[0004] The embodiments of the present invention provide a raw material management method and system for plant protein beverages, which are used to solve the following technical problems: the existing raw material management methods for plant protein beverages have not formed a unified and efficient management method, and there are still many manual participation links in the management process, which are prone to management loopholes and affect product quality.

[0005] The embodiment of the present invention adopts the following technical solutions: On the one hand, an embodiment of the present invention provides a raw material management method for plant protein beverages, the method comprising: based on the current enterprise's demand for raw materials of plant protein beverages, constructing a corresponding raw material management risk impact indicator system; the raw material management risk impact indicator system at least includes an attribute layer and an indicator layer; Based on the raw material management risk impact indicator system, analyzing the intra-layer weight of each indicator in the indicator layer; Determine the comprehensive matching degree of each raw material supplier according to the intra-layer weights, and select the final raw material supplier according to the comprehensive matching degree; Based on the fuzzy comprehensive evaluation algorithm, the material level of each type of raw material is determined, and according to the material level, the corresponding quality inspection method is adopted to conduct quality inspection on the purchased raw materials to obtain the quality inspection results; Generate corresponding initial storage environment parameters according to the material level and quality inspection results, and adaptively store the raw materials based on the initial storage environment parameters; When raw materials are shipped out, shipping batch recommendations are made based on the stored raw material data.

[0006] In a feasible implementation, based on the current demand of enterprises for raw materials of plant protein beverages, a corresponding raw material management risk impact indicator system is constructed, specifically including: From the current demand of enterprises for raw materials of plant protein beverages, several demand items are extracted; wherein the demand items include at least one or more of the following: supply chain demand, supplier demand, transportation demand, quality demand, information transparency demand and cost demand; Classifying the demand items according to attributes to construct the attribute layer; wherein the attribute layer at least includes: traceability management, quality management and cost management; Subdividing the demand items to obtain a number of risk indicators, and constructing the indicator layer; Several indicators in the indicator layer are associated with the attribute layer to obtain the raw material management risk impact indicator system.

[0007] In a feasible implementation, based on the raw material management risk impact indicator system, the intra-layer weight of each indicator in the indicator layer is analyzed, specifically including: Based on expert experience, score the importance of each attribute and each indicator in the raw material management risk impact indicator system; According to the scoring results of each attribute, construct the attribute layer feature matrix; According to the scoring results of multiple indicators associated with each attribute layer, the indicator layer feature matrix corresponding to each attribute layer is generated respectively; The intra-layer weight of each indicator in the indicator layer is calculated according to the attribute layer feature matrix and the indicator layer feature matrix.

[0008] In a feasible implementation manner, according to the attribute layer feature matrix and the indicator layer feature matrix, calculating the intra-layer weight of each indicator in the indicator layer specifically includes: Take each indicator layer feature matrix as a diagonal element and construct a diagonal matrix; The diagonal matrix is ​​multiplied by the attribute layer feature matrix to obtain a weight matrix; the element values ​​in the weight matrix are the intra-layer weights of the indicators in the corresponding order.

[0009] In a feasible implementation, the comprehensive matching degree of each raw material supplier is determined according to the intra-layer weight, and the final raw material supplier is selected according to the comprehensive matching degree, specifically including: Obtain the corresponding indicator values ​​of each raw material supplier; Perform weighted calculation on the index value and the intra-layer weight to obtain the initial comprehensive matching degree of each raw material supplier; Multiply the index values ​​of the top three raw material suppliers with the highest initial comprehensive matching degree by the historical purchasing coefficient, and determine the raw material supplier with the largest calculated result as the final raw material supplier; wherein, the historical purchasing coefficient is related to the historical number of times the current enterprise has purchased raw materials from the raw material supplier.

[0010] In a feasible implementation, the material level of each type of raw material is determined based on a fuzzy comprehensive evaluation algorithm, specifically including: Extract the grade evaluation factors of various raw materials of plant protein beverages and construct a set of evaluation factors; Build a level selection set based on the raw material levels set in the quality inspection system; According to the importance of the factors at each level, the corresponding factor weights are generated and the factor weight matrix is ​​constructed; Based on the fuzzy comprehensive evaluation algorithm, the membership degree of each evaluation factor of each type of raw material to each level in the level alternative set is calculated; The membership degrees corresponding to each evaluation factor are combined into a matrix form to obtain a single factor evaluation matrix for each type of raw material; Multiplying the single factor evaluation matrix by the factor weight matrix to obtain a fuzzy comprehensive evaluation set for each type of raw material; In the fuzzy comprehensive evaluation set, the level corresponding to the maximum membership degree is extracted as the material level of the current type of raw material.

[0011] In a feasible implementation, according to the material level, a corresponding quality inspection method is adopted to perform quality inspection on the purchased raw materials to obtain quality inspection results, which specifically include: After the raw materials are purchased, they are divided according to the material level of each type of raw materials, and the corresponding quality inspection process and quality inspection standards are matched according to the material level; According to the quality inspection process and quality inspection standards, quality inspection is performed on the corresponding type of raw materials to obtain the quality inspection results.

[0012] In a feasible implementation, according to the material level and the quality inspection result, corresponding initial storage environment parameters are generated, and based on the initial storage environment parameters, the raw materials are adaptively stored, specifically including: Determine the initial storage environment parameters of the raw materials according to the type of raw materials, material level and quality inspection results; the initial storage environment parameters include at least: storage method, storage level, storage temperature and storage humidity; Based on the preset time interval, the stored raw materials are sampled and analyzed, and according to the raw material status obtained by the analysis, the initial storage environment parameters are adaptively adjusted to achieve adaptive storage.

[0013] In a feasible implementation, when raw materials are shipped out, a shipping batch recommendation is performed based on the stored raw material data, specifically including: Extract the raw material usage requirements from the raw material outbound demand, and match the appropriate raw material batches according to the raw material usage requirements; The suitable raw material batches are sorted according to the order of storage time from early to late, and the sorted raw material batches are pushed to the outbound terminal to make outbound batch recommendations.

[0014] On the other hand, an embodiment of the present invention further provides a raw material management system for plant protein beverages, the system comprising: A raw material procurement unit is used to construct a corresponding raw material management risk impact indicator system based on the current enterprise's demand for raw materials of plant protein beverages; the raw material management risk impact indicator system at least includes an attribute layer and an indicator layer; and based on the raw material management risk impact indicator system, analyze the intra-layer weight of each indicator in the indicator layer; determine the comprehensive matching degree of each raw material supplier according to the intra-layer weight, and select the final raw material supplier according to the comprehensive matching degree; The raw material quality inspection unit is used to determine the material level of each type of raw material based on the fuzzy comprehensive evaluation algorithm, and adopt the corresponding quality inspection method to inspect the purchased raw materials according to the material level to obtain the quality inspection results; A raw material storage unit, used to generate corresponding initial storage environment parameters according to the material level and quality inspection results, and adaptively store the raw materials based on the initial storage environment parameters; The raw material outbound unit is used to recommend outbound batches based on the stored raw material data when the raw materials are outbound.

[0015] Compared with the prior art, the raw material management method and system for plant protein beverages provided by the embodiment of the present invention have the following beneficial effects: The present invention proposes an automated execution method for the management of raw materials for plant protein beverages in four aspects, namely, procurement, quality inspection, storage and delivery. The method can realize the functions of automatically evaluating and selecting raw material suppliers, automatically distinguishing raw material grades and selecting appropriate quality inspection methods for quality inspection, distinguishing storage parameters of raw materials according to material levels and quality inspection results, regularly adaptively adjusting storage parameters, and recommending delivery batches when delivering the goods. It not only proposes a unified and efficient raw material management method, but also greatly reduces the links involved in manual work. By controlling each management link through artificial intelligence and automation technology, it can make up for management loopholes, unify management standards, ensure the quality and safety of raw materials for plant protein beverages from the source, and improve the safety of plant protein beverages. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] 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 prior art descriptions. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings: Figure 1 A flow chart of a raw material management method for plant protein beverages provided in an embodiment of the present invention; Figure 2 A schematic structural diagram of a raw material management system for plant protein beverages provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0018] The embodiment of the present invention provides a raw material management method for plant protein beverages, such as Figure 1 As shown, the raw material management method for plant protein beverages specifically includes steps S101-S106: S101. Based on the current demand of enterprises for raw materials of plant protein beverages, construct a corresponding raw material management risk impact indicator system.

[0019] Specifically, the raw material management risk impact indicator system includes at least an attribute layer and an indicator layer.

[0020] First, several demand items are extracted from the current corporate demand for raw materials for plant protein beverages; among them, the demand items include at least one or more of the following: supply chain demand, supplier demand, transportation demand, quality demand, information transparency demand and cost demand.

[0021] Furthermore, the demand items are classified according to their attributes to construct an attribute layer; wherein the attribute layer at least includes: traceability management, cost management and quality management.

[0022] As a feasible implementation method, supply chain requirements, supplier requirements and transportation requirements belong to traceability management attributes, quality requirements and information transparency requirements belong to quality management attributes, and cost requirements belong to cost management attributes.

[0023] Furthermore, these requirements are subdivided to obtain several management indicators and construct an indicator layer. Then, several indicators in the indicator layer are associated with the attribute layer to obtain the raw material management risk impact indicator system.

[0024] As a feasible implementation method, a raw material management risk impact indicator system obtained based on the above steps is shown in Table 1.

[0025] Table 1

[0026] S102. Based on the raw material management risk impact indicator system, analyze the intra-layer weights of each indicator in the indicator layer.

[0027] Specifically, based on expert experience, each attribute and each indicator in the raw material management risk impact index system is scored for importance.

[0028] Furthermore, according to the scoring results of each attribute, an attribute layer feature matrix is ​​constructed.

[0029] As a feasible implementation, the value of each element is calculated in the form of Table 2, and the calculation method is: attribute score value represented by the row / attribute score value represented by the column. For example, if the score of traceability management is 4 and the score of quality management is 3, then the element value of the first row and second column is 4 / 3. Similarly, the values ​​of other elements can be inferred to obtain the judgment matrix of the attribute layer.

[0030] Table 2

[0031] As shown in the example in Table 2, the attribute layer judgment matrix obtained is: Then calculate the ratio of the sum of the element values ​​in each row to the sum of all the element values ​​to get the attribute layer feature matrix .

[0032] Furthermore, based on the above method, according to the scoring results of multiple indicators associated with each attribute layer, an indicator layer feature matrix corresponding to each attribute layer is generated respectively.

[0033] Furthermore, according to the attribute layer feature matrix and the indicator layer feature matrix, the intra-layer weight of each indicator in the indicator layer is calculated, specifically including: Each indicator layer feature matrix is ​​used as a diagonal element to construct a diagonal matrix. Then the diagonal matrix is ​​multiplied with the attribute layer feature matrix to obtain a weight matrix. The element value in the weight matrix is ​​the intra-layer weight of the indicator in the corresponding order.

[0034] S103. Determine the comprehensive matching degree of each raw material supplier according to the intra-layer weight, and select the final raw material supplier according to the comprehensive matching degree.

[0035] Specifically, the index values ​​corresponding to each raw material supplier are obtained, and the index values ​​are weighted with the corresponding intra-layer weights to obtain the initial comprehensive matching degree of each raw material supplier.

[0036] Furthermore, the index values ​​of the top three raw material suppliers with the highest initial comprehensive matching degree are multiplied by the historical purchasing coefficient, and the raw material supplier with the largest calculation result is determined as the final raw material supplier. Among them, the historical purchasing coefficient is related to the historical number of times the current enterprise has purchased raw materials from this raw material supplier.

[0037] The present invention collects various indicator values ​​of each raw material supplier, performs weighted calculation with the intra-layer weight calculated previously, selects the top three suppliers after the first screening, and then generates a historical procurement coefficient based on the historical procurement times. It can comprehensively consider the comprehensive level of the supplier and the historical cooperation between the current enterprise and the supplier, and produce a recommendation plan that is more suitable for the current enterprise.

[0038] S104. Based on the fuzzy comprehensive evaluation algorithm, the material level of each type of raw material is determined, and according to the material level, corresponding quality inspection methods are adopted to conduct quality inspection on the purchased raw materials to obtain quality inspection results.

[0039] Specifically, we first extract the level evaluation factors of various raw materials of plant protein beverages and construct a set of evaluation factors. Then, we construct a set of alternative levels based on the raw material levels set in the quality inspection system. Then, we generate corresponding factor weights based on the importance of each level evaluation factor and construct a factor weight matrix.

[0040] As a feasible implementation method, the level evaluation factors at least include: raw material type, raw material quality inspection standard, raw material quality inspection difficulty and other factors. The factors affecting the raw material level should be determined according to the actual situation of the production enterprise. Different enterprises may have different level evaluation factors, so this is not limited in the present invention. The level selection set includes a total of several levels. If it is divided into A-level materials, B-level materials and C-level materials, then the level selection set is {A, B, C}.

[0041] Furthermore, based on the fuzzy comprehensive evaluation algorithm, the membership of each evaluation factor of each type of raw material to each level in the level selection set is calculated. The membership corresponding to each evaluation factor is combined into a matrix form to obtain a single factor evaluation matrix for each type of raw material.

[0042] Then, the single factor evaluation matrix is ​​multiplied by the factor weight matrix to obtain the fuzzy comprehensive evaluation set for each type of raw material. In the fuzzy comprehensive evaluation set, the level corresponding to the maximum membership degree is extracted as the material level of the current type of raw material.

[0043] In one embodiment, if the fuzzy comprehensive evaluation set of the soybean raw material is {0.5, 0.2, 0.3}, and 0.5 is the largest, then the level A in the level alternative set corresponding to 0.5 is the material level of the soybean raw material.

[0044] Furthermore, after the raw materials are purchased, the raw materials are divided according to the material level of each type of raw materials, and the corresponding quality inspection process and quality inspection standards are matched according to the material level. The corresponding type of raw materials are quality inspected according to the quality inspection process and quality inspection standards to obtain the quality inspection results.

[0045] S105, generating corresponding initial storage environment parameters according to the material level and quality inspection results, and adaptively storing the raw materials based on the initial storage environment parameters; Specifically, the initial storage environment parameters of the raw materials are determined according to the type of raw materials, material level and quality inspection results; the initial storage environment parameters include at least: storage method, storage level, storage temperature and storage humidity.

[0046] Furthermore, based on preset time intervals, the stored raw materials are sampled and analyzed, and then according to the raw material states obtained from the analysis, the initial storage environment parameters are adaptively adjusted to achieve adaptive storage.

[0047] As a feasible implementation method, a suitable storage environment is constructed according to the classification of raw materials, and storage parameters such as temperature and humidity are controlled. Then, the stored raw materials are sampled regularly for component analysis, and the storage environment is appropriately adjusted based on the results of the component analysis, thereby extending the shelf life of the raw materials.

[0048] S106. When raw materials are shipped out, a shipping batch is recommended based on the stored raw material data.

[0049] Specifically, the raw material usage requirements are extracted from the raw material outbound demand, and appropriate raw material batches are matched according to the raw material usage requirements. Then, the appropriate raw material batches are sorted according to the order of storage time from early to late, and the sorted raw material batches are pushed to the outbound terminal for outbound batch recommendation.

[0050] In addition, the embodiment of the present invention also provides a raw material management system for plant protein beverages, such as Figure 2 As shown, the raw material management system 200 for plant protein beverages specifically includes: The raw material procurement unit 210 is used to construct a corresponding raw material management risk impact indicator system based on the current enterprise's demand for raw materials of plant protein beverages; the raw material management risk impact indicator system at least includes an attribute layer and an indicator layer; and based on the raw material management risk impact indicator system, analyze the intra-layer weight of each indicator in the indicator layer; determine the comprehensive matching degree of each raw material supplier according to the intra-layer weight, and select the final raw material supplier according to the comprehensive matching degree; The raw material quality inspection unit 220 is used to determine the material level of each type of raw material based on the fuzzy comprehensive evaluation algorithm, and adopt corresponding quality inspection methods to perform quality inspection on the purchased raw materials according to the material level to obtain quality inspection results; A raw material storage unit 230, for generating corresponding initial storage environment parameters according to the material level and the quality inspection result, and adaptively storing the raw materials based on the initial storage environment parameters; The raw material outbound unit 240 is used to recommend outbound batches based on the stored raw material data when the raw materials are outbound.

[0051] Each embodiment of the present invention is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0052] The above describes specific embodiments of the present invention. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0053] The above description is only an embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the embodiments of the present invention may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for managing raw materials of plant protein beverages, characterized in that: The method comprises: Based on the current demand of enterprises for raw materials of plant protein beverages, a corresponding raw material management risk impact indicator system is constructed; the raw material management risk impact indicator system at least includes an attribute layer and an indicator layer; Based on the raw material management risk impact indicator system, analyzing the intra-layer weight of each indicator in the indicator layer; Determine the comprehensive matching degree of each raw material supplier according to the intra-layer weights, and select the final raw material supplier according to the comprehensive matching degree; Based on the fuzzy comprehensive evaluation algorithm, the material level of each type of raw material is determined, and according to the material level, the corresponding quality inspection method is adopted to conduct quality inspection on the purchased raw materials to obtain the quality inspection results; Generate corresponding initial storage environment parameters according to the material level and quality inspection results, and adaptively store the raw materials based on the initial storage environment parameters; When raw materials are shipped out, shipping batch recommendations are made based on the stored raw material data.

2. A method for managing raw materials for plant protein beverages according to claim 1, characterized in that: Based on the current demand of enterprises for raw materials of plant protein beverages, a corresponding raw material management risk impact indicator system is constructed, including: From the current demand of enterprises for raw materials of plant protein beverages, several demand items are extracted; wherein the demand items include at least one or more of the following: supply chain demand, supplier demand, transportation demand, quality demand, information transparency demand and cost demand; Classifying the demand items according to attributes to construct the attribute layer; wherein the attribute layer at least includes: traceability management, quality management and cost management; Subdividing the demand items to obtain a number of risk indicators, and constructing the indicator layer; Several indicators in the indicator layer are associated with the attribute layer to obtain the raw material management risk impact indicator system.

3. A method for managing raw materials for plant protein beverages according to claim 1, characterized in that: Based on the raw material management risk impact indicator system, the intra-layer weights of each indicator in the indicator layer are analyzed, specifically including: Based on expert experience, score the importance of each attribute and each indicator in the raw material management risk impact indicator system; According to the scoring results of each attribute, construct the attribute layer feature matrix; According to the scoring results of multiple indicators associated with each attribute layer, the indicator layer feature matrix corresponding to each attribute layer is generated respectively; The intra-layer weight of each indicator in the indicator layer is calculated according to the attribute layer feature matrix and the indicator layer feature matrix.

4. A method for managing raw materials for plant protein beverages according to claim 3, characterized in that: Calculating the intra-layer weight of each indicator in the indicator layer according to the attribute layer feature matrix and the indicator layer feature matrix, specifically including: Take each indicator layer feature matrix as a diagonal element and construct a diagonal matrix; The diagonal matrix is ​​multiplied by the attribute layer feature matrix to obtain a weight matrix; the element values ​​in the weight matrix are the intra-layer weights of the indicators in the corresponding order.

5. A method for managing raw materials for plant protein beverages according to claim 1, characterized in that: Determine the comprehensive matching degree of each raw material supplier according to the intra-layer weights, and select the final raw material supplier according to the comprehensive matching degree, specifically including: Obtain the corresponding indicator values ​​of each raw material supplier; Perform weighted calculation on the index value and the intra-layer weight to obtain the initial comprehensive matching degree of each raw material supplier; Multiply the index values ​​of the top three raw material suppliers with the highest initial comprehensive matching degree by the historical purchasing coefficient, and determine the raw material supplier with the largest calculated result as the final raw material supplier; wherein, the historical purchasing coefficient is related to the historical number of times the current enterprise has purchased raw materials from the raw material supplier.

6. A method for managing raw materials for plant protein beverages according to claim 1, characterized in that: Based on the fuzzy comprehensive evaluation algorithm, the material level of various raw materials is determined, including: Extract the grade evaluation factors of various raw materials of plant protein beverages and construct a set of evaluation factors; Build a level selection set based on the raw material levels set in the quality inspection system; According to the importance of the factors at each level, the corresponding factor weights are generated and the factor weight matrix is ​​constructed; Based on the fuzzy comprehensive evaluation algorithm, the membership degree of each evaluation factor of each type of raw material to each level in the level alternative set is calculated; The membership degrees corresponding to each evaluation factor are combined into a matrix form to obtain a single factor evaluation matrix for each type of raw material; Multiplying the single factor evaluation matrix by the factor weight matrix to obtain a fuzzy comprehensive evaluation set for each type of raw material; In the fuzzy comprehensive evaluation set, the level corresponding to the maximum membership degree is extracted as the material level of the current type of raw material.

7. A method for managing raw materials for plant protein beverages according to claim 1, characterized in that: According to the material level, the corresponding quality inspection method is adopted to inspect the purchased raw materials and obtain the quality inspection results, which specifically include: After the raw materials are purchased, they are divided according to the material level of each type of raw materials, and the corresponding quality inspection process and quality inspection standards are matched according to the material level; According to the quality inspection process and quality inspection standards, quality inspection is performed on the corresponding type of raw materials to obtain the quality inspection results.

8. A method for managing raw materials for plant protein beverages according to claim 1, characterized in that: According to the material level and the quality inspection result, the corresponding initial storage environment parameters are generated, and based on the initial storage environment parameters, the raw materials are adaptively stored, specifically including: Determine the initial storage environment parameters of the raw materials according to the type of raw materials, material level and quality inspection results; the initial storage environment parameters include at least: storage method, storage level, storage temperature and storage humidity; Based on the preset time interval, the stored raw materials are sampled and analyzed, and according to the state of the raw materials obtained by the analysis, the initial storage environment parameters are adaptively adjusted to achieve adaptive storage.

9. A method for managing raw materials for plant protein beverages according to claim 1, characterized in that: When raw materials are shipped out, the shipping batches are recommended based on the stored raw material data, including: Extract the raw material usage requirements from the raw material outbound demand, and match the appropriate raw material batches according to the raw material usage requirements; The suitable raw material batches are sorted according to the order of storage time from early to late, and the sorted raw material batches are pushed to the outbound terminal to make outbound batch recommendations.

10. A raw material management system for plant protein beverages, characterized in that: The system comprises: A raw material procurement unit is used to construct a corresponding raw material management risk impact indicator system based on the current enterprise's demand for raw materials of plant protein beverages; the raw material management risk impact indicator system at least includes an attribute layer and an indicator layer; and based on the raw material management risk impact indicator system, analyze the intra-layer weight of each indicator in the indicator layer; determine the comprehensive matching degree of each raw material supplier according to the intra-layer weight, and select the final raw material supplier according to the comprehensive matching degree; The raw material quality inspection unit is used to determine the material level of each type of raw material based on the fuzzy comprehensive evaluation algorithm, and adopt the corresponding quality inspection method to inspect the purchased raw materials according to the material level to obtain the quality inspection results; A raw material storage unit, used to generate corresponding initial storage environment parameters according to the material level and quality inspection results, and adaptively store the raw materials based on the initial storage environment parameters; The raw material outbound unit is used to recommend outbound batches based on the stored raw material data when the raw materials are outbound.

Images