Production planning support device, production planning support method, and program

Abstract

A production planning support device (1) is provided with: a variation factor index information generation unit (12) that, on the basis of information relating to a repeat customer of a product, generates variation factor index information indicating a variation factor index that causes a variation in the demand for the product; a demand variation record information generation unit (15) that, on the basis of demand record information including past sales plans and demand records for the product, generates demand variation record information indicating records of variations in the demand for the product; a demand variation value information generation unit (17) that, on the basis of the variation factor index information and the demand variation record information, generates demand variation value information indicating a demand variation value; a customer dependency information generation unit (19) that, on the basis of the demand record information, generates customer dependency information indicating customer dependency; and a risk calculation unit (24) that calculates a risk value concerning demand variation on the basis of the demand variation value information and the customer dependency information and that outputs risk value information indicating the risk value concerning demand variation.

Description

Technical Field

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[0001] The present disclosure relates to a production plan support device, a production plan support method, and a program.

Background Art

[0002] With the COVID-19 pandemic, it has become extremely difficult worldwide to procure electronic components, long-lead-time components, etc. In the manufacturing industry, in order to secure parts, there are cases where the production quantity of products is planned in excess to secure an excess quantity of parts. However, the act of planning the production quantity of products in excess depends greatly on the experience and intuition of the factory operation staff, and there is a risk of ordering too few or too many parts, resulting in excess inventory or shortages due to inventory levels. Hereinafter, the risk of excess inventory or shortages due to inventory levels is referred to as inventory risk. Conventionally, for parts procurement, the required quantity of parts is calculated by multiplying the number of parts constituting the products produced at the production site by the planned quantity of products to be produced, and based on the required quantity of parts and the inventory quantity of parts, the procurement quantity of parts is calculated.

[0003] In Patent Document 1, in addition to the above method, a simulation device is disclosed that calculates the procurement quantity of parts by taking into account the lead time from the input of parts to the production site to the completion of product production among multiple production sites.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, the technology described in Patent Document 1 does not take into account fluctuations in demand from customers who repeatedly purchase the product when calculating the planned quantity to be produced. As a result, the accuracy of the planned quantity to be produced is low, and consequently, there is a risk that the quantity of parts ordered will be either too small or too large.

[0006] This disclosure is made to address the problems described above and aims to reduce the risk of insufficient or excessive quantities of parts being ordered in the product production plan. [Means for solving the problem]

[0007] To achieve the above objectives, the production planning support device relating to this disclosure comprises a fluctuation factor indicator information generation unit, a demand fluctuation performance information generation unit, a demand fluctuation value information generation unit, a customer dependency information generation unit, and a risk calculation unit. The fluctuation factor indicator information generation unit generates fluctuation factor indicator information that shows fluctuation factor indicators that are factors causing fluctuations in product demand, based on information about repeat customers of the product. The demand fluctuation performance information generation unit generates demand fluctuation performance information that shows the actual fluctuations in product demand, based on demand performance information including past sales plans and demand performance of the product. The demand fluctuation value information generation unit generates demand fluctuation value information that shows the demand fluctuation value representing how much the demand for the product fluctuates, based on the fluctuation factor indicator information and the demand fluctuation performance information. The customer dependency information generation unit generates customer dependency information that shows the customer dependency representing how much the product is purchased by a particular repeat customer, based on the demand performance information. The risk calculation unit calculates the risk value of demand fluctuations based on the demand fluctuation value information and the customer dependency information, and outputs risk value information that shows the risk value of demand fluctuations. [Effects of the Invention]

[0008] According to this disclosure, by presenting users with demand fluctuation risk values ​​that reflect information on repeat customers, this can be used to determine planned quantities in product production plans. This improves the accuracy of planned product production quantities, ultimately reducing the risk of under- or over-procuring parts in product production plans. [Brief explanation of the drawing]

[0009] [Figure 1] A diagram showing an example configuration of a production planning support device according to an embodiment. [Figure 2] An illustrative diagram showing the economic trends of repeat customers and the impact of seasonal fluctuations in the location of repeat customers according to the embodiment. [Figure 3] A diagram showing an example of variable factor indicator information according to the embodiment. [Figure 4] An illustrative diagram showing the impact of demand fluctuations and component commonality on the product according to the embodiment. [Figure 5] A diagram showing an example of demand fluctuation data related to the embodiment. [Figure 6] An illustrative diagram showing the impact of customer dependency in the embodiment. [Figure 7] A diagram showing an example of customer dependency information according to the embodiment. [Figure 8] A diagram showing an example of component commonality information according to the embodiment. [Figure 9] Flowchart showing production planning support processing according to the embodiment [Figure 10] A diagram showing an example of the hardware configuration of a production planning support device according to an embodiment. [Modes for carrying out the invention]

[0010] The production planning support device, production planning support method, and program according to this embodiment will be described in detail below with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals. In the following description, customers who repeatedly purchase products will be referred to as repeat customers.

[0011] The functional configuration of the production planning support device 1 according to the embodiment will be explained with reference to Figure 1. As shown in Figure 1, the production planning support device 1 comprises an information collection unit 11 that collects information on repeat customers, a fluctuation factor indicator information generation unit 12 that generates fluctuation factor indicator information showing fluctuation factor indicators that are factors that cause fluctuations in product demand based on information on repeat customers, a fluctuation factor indicator information storage unit 13 that stores the fluctuation factor indicator information, a demand performance information storage unit 14 that stores demand performance information including past sales plans and demand performance of products, a demand fluctuation performance information generation unit 15 that generates demand fluctuation performance information showing actual demand fluctuations of products based on the demand performance information, and a demand fluctuation performance information storage unit 16 that stores the demand fluctuation performance information.

[0012] Furthermore, the production planning support device 1 includes a demand fluctuation value information generation unit 17 that generates demand fluctuation value information indicating how much the demand for a product will fluctuate based on fluctuation factor indicator information and actual demand fluctuation information; a demand fluctuation value information storage unit 18 that stores the demand fluctuation value information; a customer dependency information generation unit 19 that generates customer dependency information indicating how much a product is purchased by a specific repeat customer based on actual demand information; a customer dependency information storage unit 20 that stores the customer dependency information; a component configuration information storage unit 21 that stores component configuration information indicating the component configuration of a product; a component commonality information generation unit 22 that generates component commonality information indicating how many products a component is used in common with all products based on the component configuration information; a component commonality information storage unit 23 that stores the component commonality information; and a risk calculation unit 24 that calculates a risk value of the inventory risk of components based on the demand fluctuation value information, customer dependency information, and component commonality information.

[0013] The information gathering unit 11 collects various information about repeat customers that can serve as indicators of fluctuation factors, for example, from the internet. The information gathering unit 11 collects information such as asset information and net profit from the income statement listed on the repeat customer's balance sheet, the GDP (Gross Domestic Product), consumer price index and policy interest rate of the repeat customer's country, and seasonal fluctuations in the repeat customer's location. Users may also be allowed to input information about repeat customers into the information gathering unit 11.

[0014] Here, we will explain the impact of repeat customers' economic trends and seasonal fluctuations in their locations on parts inventory using Figure 2. The example in Figure 2 shows the fluctuation factor indicators for a combination of the repeat customers' economic situation and climate change information in their locations. Pattern 1 shows a case where the repeat customers' financial situation deteriorates, but there is no change in climate change in their locations. Pattern 2 shows a case where the repeat customers' financial situation is strong, but there is significant climate change in their locations.

[0015] In Pattern 1, if the financial situation of repeat customers deteriorates, demand tends to shrink in the future. Due to the nature of the product, climate change has the property of increasing demand as the fluctuations become greater. For example, a heatwave increases the demand for air conditioning equipment, and a cold wave increases the demand for heating equipment. In Pattern 1, since the climate change in the location of the repeat customers remains unchanged from previous years, it is predicted that the demand for the product will decrease due to the reduction in demand caused by the deterioration of the financial situation of repeat customers. A decrease in the demand for the product increases the risk of excess inventory of the parts used in that product.

[0016] In Pattern 2, the financial condition of repeat customers is strong, leading to a tendency for demand to expand in the future. Furthermore, climate change in the repeat customers' locations will result in a colder-than-usual period, further increasing demand. Due to the increased demand resulting from strong financial conditions and the significantly altered climate, a substantial increase in demand for the manufacturing plant is predicted. Increased demand for products raises the risk of shortages of components used in those products.

[0017] Returning to FIG. 1, the variation factor index information generation unit 12 generates variation factor index information based on the information regarding repeat customers collected by the information collection unit 11. The variation factor index information generation unit 12 stores the generated variation factor index information in the variation factor index information storage unit 13.

[0018] An example of the variation factor index information is shown in FIG. 3. FIG. 3 is a diagram showing an example of the economic trend of repeat customers, which is one of the variation factor indexes. The variation factor index information generation unit 12 calculates the total assets, net assets, negative assets, and the ratio of net assets to total assets, i.e., the equity ratio, of customers C1, C2, and C3 who are repeat customers collected by the information collection unit 11, from the balance sheets, profit and loss statements, etc. of customers C1, C2, and C3, and generates variation factor index information as shown in FIG. 3. For example, customer C1 has total assets of 1 billion yen, net assets of 500 million yen, negative assets of 500 million yen, and an equity ratio of 0.5. Generally, it can be said that the higher the equity ratio, the higher the stability, and it can be judged that the demand is less likely to fluctuate. Conversely, the lower the equity ratio, the lower the stability, and it can be judged that the demand is more likely to fluctuate.

[0019] Subsequently, the influence of product demand fluctuations and component commonality on component inventory levels will be described using FIG. 4. In the example of FIG. 4, there are large customers who are repeat customers with a large sales scale, general customers who are repeat customers with a medium sales scale, and small customers who are repeat customers with a small sales scale. Also, there is component p1 as one of the components constituting product P1, and component p2 as one of the components constituting products P2 and P3. Component p1, which is used only in product P1 purchased only by large customers, is greatly affected by the demand fluctuations of large customers. That is, when the demand from large customers fluctuates significantly, the inventory risk of component p1 increases. On the other hand, component p2, which is used in both products P2 and P3 widely purchased by large customers, general customers, and small customers, is less affected by the demand fluctuations of specific repeat customers. However, even for component p2, when the overall demand fluctuates significantly, the inventory risk increases.

[0020] As described above, inventory levels of parts used in products purchased intensively by specific repeat customers are heavily influenced by fluctuations in demand from those specific repeat customers, and this influence increases with the size of the customer. Furthermore, inventory levels of parts used only in a single product are even more heavily influenced by fluctuations in demand from that specific repeat customer. On the other hand, inventory levels of parts used in products purchased by a wide range of repeat customers are less affected by fluctuations in demand from specific repeat customers. Furthermore, inventory levels of parts used in multiple products are even less affected by fluctuations in demand from specific repeat customers.

[0021] Returning to Figure 1, the demand fluctuation performance information generation unit 15 generates demand fluctuation performance information showing the actual demand fluctuations of the product based on the demand performance information stored in the demand performance information storage unit 14. The demand performance information includes the product's past sales plans and actual demand. The demand performance information may be input by the user into the production planning support device 1, for example, or obtained from an external device or system. The demand fluctuation performance information generation unit 15 stores the generated demand fluctuation performance information in the demand fluctuation performance information storage unit 16.

[0022] An example of demand fluctuation performance information is shown in Figure 5. Figure 5 is an example of demand fluctuation performance information for product P1. In the example in Figure 5, the demand fluctuation performance information has the following items: "Product" which indicates the product name, "Customer" which indicates the name of the repeat customer who purchased the product, and "Demand Fluctuation" which indicates the ratio of the sales plan to the actual demand from six months prior to one month prior, starting from a specified month. "Demand Fluctuation" has the following items: "n-6", "n-5", "n-4", "n-3", "n-2", and "n-1", which indicate the ratio of the sales plan to the actual demand for each month from six months prior to one month prior, starting from a specified month (for example, the current month). For example, the ratio of the sales plan to the actual demand for product P1 for customer C1 six months ago is 20%. "Product" and "Customer" do not have to be names, but can be information that identifies the product and information that identifies the repeat customer, respectively. The starting month can also be specified by the user.

[0023] Returning to Figure 1, the demand fluctuation value information generation unit 17 generates demand fluctuation value information based on the fluctuation factor indicator information stored in the fluctuation factor indicator information storage unit 13 and the demand fluctuation actual information stored in the demand fluctuation actual information storage unit 16. For example, the demand fluctuation value information generation unit 17 weights the demand fluctuation actual information according to the likelihood or difficulty of demand fluctuation due to the fluctuation factor indicators indicated by the fluctuation factor indicator information, and generates demand fluctuation value information. By taking into account the influence of the fluctuation factor indicators on demand fluctuations, the accuracy of the demand fluctuation value is improved.

[0024] When generating demand fluctuation value information based on the fluctuation factor indicator information shown in Figure 3 and the demand fluctuation performance information shown in Figure 5, the demand fluctuation value information generation unit 17, for example, determines that demand is less likely to fluctuate if the equity ratio of repeat customers is greater than a threshold, and calculates the demand fluctuation value for that repeat customer and product combination by multiplying the standard deviation of the ratio of the sales plan to the actual demand for the product each month of that repeat customer by a weighting coefficient of less than 1.0. On the other hand, if the equity ratio of repeat customers is below a threshold, it determines that demand is more likely to fluctuate, and calculates the demand fluctuation value for that repeat customer and product combination by multiplying the standard deviation of the ratio of the sales plan to the actual demand for the product each month of that repeat customer by a weighting coefficient of 1.0 or greater. The demand fluctuation value information generation unit 17 stores the calculated demand fluctuation value information in the demand fluctuation value information storage unit 18.

[0025] Furthermore, if the increase or decrease in the quantity of products requested by repeat customers can be predicted based on the fluctuation factor indicators shown in the fluctuation factor indicator information, the demand fluctuation value information generation unit 17 may apply weighting to the standard deviation of the ratio of the sales plan to the actual monthly demand for the product of the repeat customer, based on the fluctuation factor indicators, and calculate the demand fluctuation value for the combination of the repeat customer and the product.

[0026] Next, we will explain the impact of customer dependency on inventory levels of parts using Figure 6. Customer dependency is an indicator that shows the proportion of a product purchased by a particular repeat customer. In the example in Figure 6, there is customer C1 who purchases 10 units each of products P1, P2, and P3; customers C2 and C3 who purchase 5 units each of products P2 and P3; and customers C4, C5, and C6 who purchase 3 units each of product P3. Customer dependency can be calculated by dividing the number of purchases by a customer by the total number of purchases. Since customer C1 has purchased 10 units of product P1, the customer dependency of the largest purchaser is the number of purchases by the largest purchaser / total purchases = 10 / 10 = 1.0. Since customers C1, C2, and C3 have purchased 10, 5, and 5 units of product P2, respectively, the customer dependency of the largest purchaser is the number of purchases by the largest purchaser / total purchases = 10 / (10 + 5 + 5) = 0.5. Product P3 has been purchased by customers C1, C2, C3, C4, C5, and C6 in quantities of 10, 5, 5, 3, 3, and 3 units respectively. Therefore, the customer dependency ratio for the largest purchasing customer is calculated as: Number of purchases by the largest purchasing customer / Total number of purchases = 10 / (10 + 5 + 5 + 3 + 3 + 3) = 0.34 (rounded down to the third decimal place).

[0027] As described above, customer dependency is a quantitative indicator that measures how much product demand depends on a particular repeat customer. A value closer to 1 indicates high dependency, while a value closer to 0 indicates low dependency. The higher the customer dependency of a product, the higher the risk of excess inventory due to changes in the requirements of that repeat customer. Conversely, the lower the customer dependency of a product, the lower the risk of excess inventory due to changes in the requirements of that repeat customer.

[0028] Returning to Figure 1, the customer dependency information generation unit 19 generates customer dependency information based on the demand performance information stored in the demand performance information storage unit 14. The customer dependency information generation unit 19 stores the generated customer dependency information in the customer dependency information storage unit 20.

[0029] An example of customer dependency information is shown in Figure 7. Figure 7 is an example of customer dependency information for product P1. In the example in Figure 7, the customer dependency information has the following items: "Product" which indicates the product name, "Customer" which indicates the name of the repeat customer who purchased the product, "Sales Volume" which indicates the number of units sold during a specified period, and "Customer Dependency" which indicates the customer dependency of the product. In the example in Figure 7, product P1 has been sold to customers C1, C2, C3, and C4 in quantities of 100, 1500, 120, and 20 units, respectively. Therefore, the customer with the largest purchase of product P1 is customer C2, and the customer dependency of the customer with the largest purchase is the number of units purchased by the customer with the largest purchase / total number of units purchased = 1500 / 1740 = 0.86 (rounded down to the third decimal place). "Product" and "Customer" do not have to be names, but can be information that identifies the product and information that identifies the repeat customer, respectively. The specified period can be the entire past period or a part of the past period.

[0030] Returning to Figure 1, the component commonality information generation unit 22 generates component commonality information based on the component configuration information stored in the component configuration information storage unit 21. The component commonality information generation unit 22 stores the generated component commonality information in the component commonality information storage unit 23. For example, the component commonality information generation unit 22 maps which products each component is used in based on the component configuration information, and calculates the percentage of products in which each component is used relative to all products as the component commonality.

[0031] An example of part commonality information is shown in Figure 8. In the example in Figure 8, the part commonality information has three items: "Product," which indicates the product name; "Part," which indicates the name of the part used in the product; and "Part Commonality," which indicates the degree of commonality of the part. For example, part p1 is used in products P1, P2, etc., and the part commonality is 0.98. "Product" and "Part" do not necessarily have to be names; any information that identifies the product and information that identifies the part are acceptable.

[0032] As described above, parts commonality is an indicator that shows how many products a part is used in common with all products. The higher the parts commonality, the lower the risk of parts remaining on shelves; conversely, the lower the parts commonality, the higher the risk of parts remaining on shelves.

[0033] Returning to Figure 1, the risk calculation unit 24 generates risk value information indicating the risk value of inventory remaining risk for parts based on the demand fluctuation value information stored in the demand fluctuation value information storage unit 18, the customer dependency information stored in the customer dependency information storage unit 20, and the parts commonality information stored in the parts commonality information storage unit 23. For example, the risk calculation unit 24 calculates the demand fluctuation risk value for a product by multiplying the demand fluctuation value for each product and repeat customer combination by the customer dependency for each corresponding product and repeat customer combination. Based on the parts commonality information, the risk calculation unit 24 calculates the risk value of inventory remaining risk for each part by dividing the sum of the demand fluctuation risk values ​​of the products used by the parts by the parts commonality. The risk calculation unit 24 outputs risk value information indicating the risk value of inventory remaining risk for parts. The method of outputting the risk value information may be, for example, by displaying it on the screen or by sending it to a user terminal used by the user.

[0034] The risk values ​​indicated by the risk value information output by the production planning support device 1 can be used to determine the quantity of parts to be procured, such as by setting a safety factor for calculating safety stock.

[0035] Here, the flow of the production planning support process executed by the production planning support device 1 will be explained using Figure 9. The production planning support process shown in Figure 9 starts, for example, when a risk value output instruction is input to the production planning support device 1. The information gathering unit 11 of the production planning support device 1 collects information on repeat customers that can serve as indicators of fluctuation factors, for example, from the internet (step S11). The information on repeat customers collected by the information gathering unit 11 includes, for example, asset information and net profit from the income statement listed on the repeat customer's balance sheet, the GDP of the repeat customer's country, the consumer price index and policy interest rate, and seasonal fluctuations in the repeat customer's location.

[0036] The fluctuation factor indicator information generation unit 12 generates fluctuation factor indicator information based on the information about repeat customers collected by the information collection unit 11 (step S12). The fluctuation factor indicator information generation unit 12 stores the generated fluctuation factor indicator information in the fluctuation factor indicator information storage unit 13.

[0037] In the example shown in Figure 3, the fluctuation factor indicator information shows the economic trends of repeat customers, which is one of the fluctuation factor indicators. The fluctuation factor indicator information generation unit 12 calculates the total assets, net assets, liabilities, and equity ratio (the ratio of net assets to total assets) of customers C1, C2, and C3 from the balance sheets, income statements, etc. of customers C1, C2, and C3 collected by the information collection unit 11, and generates the fluctuation factor indicator information shown in Figure 3. Generally, the higher the equity ratio, the greater the stability, and the less likely demand is to fluctuate. Conversely, the lower the equity ratio, the less stable the company, and the more likely demand is to fluctuate.

[0038] Returning to Figure 9, the demand fluctuation performance information generation unit 15 generates demand fluctuation performance information showing the actual demand fluctuations of the product based on the demand performance information stored in the demand performance information storage unit 14 (step S13). The demand performance information includes the product's past sales plans and actual demand. The demand performance information may be input by the user into the production planning support device 1, for example, or obtained from an external device or system. The demand fluctuation performance information generation unit 15 stores the generated demand fluctuation performance information in the demand fluctuation performance information storage unit 16.

[0039] In the example in Figure 5, the demand fluctuation information includes the following items: "Product," which indicates the product name; "Customer," which indicates the name of a repeat customer who purchased the product; and "Demand Fluctuation," which shows the ratio of the sales plan to the actual demand from six months prior to one month prior, starting from a specified month. The "Demand Fluctuation" item includes "n-6," "n-5," "n-4," "n-3," "n-2," and "n-1," respectively, which show the ratio of the sales plan to the actual demand for each month from six months prior to one month prior, starting from a specified month (for example, the current month).

[0040] Returning to Figure 9, the demand fluctuation value information generation unit 17 generates demand fluctuation value information based on the fluctuation factor indicator information stored in the fluctuation factor indicator information storage unit 13 and the demand fluctuation actual information stored in the demand fluctuation actual information storage unit 16 (step S14). The demand fluctuation value information generation unit 17 stores the generated demand fluctuation value information in the demand fluctuation value information storage unit 18.

[0041] When generating demand fluctuation value information based on the fluctuation factor indicator information shown in Figure 3 and the demand fluctuation performance information shown in Figure 5, the demand fluctuation value information generation unit 17, for example, determines that demand is less likely to fluctuate if the equity ratio of repeat customers is greater than a threshold, and calculates the demand fluctuation value for that repeat customer and product combination by multiplying the standard deviation of the ratio of the sales plan to the actual demand for the product each month of that repeat customer by a weighting coefficient of less than 1.0. On the other hand, if the equity ratio of repeat customers is below a threshold, it determines that demand is more likely to fluctuate, and calculates the demand fluctuation value for that repeat customer and product combination by multiplying the standard deviation of the ratio of the sales plan to the actual demand for the product each month of that repeat customer by a weighting coefficient of 1.0 or greater.

[0042] Returning to Figure 9, the customer dependency information generation unit 19 generates customer dependency information based on the demand performance information stored in the demand performance information storage unit 14 (step S15). The customer dependency information generation unit 19 stores the generated customer dependency information in the customer dependency information storage unit 20.

[0043] In the example in Figure 7, the customer dependency information includes the following items: "Product" indicating the product name, "Customer" indicating the name of the repeat customer who purchased the product, "Sales Volume" indicating the number of units sold over a specified period, and "Customer Dependency" indicating the customer dependency of the product. The customer dependency for repeat customers is calculated as the number of purchases by the repeat customer divided by the total number of purchases.

[0044] Returning to Figure 9, the component commonality information generation unit 22 generates component commonality information based on the component configuration information stored in the component configuration information storage unit 21 (step S16). The component commonality information generation unit 22 stores the generated component commonality information in the component commonality information storage unit 23.

[0045] In the example shown in Figure 8, the parts commonality information includes the following items: "Product" indicating the product name, "Part" indicating the name of the part used in the product, and "Part Commonality" indicating the degree of commonality of the parts. The parts commonality information generation unit 22 maps which products each part is used in based on the parts configuration information, and calculates the percentage of all products in which each part is used as the parts commonality.

[0046] Returning to Figure 9, the risk calculation unit 24 generates risk value information indicating the risk value of the remaining stock risk of parts based on the demand fluctuation value information stored in the demand fluctuation value information storage unit 18, the customer dependency information stored in the customer dependency information storage unit 20, and the parts commonality information stored in the parts commonality information storage unit 23 (step S17).

[0047] For example, the risk calculation unit 24 calculates the demand fluctuation risk value for a product by multiplying the demand fluctuation value for each product-repeat customer combination by the customer dependency ratio for each corresponding product-repeat customer combination. Based on the parts commonality information, the risk calculation unit 24 calculates the risk value of the remaining stock risk for each part by dividing the sum of the demand fluctuation risk values ​​for the products used by each part by the parts commonality ratio.

[0048] The risk calculation unit 24 outputs risk value information indicating the risk value of the remaining inventory risk of parts (step S18), and terminates the process. The risk value information may be output by, for example, displaying it on the screen or sending it to a user terminal used by the user.

[0049] According to the production planning support device 1 of the embodiment, by presenting the user with a risk value for the risk of remaining stock of parts based on a risk value for demand fluctuations that reflects information on repeat customers, it is possible to use this to determine the quantity of parts to be procured in the product production plan, thereby reducing the risk of the quantity of parts procured in the product production plan being too small or too large.

[0050] The hardware configuration of the production planning support device 1 will be explained using Figure 10. As shown in Figure 10, the production planning support device 1 includes a temporary storage unit 101, a storage unit 102, a calculation unit 103, an input unit 104, a transmitting / receiving unit 105, and a display unit 106. The temporary storage unit 101, storage unit 102, input unit 104, transmitting / receiving unit 105, and display unit 106 are all connected to the calculation unit 103 via a BUS.

[0051] The calculation unit 103 is, for example, a CPU (Central Processing Unit). The calculation unit 103 executes the processing of the fluctuation factor indicator information generation unit 12, the demand fluctuation performance information generation unit 15, the demand fluctuation value information generation unit 17, the customer dependency information generation unit 19, the parts commonality information generation unit 22, and the risk calculation unit 24 according to the control program stored in the storage unit 102.

[0052] The temporary storage unit 101 is, for example, RAM (Random-Access Memory). The temporary storage unit 101 loads the control program stored in the storage unit 102 and uses it as a work area for the calculation unit 103.

[0053] The memory unit 102 is a non-volatile memory such as flash memory, hard disk, DVD-RAM (Digital Versatile Disc - Random Access Memory), or DVD-RW (Digital Versatile Disc - ReWritable). The memory unit 102 pre-stores a program for causing the calculation unit 103 to perform processing for the production planning support device 1, and also supplies the information stored in this program to the calculation unit 103 according to the instructions of the calculation unit 103, and stores the information supplied from the calculation unit 103. The fluctuation factor indicator information storage unit 13, the demand performance information storage unit 14, the demand fluctuation performance information storage unit 16, the demand fluctuation value information storage unit 18, the customer dependency information storage unit 20, the parts configuration information storage unit 21, and the parts commonality information storage unit 23 are all configured in the memory unit 102.

[0054] The input unit 104 is an interface device that connects input devices such as a keyboard, pointing device, and voice input device to the BUS. Information entered by the user is supplied to the calculation unit 103 via the input unit 104. In a configuration where the user can input information about repeat customers to the information collection unit 11, the input unit 104 functions as the information collection unit 11.

[0055] The transmitting / receiving unit 105 is a network termination device or wireless communication device connected to a network, and a serial interface or LAN (Local Area Network) interface connected to them. The transmitting / receiving unit 105 functions as an information collection unit 11. In a configuration where the risk calculation unit 24 transmits risk value information to a user terminal, the transmitting / receiving unit 105 functions as the risk calculation unit 24.

[0056] The display unit 106 is a display device such as an LCD (Liquid Crystal Display) or an organic EL (electroluminescence) display. In a configuration where the risk calculation unit 24 displays risk value information on the screen, the display unit 106 functions as the risk calculation unit 24.

[0057] The processing of the information collection unit 11, fluctuation factor indicator information generation unit 12, fluctuation factor indicator information storage unit 13, demand performance information storage unit 14, demand fluctuation performance information generation unit 15, demand fluctuation performance information storage unit 16, demand fluctuation value information generation unit 17, demand fluctuation value information storage unit 18, customer dependency information generation unit 19, customer dependency information storage unit 20, component configuration information storage unit 21, component commonality information generation unit 22, component commonality information storage unit 23, and risk calculation unit 24 of the production planning support device 1 shown in Figure 1 is performed by a control program that uses resources such as the temporary storage unit 101, calculation unit 103, storage unit 102, input unit 104, transmission / reception unit 105, and display unit 106 to process the information collection unit 11, fluctuation factor indicator information generation unit 12, fluctuation factor indicator information storage unit 13, demand performance information storage unit 14, demand fluctuation performance information generation unit 15, demand fluctuation performance information storage unit 16, demand fluctuation value information generation unit 17, demand fluctuation value information storage unit 18, customer dependency information generation unit 19, customer dependency information storage unit 20, component configuration information storage unit 21, component commonality information generation unit 22, component commonality information storage unit 23, and risk calculation unit 24.

[0058] Furthermore, the aforementioned hardware configuration and flowchart are examples only and can be changed and modified as needed.

[0059] The core components of the production planning support device 1, such as the calculation unit 103, temporary storage unit 101, storage unit 102, input unit 104, transmission / reception unit 105, and display unit 106, can be implemented using a standard computer system, rather than a dedicated system. For example, the production planning support device 1 can be configured by distributing a computer-readable recording medium such as a flexible disk, CD-ROM (Compact Disc - Read Only Memory), or DVD-ROM (Digital Versatile Disc - Read Only Memory) containing a computer program for performing the aforementioned operations, and then installing the computer program on a computer. Alternatively, the production planning support device 1 can be configured by storing the computer program on a storage device of a server on a communication network such as the Internet, and then downloading it from a standard computer system.

[0060] Furthermore, if the functions of the production planning support device 1 are realized through a division of labor between the OS (Operating System) and the application program, or through collaboration between the OS and the application program, then only the application program portion may be stored on the recording medium or storage device.

[0061] Furthermore, it is possible to superimpose a computer program onto the carrier wave and provide it via a communication network. For example, the computer program may be posted on a bulletin board system (BBS) on the communication network and provided via the communication network. The system may then be configured to execute the aforementioned processing by starting this computer program and running it under the control of the OS, just like other application programs.

[0062] In the above embodiment, the risk calculation unit 24 of the production planning support device 1 generates and outputs risk value information indicating the risk value of inventory risk for parts based on demand fluctuation value information, customer dependency information, and part commonality information, but is not limited to this. For example, the risk calculation unit 24 may generate and output risk value information indicating the risk value of demand fluctuations by summing the demand fluctuation values ​​obtained by multiplying the demand fluctuation value for each product and repeat customer combination by the customer dependency for each corresponding product and repeat customer combination. In this case, the production planning support device 1 does not need to include a part configuration information storage unit 21, a part commonality information generation unit 22, and a part commonality information storage unit 23.

[0063] In the above embodiment, the production planning support device 1 includes an information collection unit 11, a fluctuation factor indicator information generation unit 12, and a demand fluctuation performance information generation unit 15. However, it is not limited to this configuration, and the fluctuation factor indicator information storage unit 13 may store fluctuation factor indicator information entered by the user or acquired from an external device or system. Similarly, the demand fluctuation performance information storage unit 16 may store demand fluctuation performance information entered by the user or acquired from an external device or system. In these cases, the production planning support device 1 does not need to include the information collection unit 11, the fluctuation factor indicator information generation unit 12, and the demand fluctuation performance information generation unit 15.

[0064] In the above embodiment, the production planning support device 1 includes a variable factor indicator information storage unit 13, a demand performance information storage unit 14, a demand fluctuation performance information storage unit 16, a demand fluctuation value information storage unit 18, a customer dependency information storage unit 20, a component configuration information storage unit 21, and a component commonality information storage unit 23. However, these storage units may be provided by external devices or systems.

[0065] In the above embodiment, the risk calculation unit 24 calculated the risk value of demand fluctuation for a product by multiplying the demand fluctuation value for each product-repeat customer combination by the customer dependency ratio for each corresponding product-repeat customer combination. However, it is not limited to this. For example, the customer dependency ratio for a product may be set to the customer dependency ratio of the highest purchasing customer, and the risk calculation unit 24 may calculate the risk value of demand fluctuation for a product by multiplying the demand fluctuation value of the highest purchasing customer for each product by the customer dependency ratio.

[0066] Although preferred embodiments have been described in detail above, the invention is not limited to the embodiments described above, and various modifications and substitutions can be made to the embodiments described above without departing from the scope of the claims.

[0067] The various aspects of this disclosure are summarized below as an appendix.

[0068] (Note 1) A variable factor indicator information generation unit generates variable factor indicator information that shows variable factor indicators that are factors causing fluctuations in product demand, based on information about repeat customers of the product. A demand fluctuation performance information generation unit generates demand fluctuation performance information that shows the actual fluctuations in demand for a product, based on demand performance information including past sales plans and actual demand for the product. A demand fluctuation value information generation unit generates demand fluctuation value information that indicates how much the demand for a product will fluctuate, based on the fluctuation factor indicator information and the actual demand fluctuation information. A customer dependency information generation unit generates customer dependency information that indicates how much of the product is purchased by a particular repeat customer, based on the aforementioned demand performance information. A risk calculation unit calculates a risk value for demand fluctuations based on the demand fluctuation value information and the customer dependency information, and outputs risk value information indicating the risk value for demand fluctuations. A production planning support device equipped with the following features. (Note 2) The system further includes a component commonness information generation unit that generates component commonness information indicating how many products a component is used in common with all products, based on component configuration information that shows the component configuration of the product. The aforementioned risk calculation unit, Based on the demand fluctuation information, customer dependency information, and part commonality information, the system calculates the risk value of the part's remaining stock risk and outputs risk value information indicating the risk value of the part's remaining stock risk. The production planning support device described in Appendix 1. (Note 3) The aforementioned demand fluctuation value information generation unit, Based on the likelihood or difficulty of demand fluctuations indicated by the fluctuation factor indicators shown in the aforementioned fluctuation factor indicator information, the actual demand fluctuation information is weighted to generate demand fluctuation value information. Production planning support device as described in Appendix 1 or 2. (Note 4) The aforementioned risk calculation unit, The demand fluctuation risk value for a product is calculated by multiplying the demand fluctuation value for each product-and-repeat customer combination by the customer dependency ratio for that combination. A production planning support device as described in any of the appendices 1 to 3. (Note 5) The aforementioned risk calculation unit, The demand fluctuation value of the product is calculated by multiplying the demand fluctuation value of the product's largest customer by the customer dependency of that largest customer. This value is then used as the risk value for demand fluctuations of the product. A production planning support device as described in any of the appendices 1 to 3. (Note 6) The production planning support system is executed. The steps include generating variable factor indicator information that shows variable factor indicators that are factors causing fluctuations in product demand, based on information about repeat customers of the product, and A step of generating demand fluctuation information that shows the actual fluctuations in demand for a product, based on demand information including past sales plans and actual demand for the product, Based on the aforementioned fluctuation factor indicator information and the aforementioned demand fluctuation performance information, the step of generating demand fluctuation value information that indicates how much the demand for the product will fluctuate, Based on the aforementioned demand performance information, the step of generating customer dependency information that indicates how much of the product is purchased by a particular repeat customer, The steps include: calculating a risk value for demand fluctuations based on the demand fluctuation value information and the customer dependency information, and outputting risk value information indicating the risk value for demand fluctuations; A production planning support method equipped with the following features. (Note 7) Computers, A demand fluctuation value information generation unit generates demand fluctuation value information that indicates how much product demand will fluctuate, based on fluctuation factor indicator information that shows fluctuation factor indicators that are factors that cause fluctuations in product demand, and demand fluctuation performance information that shows actual fluctuations in product demand. Based on the aforementioned demand performance information, a customer dependency information generation unit generates customer dependency information that indicates the degree to which a product is purchased by a specific repeat customer, and A risk calculation unit calculates a risk value for demand fluctuations based on the demand fluctuation value information and the customer dependency information, and outputs risk value information indicating the risk value for demand fluctuations. A program that makes it function as such.

[0069] Furthermore, this disclosure allows for various embodiments and modifications without departing from its broad spirit and scope. The embodiments described above are for illustrative purposes only and do not limit the scope of this disclosure. That is, the scope of this disclosure is indicated by the claims, not by the embodiments. Various modifications made within the scope of the claims and the equivalent significance of the disclosure are considered to be within the scope of this disclosure.

[0070] This application is based on Japanese Patent Application No. 2023-69526, filed on April 20, 2023. The entire specification, claims, and drawings of Japanese Patent Application No. 2023-69526 are incorporated herein by reference. [Explanation of symbols]

[0071] 1 Production planning support device, 11 Information collection unit, 12 Fluctuation factor indicator information generation unit, 13 Fluctuation factor indicator information storage unit, 14 Demand performance information storage unit, 15 Demand fluctuation performance information generation unit, 16 Demand fluctuation performance information storage unit, 17 Demand fluctuation value information generation unit, 18 Demand fluctuation value information storage unit, 19 Customer dependency information generation unit, 20 Customer dependency information storage unit, 21 Component configuration information storage unit, 22 Component commonality information generation unit, 23 Component commonality information storage unit, 24 Risk calculation unit, 101 Temporary storage unit, 102 Storage unit, 103 Calculation unit, 104 Input unit, 105 Transmit / receive unit, 106 Display unit.

Claims

1. A variable factor indicator information generation unit generates variable factor indicator information that shows variable factor indicators that are factors causing fluctuations in product demand, based on information about repeat customers of the product. A demand fluctuation performance information generation unit generates demand fluctuation performance information that shows the actual fluctuations in demand for a product, based on demand performance information including past sales plans and actual demand for the product. A demand fluctuation value information generation unit generates demand fluctuation value information that indicates how much the demand for a product will fluctuate, based on the fluctuation factor indicator information and the actual demand fluctuation information. A customer dependency information generation unit generates customer dependency information that indicates how much of the product is purchased by a particular repeat customer, based on the aforementioned demand performance information. A risk calculation unit calculates a risk value for demand fluctuations based on the demand fluctuation value information and the customer dependency information, and outputs risk value information indicating the risk value for demand fluctuations. A production planning support device equipped with the following features.

2. The system further includes a component commonness information generation unit that generates component commonness information indicating how many products a component is used in common with all products, based on component configuration information that shows the component configuration of the product. The aforementioned risk calculation unit, Based on the demand fluctuation information, customer dependency information, and part commonality information, the system calculates the risk value of the part's remaining stock risk and outputs risk value information indicating the risk value of the part's remaining stock risk. The production planning support device according to claim 1.

3. The aforementioned demand fluctuation value information generation unit, Based on the likelihood or difficulty of demand fluctuations indicated by the fluctuation factor indicators shown in the aforementioned fluctuation factor indicator information, the actual demand fluctuation information is weighted to generate demand fluctuation value information. The production planning support device according to claim 1 or 2.

4. The aforementioned risk calculation unit, The demand fluctuation risk value for a product is calculated by multiplying the demand fluctuation value for each product-and-repeat customer combination by the customer dependency ratio for that combination. The production planning support device according to claim 1 or 2.

5. The aforementioned risk calculation unit, The demand fluctuation value of the product is calculated by multiplying the demand fluctuation value of the product's largest customer by the customer dependency of that largest customer. This value is then used as the risk value for demand fluctuations of the product. The production planning support device according to claim 1 or 2.

6. The production planning support system is executed. The steps include generating variable factor indicator information that shows variable factor indicators that are factors causing fluctuations in product demand, based on information about repeat customers of the product, and A step of generating demand fluctuation information that shows the actual fluctuations in demand for a product, based on demand information including past sales plans and actual demand for the product, Based on the aforementioned fluctuation factor indicator information and the aforementioned demand fluctuation performance information, the step of generating demand fluctuation value information that indicates how much the demand for the product will fluctuate, Based on the aforementioned demand performance information, the step of generating customer dependency information that indicates how much of the product is purchased by a particular repeat customer, The steps include: calculating a risk value for demand fluctuations based on the demand fluctuation value information and the customer dependency information, and outputting risk value information indicating the risk value for demand fluctuations; A production planning support method equipped with the following features.

7. Computers, A demand fluctuation value information generation unit generates demand fluctuation value information that indicates how much product demand will fluctuate, based on fluctuation factor indicator information that shows fluctuation factor indicators that are factors that cause fluctuations in product demand, and demand fluctuation performance information that shows actual fluctuations in product demand. A customer dependency information generation unit generates customer dependency information that indicates how much of a product is purchased by a particular repeat customer, based on demand performance information including past demand performance of the product, and A risk calculation unit calculates a risk value for demand fluctuations based on the demand fluctuation value information and the customer dependency information, and outputs risk value information indicating the risk value for demand fluctuations. A program that makes it function as such.

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