Enterprise supply chain optimization method and system

Abstract

The invention relates to the technical field of enterprise supply chain optimization, and discloses an enterprise supply chain optimization system, which comprises a supply demand confirmation module, an inventory management module and a supply material scheduling module, and is characterized in that the supply demand confirmation module comprises a historical supply demand data acquisition unit and a supply demand prediction unit. According to the system, the demand data of materials in historical records and the demand data of materials in the current supply period are collected, the demand trend of the materials in the current supply period is calculated, calculation is carried out in combination with the demand data of the materials in the historical records, predicted material demand data are obtained, and therefore the material demand of an enterprise is obtained; after the material demand is determined, the inventory value is compared with the predicted material demand, so that whether scheduling from other suppliers is needed or not is obtained, if the supplier cannot perform scheduling, optimization prediction of the whole supply chain is completed according to the time needed by production of a manufacturer, and prediction of the supply demand of an enterprise is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of enterprise supply chain optimization, and in particular to an enterprise supply chain optimization method and system. Background Art

[0002] China's intelligent manufacturing is in the early stages of development, and most of it is also in the research and development stage. Only 16% of enterprises have entered the stage of intelligent manufacturing application. From the perspective of the economic benefits of intelligent manufacturing, 52% of enterprises have an intelligent manufacturing revenue contribution rate of less than 10%, and 60% of enterprises have an intelligent manufacturing profit contribution rate of less than 10%. The reason why 90% of small and medium-sized enterprises have a low degree of intelligent manufacturing is that the cost of intelligent upgrading has suppressed corporate demand, among which the lack of financing channels has the greatest impact;

[0003] At present, companies on the market generally adopt a policy of accepting orders as they come in and a production scheduling method based on a rough estimate of production capacity for material supply. However, under the basic premise of improving customer service levels and promising delivery dates, production workshops often have to work overtime or outsource to meet order delivery dates, and are unable to estimate the company's supply needs in advance. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the deficiencies in the prior art, the present invention provides a method and system for optimizing an enterprise supply chain, which has the advantages of predicting the supply demand of an enterprise and solves the above-mentioned technical problems.

[0006] (II) Technical solution

[0007] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an enterprise supply chain optimization system, comprising a supply demand confirmation module, an inventory management module and a supply material scheduling module;

[0008] The supply demand confirmation module includes a historical supply demand data collection unit and a supply demand prediction unit. The historical supply demand data collection unit is used to collect the demand data of materials in the historical records and the demand data of materials in the current supply cycle. The supply demand prediction unit calculates the demand trend of materials in the current supply cycle and calculates it in combination with the demand data of materials in the historical records to obtain the predicted material demand data. The supply demand confirmation module sends the calculated predicted material demand data to the inventory management module.

[0009] The inventory management module includes an inventory data collection unit and an inventory data calculation and analysis unit. The inventory data collection unit is used to collect material inventory data corresponding to the predicted material demand data after the supply demand confirmation module calculates and completes the calculation. The inventory data calculation and analysis unit is used to analyze and calculate whether the material inventory data can meet the predicted material demand data, and obtain the material analysis result. If the material analysis result is judged to meet the demand, the subsequent calculation is terminated. If the material analysis result is judged to not meet the demand, the material analysis result is sent to the supply material scheduling module;

[0010] The supply material scheduling module is used to schedule materials and make up the material difference in combination with the material analysis results. The supply material scheduling module includes a supplier material data collection unit, a material manufacturer data collection unit and a material difference calculation unit. The supplier material data collection unit is used to collect the supplier material data of the currently held materials, and the material manufacturer data collection unit is used to collect the manufacturer's production speed. The material difference calculation unit calculates the material difference and gives the time required to make up the difference.

[0011] As a preferred technical solution of the present invention, the historical supply demand data collection unit collects the demand data of materials in the historical records and the demand data of materials in the current supply cycle, and the expression is as follows:

[0012] LS=[LSWL1,…,LSWL i ,…,LSWL n ]

[0013] DQ=[DQWL t,1 ,…,DQWL t,j ,…,DQWL t,m ]

[0014] Among them, LSWL1,…,LSWL i ,…,LSWL n Represents 1 to n different historical supply and demand data, DQWL t,1 ,…,DQWL t,j ,…,DQWL t,m They respectively represent the demand data of the 1st material, ..., the demand data of the jth material, ..., the demand data of the mth material in the current supply cycle t. LS represents the historical supply demand data set, and DQ represents the demand data set of materials in the current supply cycle t.

[0015] As a preferred technical solution of the present invention, the supply demand forecasting unit calculates and obtains the predicted material demand data by calculating the following calculation expression:

[0016]

[0017] Among them, DQWL t,m+1 represents the predicted material demand data under the current supply cycle t, max{LS} represents the maximum value in the historical supply demand data, LSWL i represents the i-th historical supply and demand data, It represents the sum of n different historical supply and demand data, QS t Indicates the demand trend of materials in the current supply cycle.

[0018] As a preferred technical solution of the present invention, the demand trend QS of the material in the current supply cycle t The calculation expression is as follows:

[0019]

[0020] Among them, QS t Indicates the demand trend of materials in the current supply cycle, DQWL t,j Indicates the demand data of the jth material in the current supply cycle t, DQWL t,j-1 Indicates the demand data of the j-1th material in the current supply cycle t. It means to sum m-1 data.

[0021] As a preferred technical solution of the present invention, the steps of analyzing by the inventory data calculation and analysis unit in the inventory management module are as follows:

[0022] A1. DQWL is the material demand data DQWL predicted under the current supply cycle t. t,m+1 Material inventory data KC collected by the inventory data collection unit t , calculate and obtain the material analysis result CZ t ;

[0023] A2. If the material analysis result is CZ t >0, the demand is not met, and the material analysis results are sent to the supply material scheduling module. If the material analysis result CZ t ≤0, the requirement is met and subsequent calculations are terminated.

[0024] As a preferred technical solution of the present invention, the material analysis result CZ calculated in step A1 is t The expression is as follows:

[0025] CZ t =DQWL t,m+1 -KC t

[0026] Among them, CZ tIndicates the material analysis results in the current supply cycle t, KC t Indicates the material inventory data collected by the inventory data collection unit in the current supply cycle t, DQWL t,m+1 Represents the predicted material demand data under the current supply cycle t.

[0027] As a preferred technical solution of the present invention, the supplier material data collected by the supplier material data collection unit is expressed as follows:

[0028] GYS=[GYS1,…,GYS k ,…,GYS K ]

[0029] Among them, GYS1,…,GYS k ,…,GYS k They respectively represent the material storage quantity of the 1st supplier, …, the kth supplier, …, and the Kth supplier, and GYS represents the supplier material data set.

[0030] As a preferred technical solution of the present invention, the specific steps of the material difference calculation unit for calculation are as follows:

[0031] B1. Determine whether the supplier's material storage capacity can meet the material analysis results CZ t , if it can be satisfied, then terminate the calculation, if it cannot be satisfied, then execute step B2;

[0032] B2. If the requirement cannot be met, calculate the difference and work out the time required to make up the difference based on the manufacturer’s production speed.

[0033] As a preferred technical solution of the present invention, the calculation expression for the supplementary time in step B2 is as follows:

[0034]

[0035] Among them, T t represents the time required to make up the difference in the current supply cycle t, CZ t Indicates the material analysis results in the current supply cycle t, GYS k represents the material storage volume of the kth supplier, V t Represents the production speed of the manufacturer in the current supply cycle t.

[0036] The present invention also provides an enterprise supply chain optimization method, based on the above-mentioned enterprise supply chain optimization system, comprising the following steps:

[0037] S1. Collect the demand data of materials in the historical records and the demand data of materials in the current supply cycle t;

[0038] S2. Calculate the demand trend of materials in the current supply cycle and calculate it in combination with the demand data of materials in the historical records to obtain the predicted material demand data;

[0039] S3, collecting material inventory data corresponding to the predicted material demand data after calculation by the supply demand confirmation module;

[0040] S4, calculate and obtain the material analysis results, and determine whether the material inventory data can meet the predicted material demand data. If the material analysis results are determined to meet the demand, terminate the step; if the material analysis results are determined to not meet the demand, execute step S5;

[0041] S5, collect the material data of the supplier currently holding the material, and determine whether the supplier can replenish the material. If so, terminate the step; if not, execute step S6;

[0042] S6. Calculate the difference in materials based on the manufacturer’s production speed and give the time required to make up the difference.

[0043] Compared with the prior art, the present invention provides a method and system for optimizing an enterprise supply chain, which has the following beneficial effects:

[0044] The present invention collects material demand data in historical records and material demand data in the current supply cycle, calculates the demand trend of materials in the current supply cycle, and calculates in combination with the material demand data in the historical records to obtain predicted material demand data, thereby obtaining the enterprise's material demand. After determining the material demand, the inventory value is compared with the predicted material demand to determine whether it is necessary to dispatch from other suppliers. If the supplier cannot dispatch, the time required for manufacturer production is used to complete the optimization forecast of the entire supply chain, thereby realizing the forecast of the enterprise's supply demand. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic diagram of the system framework of the present invention;

[0046] Figure 2 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] See also Figure 1, an enterprise supply chain optimization system, including a supply demand confirmation module, an inventory management module and a supply material scheduling module;

[0049] The supply demand confirmation module includes a historical supply demand data collection unit and a supply demand forecasting unit. The historical supply demand data collection unit is used to collect the demand data of materials in the historical records LS=[LSWL1,…,LSWL i ,…,LSWL n ] and the demand data DQ of the current supply cycle material = [DQWL t,1 ,…,DQWL t,j ,…,DQWL t,m ], the supply demand forecasting unit calculates the demand trend of the materials in the current supply cycle, and calculates it in combination with the demand data of the materials in the historical records to obtain the predicted material demand data The supply demand confirmation module sends the calculated forecasted material demand data to the inventory management module;

[0050] Among them, LSWL1,…,LSWL i ,…,LSWL n Represents 1 to n different historical supply and demand data, DQWL t,1 ,…,DQWL t,j ,…,DQWL t,m They represent the demand data of the first material, ..., the demand data of the jth material, ..., the demand data of the mth material in the current supply cycle t, LS represents the historical supply demand data set, DQ represents the demand data set of the material in the current supply cycle t, DQWL t,m+1 represents the predicted material demand data under the current supply cycle t, max{LS} represents the maximum value in the historical supply demand data, LSWL i represents the i-th historical supply and demand data, It represents the sum of n different historical supply and demand data, QS t Indicates the demand trend of materials in the current supply cycle.

[0051] Furthermore, the demand trend of the current supply cycle material QS t The calculation expression is as follows:

[0052]

[0053] Among them, QS t Indicates the demand trend of materials in the current supply cycle, DQWL t,j Indicates the demand data of the jth material in the current supply cycle t, DQWL t,j-1Indicates the demand data of the j-1th material in the current supply cycle t. It means to sum m-1 data.

[0054] The inventory management module includes an inventory data collection unit and an inventory data calculation and analysis unit. The inventory data collection unit is used to collect material inventory data corresponding to the predicted material demand data after the supply demand confirmation module calculates and completes the calculation. The inventory data calculation and analysis unit is used to analyze and calculate whether the material inventory data can meet the predicted material demand data, and obtain the material analysis result. If the material analysis result is judged to meet the demand, the subsequent calculation is terminated. If the material analysis result is judged to not meet the demand, the material analysis result is sent to the supply material scheduling module;

[0055] The inventory data calculation and analysis unit in the inventory management module performs analysis: First, the material demand data DQWL predicted under the current supply cycle t is t,m+1 Material inventory data KC collected by the inventory data collection unit t , calculate and obtain the material analysis result CZ t =DQWL t,m+1 -KC t If the material analysis result is CZ t >0, the demand is not met, and the material analysis results are sent to the supply material scheduling module. If the material analysis result CZ t ≤0, the requirement is met and subsequent calculations are terminated;

[0056] Among them, CZ t Indicates the material analysis results in the current supply cycle t, KC t Indicates the material inventory data collected by the inventory data collection unit in the current supply cycle t, DQWL t,m+1 Represents the predicted material demand data under the current supply cycle t.

[0057] The supply material scheduling module is used to schedule materials and make up the difference of materials in combination with the material analysis results. The supply material scheduling module includes a supplier material data collection unit, a material manufacturer data collection unit and a material difference calculation unit. The supplier material data collection unit is used to collect the supplier material data of the current held materials GYS = [GYS1,…,GYS k ,…,GYS K ], the material manufacturer data collection unit is used to collect the manufacturer's production speed V t The calculation process of the material difference calculation unit is: determine whether the material storage volume of the supplier can meet the material analysis result CZ tIf it can be met, the calculation is terminated. If it cannot be met, the time required to make up the difference is calculated based on the manufacturer's production speed. The material difference calculation unit calculates the material difference and gives the time required to make up the difference.

[0058] Among them, T t represents the time required to make up the difference in the current supply cycle t, CZ t Indicates the material analysis results in the current supply cycle t, GYS k represents the material storage volume of the kth supplier, V t Represents the production speed of the manufacturer in the current supply cycle t.

[0059] Embodiment 1:

[0060] The material demand data in the current historical records is LS = [5, 6.5, 5, 7, 5.5] (in 10,000 pieces), GYS = [0.36, 0.32, 0.78], and max{LS} = 7. The demand data of the current supply cycle materials DQ = [4.5, 6, 3.8, 5, 5.5], m = 5, and based on

[0061] At this point, the predicted material demand data can be obtained The calculation result completes the predicted material demand data DQWL under the current supply cycle t. t,m+1 Calculation of

[0062] At this time, the inventory KC t = 53,845 pieces, and CZ is calculated t =DQWL t,m+1 -KC t =6.8890-5.3845=1.5045. It can be seen that the calculation result does not meet the demand, so the material analysis result is sent to the supply material scheduling module;

[0063] Determine whether the supplier's material storage capacity can meet the material analysis results CZ t ,Right now 10,000 pieces;

[0064] The time required to make up the difference in the current supply cycle t Therefore, the time to make up the difference is 1 day, thus completing the actual forecast demand;

[0065] Embodiment 2:

[0066] The material demand data in the current historical records is LS = [4, 6.5, 5, 6, 5.5] (in 10,000 pieces). At this time, max{LS} = 6.5. The demand data of the current supply cycle materials DQ = [4.5, 6, 6.2, 5, 5.5], m = 5, and based on

[0067] At this point, the predicted material demand data can be obtained The calculation result completes the predicted material demand data DQWL under the current supply cycle t. t,m+1 Calculation of

[0068] At this time, the inventory KC t = 69,845 pieces, and CZ is calculated t =DQWL t,m+1 -KC t =6.2737-6.9845=-0.7108<0, the requirement is met and subsequent calculations are terminated.

[0069] See also Figure 2 The present invention also provides an enterprise supply chain optimization method, based on the above-mentioned enterprise supply chain optimization system, comprising the following steps:

[0070] S1. Collect the demand data of materials in the historical records and the demand data of materials in the current supply cycle t;

[0071] S2. Calculate the demand trend of materials in the current supply cycle and calculate it in combination with the demand data of materials in the historical records to obtain the predicted material demand data;

[0072] S3, collecting material inventory data corresponding to the predicted material demand data after calculation by the supply demand confirmation module;

[0073] S4, calculate and obtain the material analysis results, and determine whether the material inventory data can meet the predicted material demand data. If the material analysis results are determined to meet the demand, terminate the step; if the material analysis results are determined to not meet the demand, execute step S5;

[0074] S5, collect the material data of the supplier currently holding the material, and determine whether the supplier can replenish the material. If so, terminate the step; if not, execute step S6;

[0075] S6. Calculate the difference in materials based on the manufacturer’s production speed and give the time required to make up the difference.

[0076] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An enterprise supply chain optimization system, characterized by: Including supply demand confirmation module, inventory management module and supply material scheduling module; The supply demand confirmation module includes a historical supply demand data collection unit and a supply demand prediction unit. The historical supply demand data collection unit is used to collect the demand data of materials in the historical records and the demand data of materials in the current supply cycle. The supply demand prediction unit calculates the demand trend of materials in the current supply cycle and calculates it in combination with the demand data of materials in the historical records to obtain the predicted material demand data. The supply demand confirmation module sends the calculated predicted material demand data to the inventory management module. The inventory management module includes an inventory data collection unit and an inventory data calculation and analysis unit. The inventory data collection unit is used to collect material inventory data corresponding to the predicted material demand data after the supply demand confirmation module calculates and completes the calculation. The inventory data calculation and analysis unit is used to analyze and calculate whether the material inventory data can meet the predicted material demand data, and obtain the material analysis result. If the material analysis result is judged to meet the demand, the subsequent calculation is terminated. If the material analysis result is judged to not meet the demand, the material analysis result is sent to the supply material scheduling module; The supply material scheduling module is used to schedule materials and make up the material difference in combination with the material analysis results. The supply material scheduling module includes a supplier material data collection unit, a material manufacturer data collection unit and a material difference calculation unit. The supplier material data collection unit is used to collect the supplier material data of the currently held materials, and the material manufacturer data collection unit is used to collect the manufacturer's production speed. The material difference calculation unit calculates the material difference and gives the time required to make up the difference.

2. The enterprise supply chain optimization system according to claim 1, characterized in that: The expression for collecting the demand data of materials in the historical records and the demand data of materials in the current supply cycle by the historical supply demand data collection unit is as follows: LS=[LSWL1,…,LSWL i ,…,LSWL n ] DQ=[DQWL t，1 ,…,DQWL t，j ,…,DQWL t，m ] Among them, LSWL1,…,LSWL i ,…,LSWL n Represents 1 to n different historical supply and demand data, DQWL t，1 ,…,DQWL t，j ,…,DQWL t，m They respectively represent the demand data of the 1st material, ..., the demand data of the jth material, ..., the demand data of the mth material in the current supply cycle t. LS represents the historical supply demand data set, and DQ represents the demand data set of materials in the current supply cycle t.

3. The enterprise supply chain optimization system according to claim 1, characterized in that: The supply demand forecasting unit calculates and obtains the predicted material demand data by calculating the following calculation expression: Among them, DQWL t，m+1 represents the predicted material demand data under the current supply cycle t, max{LS} represents the maximum value in the historical supply demand data, LSWL i represents the i-th historical supply and demand data, It represents the sum of n different historical supply and demand data, QS t Indicates the demand trend of materials in the current supply cycle.

4. The enterprise supply chain optimization system according to claim 2, characterized in that: The demand trend of the material in the current supply cycle QS t The calculation expression is as follows: Among them, QS t Indicates the demand trend of materials in the current supply cycle, DQWL t，j Indicates the demand data of the jth material in the current supply cycle t, DQWL t，j-1 Indicates the demand data of the j-1th material in the current supply cycle t. It means to sum m-1 data.

5. The enterprise supply chain optimization system according to claim 1, characterized in that: The steps of analyzing by the inventory data calculation and analysis unit in the inventory management module are as follows: A1. DQWL is the material demand data DQWL predicted under the current supply cycle t. t，m+1 Material inventory data KC collected by the inventory data collection unit t , calculate and obtain the material analysis result CZ t ; A2. If the material analysis result is CZ t >0, the demand is not met, and the material analysis results are sent to the supply material scheduling module. If the material analysis results CZ t ≤0, the requirement is met and subsequent calculations are terminated.

6. The enterprise supply chain optimization system according to claim 5, characterized in that: The material analysis result CZ is calculated in step A1 t The expression is as follows: CZ t =DQWL t，m+1 -KC t Among them, CZ t Indicates the material analysis results in the current supply cycle t, KC t Indicates the material inventory data collected by the inventory data collection unit in the current supply cycle t, DQWL t，m+1 Represents the predicted material demand data under the current supply cycle t.

7. The enterprise supply chain optimization system according to claim 1, characterized in that: The supplier material data collected by the supplier material data collection unit is expressed as follows: GYS=[GYS1,…,GYS k ,…,GYS K ] Among them, GYS1,…,GYS k ,…,GYS K They respectively represent the material storage quantity of the 1st supplier, …, the kth supplier, …, and the Kth supplier, and GYS represents the supplier material data set.

8. The enterprise supply chain optimization system according to claim 1, characterized in that: The specific steps of the material difference calculation unit for calculation are as follows: B1. Determine whether the supplier's material storage capacity can meet the material analysis results CZ t , if it can be satisfied, then terminate the calculation, if it cannot be satisfied, then execute step B2; B2. If the requirement cannot be met, calculate the difference and work out the time required to make up the difference based on the manufacturer’s production speed.

9. The enterprise supply chain optimization system according to claim 8, characterized in that: The calculation expression for the supplementary time in step B2 is as follows: Among them, T t represents the time required to make up the difference in the current supply cycle t, CZ t Indicates the material analysis results in the current supply cycle t, GYS k represents the material storage volume of the kth supplier, V t Represents the production speed of the manufacturer in the current supply cycle t.

10. A method for optimizing an enterprise supply chain, based on an enterprise supply chain optimization system according to any one of claims 1 to 9, characterized in that: The following steps are involved: S1. Collect the demand data of materials in the historical records and the demand data of materials in the current supply cycle t; S2. Calculate the demand trend of materials in the current supply cycle and calculate it in combination with the demand data of materials in the historical records to obtain the predicted material demand data; S3, collecting material inventory data corresponding to the predicted material demand data after calculation by the supply demand confirmation module; S4, calculate and obtain the material analysis results, and determine whether the material inventory data can meet the predicted material demand data. If the material analysis results are determined to meet the demand, terminate the step; if the material analysis results are determined to not meet the demand, execute step S5; S5, collect the material data of the supplier currently holding the materials, and determine whether the supplier can replenish the materials. If so, terminate the step; if not, execute step S6; S6. Calculate the difference in materials based on the manufacturer’s production speed and give the time required to make up the difference.

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