JP4845488B2 - Production planning program - Google Patents

Description

The present invention relates to a production planning program, and more particularly to a production planning program that creates a production process flow and obtains a production plan that optimizes the production process flow using linear programming (hereinafter referred to as Linear Programming ).

  Conventionally, in a process industry such as a petroleum / chemical system that generates a predetermined product from one or a plurality of types of raw materials, LP has been used for planning a production process from raw material purchase to product sales. LP is a mathematical optimization technology that can optimally determine the balance of “flow of goods” by evaluating the amount of money. In production planning using LP, a series of processes from raw material procurement to production and product sales The flow is expressed by one production process flow, and the flow of “thing” on the flow is determined so that the evaluation of “money” is the highest.

  The plan optimization system that supports production planning using LP supports the creation of production process flow using GUI (Graphical User Interface) by the user and the input of table data to set information on processing means on the flow Then, optimization calculation processing is performed from the produced production process flow and table data, and the calculation result is presented to the user.

  In creation of a production process flow, a production process is expressed by combining boxes representing points in time in the production process and connecting them with a connecting line. FIG. 15 is a diagram showing an example of a production process flow in a chemical process.

  Each box represents a processing means in the production process of the chemical process. Box A (901) is a raw material purchase, Box B (902) is a decomposition device, Box C (903) is a mixing device, and Box D (904) is an assembly device. And Box E (905) represents product sales. The connecting line represents the flow of things, and the connecting line 906 connecting the box A (901) and the box B (902) indicates the flow of the raw material 1, and the connecting line 907 output from the box B (902). , 908 and 909 indicate the flows of the intermediate products 1, 2 and 3, respectively. Then, a value is input to the table data developed for each box, and the setting by the user is completed.

  In the next optimization calculation process, the modeling system creates a relational expression between the input and output of the box, summarizes the relational expressions of all the boxes, and creates an LP model. FIG. 16 is a diagram showing a conventional LP model creation method.

  In LP model generation, the relationship of how the input to each box changes to become an output is formulated. For example, a relational expression 911 is obtained that formulates the relation between the input Xin (raw material 1) and the outputs Xout1 (intermediate product 1), Xout2 (intermediate product 2), and Xout3 (intermediate product 3) for the box B (902). Similarly, for the next box C (903), the relationship between inputs Yin1 (intermediate product 1) and Yin2 (intermediate product 2) and Yout1 (product 1), Yout2 (product 2) and Yout3 (product 3) is formulated. To do. Further, in order to express the continuity of processing, Yin1 = Xout1 and Yin2 = Xout2 indicating the relationship between the input and other box outputs are added to obtain a relational expression 912. An LP model is created by putting together the relational expressions in the respective processing means thus calculated.

Then, based on the created LP model, an optimal solution that maximizes profit is calculated, and the calculation result is presented to the user.
In actual production process planning, simulation is performed repeatedly to create and modify a model and optimize calculation, thereby optimizing the plan. However, in the simulation, there is a problem that if the model is changed even a little, the optimization calculation which requires a huge amount of time must be performed again. Therefore, the inventor of the present application can perform a simulation without changing the initial production plan model when performing a simulation in which an arbitrary value is changed with respect to the optimization calculation result to determine the influence on other values. A possible production planning system is proposed (for example, see Patent Document 1).
Japanese Patent Laid-Open No. 2000-254893 (FIG. 1)

  However, the conventional production planning using LP has a problem that it is difficult to disassemble the production process for each product from the plan data (LP model, LP optimization calculation result) generated by the optimization calculation.

  When a production plan is created, various decisions are made based on the production plan. For example, the planned cost for each product used for the determination of the sales price and the profit / loss simulation is calculated based on the amount of raw material used for each product, the amount of operating equipment for each product, the amount of utility used for each product, etc. calculated from the production process flow. The values of these various elements for each product are obtained by following the production process drawn for each product and back-calculating from the LP optimization calculation result. For example, in the production process flow shown in FIG. 15, the amount of the raw material 1 contained in the product 1 is the amount of the intermediate product 1 and the intermediate product 2 contained in the product 1 in the “mixing” of the box C (903). Next, the amount of the raw material 1 contained in the intermediate product 1 and the intermediate product 2 in the “decomposing apparatus” in box B (902) is calculated, and the sum is calculated. The same applies to the calculation of the device operation amount for each product, the utility usage amount for each product, and the like, and the process until the product is generated is calculated in reverse.

  However, in the optimization calculation using the LP model, the amount of raw material used for the entire process is calculated, but process information such as the amount of raw material used for each product and the amount of intermediate product used is not generated. Therefore, it is desirable to calculate the generation process information for each product using the LP model used for the optimization calculation. However, as shown in FIG. 16, the LP formula data is a relational expression between the input and output of the box. Since this is a set and does not represent the relationship between boxes, there is a problem that it is difficult to reversely follow the production process flow. For example, the previous box of the box C (903) represented by the relational expression 912 is the box B (902), but information about the previous box cannot be obtained from the relational expression 912. Although it is not impossible to search for a box having Yin1 = Xout1 to Xout1 in the relational expression 912 as an output, it is not realistic to perform such processing in an actual process with a huge number of boxes.

  Therefore, in the past, the reverse process of tracing the production process flow backwards and back-calculating the process information for each product from the LP optimization calculation results has been left to human labor. , While calculating backwards, desired values such as the amount of raw material used for each product were obtained. For this reason, enormous time and expense were required for calculation. Furthermore, in order to perform the reverse calculation, it is necessary to have many years of experience and expertise, such as knowledge of what processes each product has and how it is processed. There is also the problem of being limited.

  In addition, when the production process for each product is not fixed as in the process industry, the optimal production process flow is set as needed according to changes in the environment, and the relational expression between the input and output of the box also changes. The production process information for each product also changes. However, it was difficult to instantaneously calculate the production process information for each product according to the change in the environment if the reverse development of the production process flow was left manually.

  The present invention has been made in view of these points, and an object of the present invention is to provide a production plan program for optimizing a production plan that enables reverse development of a production process flow.

In order to solve the above-mentioned problems, the present invention provides a production planning program for causing a computer to execute the process shown in FIG. The production planning program according to the present invention can cause the computer to function as the LP model creation means 11, the optimization calculation means 12, and the flow reverse expansion means 13 to execute the following processing. The LP model creation means 11 uses, as an element, what is used or generated until a product is generated from a raw material in a production process, and a box representing a process step for processing the element, and connects the box and passes through the process step. The input side connection line of the box describes the process flow data describing the production process flow that represents the production process by the connection line that represents the flow of the elements, and the processing data that describes the processing performed in the processing step and the processing conditions and costs. The process flow data and the box related data are read from the storage means for storing the indicated element and the box related data associated with the element indicated by the output connection line of the box, and the process flow data is analyzed to analyze the origin of the connecting line. Identifies the box and end box, and the connecting line shows the start box and end box Conversion data associated with the element is generated and stored in the storage means, and for all boxes in the production process flow, the processing data is used to indicate the input side connection line and the output side connection line that connect the box processing to the box. Using the element amount as a decision variable, the relation and cost between the decision variable corresponding to the input connection line element and the decision variable corresponding to the output connection line element are expressed as a relational expression, and the generated relational expression group and conversion data are expressed as An LP model of the production process flow is assumed. The optimization calculation means 12 performs optimization calculation of the relational expression group using linear programming , calculates the value of the decision variable that maximizes the profit based on the relational expression, and optimizes the element indicated by the connecting line. And The flow reverse expansion means 13 searches the conversion data for each product in the production process and detects the box connected as the output side connecting line, including the element indicating the product, as a target box and corresponds to the product. The input side connection line connected to the target box is extracted as the required amount, and based on the box-related data of the box, the input side connection line used to generate the required amount in the box Calculates the usage amount, obtains the next box to pre-process the box based on the conversion data corresponding to the input side connection line, uses the element usage indicated by the input side connection line as the required amount, and sets the next box as the target box As described above, the process from the extraction of the input side connecting line connected to the target box is repeated, and the production process flow is reversely developed until the next box is the raw material purchase.

  In the optimization process of the production plan executed by the production planning program of the present invention, conversion data with the flow of elements in the production process flow as a variable can be held simultaneously with the LP model information, so refer to the conversion data. For example, the production process flow of an arbitrary product is traced in reverse, and the production process for each product is decomposed by calculating backward from the LP solution data, and the amount of a desired element in the product production process flow can be calculated. That is, there is an advantage that the production process flow can be reversely developed for each product based on the conversion data, and the production process information for each product such as the intermediate product usage amount and the raw material usage amount for each product can be automatically calculated.

  In addition, because the generation process information such as raw material usage by product can be automatically calculated based on the plan data as described above, the generation process information after the change can be immediately acquired and used for various decision making even when the plan is changed. Is possible.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. First, the concept of the invention applied to the embodiment will be described, and then the specific contents of the embodiment will be described.
FIG. 1 is a conceptual diagram of the invention applied to the embodiment.

  The production planning program according to the present invention stores a process flow data file 21, a table data file 22, an LP model file 23, a conversion data file 24, an LP solution file 25, and a flow reverse development file 26 in storage means connected to a computer. In addition, by causing the computer to function as the LP model creation means 11, the optimization calculation means 12, and the flow reverse expansion means 13, an environment for optimizing the production plan is provided to the user.

  The LP model creating means 11 reads out the process flow data describing the production process flow representing the production process step from the process flow data file 21 and table data in which box-related data is stored in a table format. The box-related data of the target production process flow is read from the file 22, and conversion data and an LP model are created. The production process flow represents a production process by a processing step in the production process and a flow of various elements (flow of things) passing through the processing step. On the display screen of the production process flow provided to the user, the processing steps are represented by boxes and the flow of elements are represented by connecting lines that connect the boxes. Therefore, the processing steps are hereinafter referred to as boxes and the flow of elements is called a connecting line. The conversion data is data used as flow variables of various elements on the production process flow, and is stored in the conversion data file 24 after being created. The LP model is a collection of formula data generated based on the LP format using conversion data and table data, and is stored in the LP model file 23 after being created.

  The optimization calculation unit 12 performs mathematical optimization calculation on the target production process flow based on the LP model created by the LP model creation unit 11 to calculate LP solution data, and stores the LP solution data in the LP solution file 25. At this time, the optimization calculation result is reflected in the corresponding portions of the process flow data file 21 and the table data file 22 as necessary.

  The flow reverse development means 13 indicates which conversion data file 24 relates to which apparatus the product passes through and how much intermediate product is used, and what raw material is used by the intermediate product. The calculation is performed with reference to the LP solution data of the target product in the LP solution file 25 and the related processing data in the table data file 22. That is, based on the conversion data, the production process flow is traced in reverse order from the product to the raw material, and a production process flow for each product is created. At the same time, based on the LP solution data and the table data, various generation process amounts are calculated for each product by inversely calculating the necessary amount (material balance) in the connection line of the generation process flow for each product. For example, intermediate product usage, raw material usage, inventory usage, device usage, utility usage, and the like can be calculated. The calculation result is stored in the flow reverse expansion file 26. Hereinafter, the process of reversely developing the production process flow and calculating the various usage amounts for each product by back-calculating from the LP solution data is referred to as material balance (hereinafter referred to as “matevala”) development.

Next, files stored in the storage means will be described.
The process flow data file 21 is data describing a production process flow that expresses a production process by a box indicating processing means in the production process and a connection line connecting the boxes and indicating the flow of various elements between the boxes. And connecting line information. As box information, it has information on a unique name in the production process flow defined for each box and its attribute (selected from prepared processing attributes). Further, as connection line information, there is information relating to the name of the element represented by the connection line, the connection source box name, and the connection destination box name. The flow of “element name” from “connection source box name” to “connection destination box name” is defined by the connection line information.

  The table data file 22 stores box-related data including processing data related to processing executed in the box in a table format. The table manages data set by, for example, sheet information related to the table and cell information related to the items of the table based on the specifications of general table processing software. A separate sheet is prepared for each box, and a matrix is formed in which box input lines (input side connecting lines) to be input to the boxes are arranged in columns and box output lines (output side connecting lines) are arranged in rows. In the table data file 22, the sheet information and cell information are set. In addition, data set in the table (for example, yield, purchase cost, sales price, etc. in the disassembling apparatus) can be mapped by setting sheet information and cell information.

  The LP model file 23 stores data related to the LP model created based on the conversion data file 24 and the table data file 22. The LP model is created as formula data based on the LP format.

  The conversion data file 24 stores conversion data indicating connecting lines connecting boxes. The conversion data is created as a variable including “connection source box name− (element) name−connection destination box name” for each connecting line.

The LP solution file 25 stores the optimization calculation result (LP solution data) obtained by the optimization calculation based on the LP model.
The flow reverse expansion file 26 stores a generation process flow for each product generated by reverse expansion from the conversion data, and data related to material ribs in a connection line in the process calculated from the optimization result data. Hereinafter, the flow reverse expansion file is also referred to as a materialized expansion file.

  The production plan optimizing process and the materialized process will be described. FIG. 2 is a diagram showing a data flow in the production plan optimization process. In the figure, the solid line shows the data flow in the optimization calculation process, and the broken line shows the data flow in the materialization processing.

  The process flow data file 21 and the table data file 22 include process flow data (configuration data) 21a for describing a production process flow created in advance by a user, and table data 22a created for each box on the production process flow. Is stored. In the process flow data 21a, the name (represented as NAME (B)) and attributes are set for all boxes, which box is the connection source (represented as FROM), and which box is the connection destination for all connection lines. (Named as TO) and name (named as NAME (L)). On the other hand, cell information, sheet information, and processing information are set in the table data 22a for a box that requires input information. The format of the data sheet is determined according to the attribute of the box. For example, raw material purchase, product sales, disassembling apparatus, assembling apparatus, mixing, etc. have their own specific data sheets. Some box attributes do not have a data sheet itself. For example, a branch or the like does not have setting data and therefore has no data sheet.

  The LP model creation means 11 creates conversion data 24a and LP model data 23a from the process flow data 21a and table data 22a. The conversion data 24a represents the flow of what is a decision variable in the form of FROM_NAME (L) _TO. The LP model data 23a is generated as formula data in the LP format from the processing data of the conversion data 24a and the table data 22a. A specific example will be described. FIG. 3 is a diagram showing creation of an LP model. The production process flow is the same as in FIG.

  As conversion data regarding the box B (31), conversion data A_X_B (32a) of FROM (= box A), TO (= box C), TO (= box C), and NAME (L) (= X) representing input connection lines is converted from the process flow data. In the same manner, B_Y1_C (32b), B_Y2_C (32c), and B_Y3_D (32d) representing the output connection line are set. Further, C_Z1_E (35a), C_Z2_E (35b), and C_Z3_E (35c) representing the output connection line are set as the conversion data related to the box C (34). The input side is the same as the output side of box B (31).

  In creating the LP model, the conversion data 32a, 32b, 32c, 32d and the processing data (Y1: Y2: Y3 = 3A: 5A: 2A) of the decomposer are formulated for the box B (31), and the LP model data (B_Y1_C = 0.3A_X_B, B_Y2_C = 0.5A_X_B, B_Y3_D = 0.2A_X_B) 33. Similarly, LP model data (C_Z1_E = 0.4B_Y1_C + 0.2B_Y2_C, C_Z2_E = 0.2B_Y1_C + 0.3B_Y2_C, C_Z3_E = 0.2B_Y1_C + 0.5B_Y2_C) is created for the box C (34).

  Compared with the LP model data of FIG. 16, the LP model data created in this way includes “flow of things” in the equation data, and it can be seen that the process can be reversed.

Returning to FIG.
The optimization calculation means 12 performs optimization calculation based on the LP model data created by the LP model creation means 11 to calculate LP solution data 25a. The LP solution data has an objective function value and a value of each decision variable. By presenting the optimization calculation result in the production process flow and the table data, the optimal solution is notified to the user.

  The flow reverse expansion means 13 performs materialized expansion processing for all products. In the materialize expansion process, the process flow data 21a is reversely expanded from the product based on the conversion data 24a, and a generation process flow for each product is created. Then, based on the LP solution data 25a, the table data 22a is referred to, and the amount of a predetermined element of the connecting line in the generation process flow for each product is calculated. For example, in the example of FIG. 3, the case where the amount of raw material used of the raw material X contained in the product Z1 is obtained will be described. Based on the conversion data (C_Z1_E, B_Y1_C, B_Y2_C, A_X_B), for the product Z1, a generation process flow of raw material, box B (31), box C (34), and product is obtained. Based on this generation process flow, if the back calculation is performed using the LP solution data, the raw material usage amount of the raw material X related to the product Z1 can be calculated. With the same procedure, it is possible to calculate production process information, intermediate product usage, inventory usage, device usage, and utility usage for each final product.

  In this way, when creating an LP model, by having conversion data with the flow of things as a variable at the same time as the LP model information, the process from product to raw material for each product is reversed based on the conversion data, and the generation process for each product A flow can be created. Further, it is possible to calculate production process information for each product such as an intermediate product usage amount and a raw material usage amount by performing reverse calculation from LP solution data obtained by optimization calculation based on the production process flow for each product.

  Using the product-specific generation process information calculated in this way, for example, the planned cost for each product can be automatically calculated, and the product planned cost can be easily calculated even when there is no specialized knowledge. It will be possible to ask. Furthermore, since it can be performed automatically, it is possible to easily cope with environmental changes and accurately grasp the planned cost for each product.

  Hereinafter, an embodiment will be described in detail with reference to the drawings, taking as an example a case where the embodiment is applied to a plan optimization system that optimizes a production plan of a process industry. FIG. 4 is a diagram illustrating a configuration example of the plan optimization system according to the embodiment.

  The plan optimization system according to the embodiment creates a production process flow, performs optimization calculation using LP, and performs a mathematical calculation for performing optimization calculation processing in the plan optimization apparatus 100 that supports optimization of the production plan. The plan solver 150, the monitor 108 that presents the calculation result to the user 200, and the input device 109 that receives inputs such as data settings and instructions by the user 200 are connected via an internal bus or a network. It is also possible to connect to a profit / loss simulator or a terminal device of a person in charge of each department via a network.

The plan optimization apparatus 100 includes a GUI processing unit 110, a plan optimization calculation processing unit 120, a storage device 130, and a materialize expansion processing unit 140.
The GUI processing unit 110 controls the monitor 108 and the input device 109 using a GUI function. The user 200 creates and sets a production process flow and table data according to the GUI displayed on the monitor 108 under the control of the GUI processing unit 110. The setting data is input to the GUI processing unit 110 via the input device 109, and the GUI processing unit 110 reflects the setting data on the display screen, creates process flow data and table data, and stores them in the storage device 130.

  The plan optimization calculation processing unit 120 creates conversion data and LP model data related to the production process flow based on the production process flow and table data set via the GUI processing unit 110, performs optimization calculation, and performs LP optimization. Calculate the solution. The optimization calculation is requested to the mathematical programming solver 150, and the optimization calculation result is notified to the user 200 via the GUI processing unit 110.

  The storage device 130 is a storage means that can be accessed from the GUI processing unit 110, the plan optimization calculation processing unit 120, and the materialize development processing unit 140, and includes a process flow data file, a table data file, an LP model file, a conversion data file, an LP A solution file, a materialized file, etc. are stored.

  The materialize expansion processing unit 140 performs materialized material expansion by product based on the conversion data, table data, and LP solution data, and generates material material expansion data such as raw material usage, inventory usage, equipment usage, utility usage, etc. To do. The materialized expansion data is notified to the user 200 via the GUI processing unit 110. The calculated materialized development data can be used, for example, for product plan cost calculation.

The mathematical programming solver 150 performs optimization calculation based on the LP model data.
Here, the hardware configuration of the plan optimization apparatus 100 will be described. FIG. 5 is a block diagram illustrating a hardware configuration example of the plan optimization apparatus according to the present embodiment.

  The plan optimization apparatus 100 is controlled by a CPU (Central Processing Unit) 101 as a whole. A random access memory (RAM) 102, a hard disk drive (HDD) 103, a graphic processing device 104, an input interface 105, and a communication interface 106 are connected to the CPU 101 via a bus 107.

  The RAM 102 temporarily stores at least part of an OS (Operating System) program and application programs to be executed by the CPU 101. The RAM 102 stores various data necessary for processing by the CPU 101. The HDD 103 stores the OS and application programs. A monitor 108 is connected to the graphic processing device 104, and an image is displayed on the screen of the monitor 108 in accordance with a command from the CPU 101. A keyboard 109 a and a mouse 109 b are connected to the input interface 105, and signals transmitted from the keyboard 109 a and the mouse 109 b are transmitted to the CPU 101 via the bus 107. The communication interface 106 is connected to a network and transmits / receives data to / from a terminal device via the network.

With such a hardware configuration, the processing functions of the present embodiment can be realized.
Next, the processes of the plan optimization calculation processing unit 120 and the materialize expansion processing unit 140 will be described in detail.

(1) Plan Optimization Calculation Processing First, the processing of the plan optimization calculation processing unit 120 will be described. FIG. 6 is a flowchart showing the LP calculation processing procedure of the present embodiment. In the figure, the production process flow by the GUI processing unit 110 and the procedure from the table data creation process are shown.

  [Step S11] In response to the start instruction, the initial setting program is activated to prepare the data input environment. On the monitor 108, a production process flow creation screen is displayed, and the user 200 waits for input of setting information of the user 200.

  [Step S12] When the setting information of the production process flow box and the connecting line (hereinafter referred to as a line) is input by the user 200, the production process flow based on the setting information is displayed on the monitor 108 based on the setting information. Create flow data. The process flow data is stored in the process flow data file 131.

  [Step S13] When a box is designated by the user 200, a data sheet is created according to the attribute of the box. The format of the data sheet is determined for each attribute of the box (raw material purchase, product sales, disassembly device, assembly device, mixing), which is displayed on the monitor 108 and waits for setting information of the user 200. An address using the box name NAME (B), the input line FROM_NAME (L), and the output line NAME (L) _TO is added to the table cell.

  [Step S14] When data is set in the table of each data sheet by the user 200, this is displayed on the monitor 108, table data is created, and set in the table data file 132.

  By executing the above processing procedure, the process flow data file 131 and the table data file 132 are set. Subsequently, optimization calculation using these is started.

  [Step S15] Based on the process flow data created in step S12, FROM_NAME (L) _TO information that is the source of conversion data is created for all boxes, and the corresponding processing in the data sheet of the corresponding box Data (numerical value) is taken out and information that is the basis of the LP formula is created.

  [Step S16] Using the information based on the LP expression created in step S15, an internal variable for LP expression corresponding to FROM_NAME (L) _TO is generated, converted data is generated, and the converted data file 133 is stored. In addition to setting, LP type data by internal variables is created and set in the LP model file 134.

[Step S17] The mathematical programming solver 150 is called to perform optimization calculation. An LP solution file 135 is set as an optimization calculation result.
[Step S18] Using the converted data file 133 set in Step S16 and the LP solution file 135 created in Step S17, the optimum calculation result is displayed on the production process flow displayed on the monitor 108 in Step S12. Let At the same time, the optimization calculation result is displayed in the data sheet of the corresponding box.

By executing the above processing procedure, LP optimization calculation is performed and the result is provided to the user.
Here, the plan optimization calculation process will be described with a specific example. FIG. 7 is a diagram showing a production process flow of a production process in which two kinds of raw materials are mixed.

  The production process flow of this production process shows the process of producing two types of regular products and café au lait by mixing two types of raw materials (coffee and milk). Raw material purchase (coffee extract) 41, raw material purchase ( Milk) 42, mixing device 45, product (regular) 47 and box of product (cafe au lait) 49, coffee 43 connecting raw material purchase (coffee extract) 41 and mixing device 45, raw material purchase (milk) 42 and mixing device It is expressed by the lines of milk 44 that connects 45, regular 46 that connects the mixing device 45 and the product (regular) 47, and cafe au lait 48 that connects the mixing device 45 and the product (cafe au lait) 49.

When such a production process flow is created, a table sheet corresponding to the box attribute is automatically created from the box information and line information of the production process flow.
FIG. 8 is a view showing a table sheet of a box in which two kinds of raw materials are mixed. The figure shows an example of a table sheet of the mixing device 45.

  A table 50 for the mixing device is automatically created from the box attribute (assembly device) of the production process flow, the regular 51a and cafe au lait 51b are set on the output side in the table row from the line information, and the input side is set in the table column. Coffee 52 and milk 53 are automatically set. From this state, the user is processing data, for example, the balance information 54 of mixing, the regular is a ratio of coffee and milk 0.9 and 0.1, the cafe au lait is a ratio of coffee and milk 0.6 and 0.4 Set to be mixed in. If necessary, a lower limit 55, an upper limit 56, and the like are also set. Here, 150 is set as the lower limit 55 of café au lait, and it is set that at least 150 must be produced. In addition, as the utility 57, the costs of 4 yen and 6 yen for the coffee extract and the milk, which are the raw materials, are set, and it is set that the milk can be purchased only 100 at the maximum as the purchase upper limit 58. Furthermore, in the example of the figure, the table is created so that the LP optimum solution (coffee solution, milk solution) can also be set in the table.

When the setting is completed and the LP calculation process is started, FROM_NAME (L) _TO information is created for all boxes, and the corresponding process data in the corresponding box table is combined with the LP data. Create the information that is the basis of the expression. For example, if raw material purchase 41,
NAME: Coffee extract Attribute: Raw material purchase Output: Coffee extract_Coffee_Mixing device Cost: 4
Such information is created.

Similarly, if the mixing device 45,
NAME: Mixing device Attribute: Assembly device Output: Mixing device_Regular_Regular_Product (Regular),
Mixing device_cafe au lait_product (cafe au lait)
Input 1: Coffee extract_Coffee_Mixing device_1, 0.9, 0.6
Input 2: Milk_milk_mixing device 0.1, 0.4
Input limit: None, 100
Input lower limit: None, None Output upper limit: None, None Output lower limit: None, 150
Is created.

Subsequently, based on the extracted information, an internal variable for the LP equation is generated to create a variable data file and an LP equation file.
In this example, internal variables X1, X2, X3, and X4 are respectively associated with line (regular) 48, line (cafe au lait) 46, line (coffee) 43, and line (milk) 44 as conversion data.
X1, Mixing device_Regular_Regular X2, Mixing device_Cafe au lait_Product (Cafe au lait)
X3, raw material purchase (coffee extract) _coffee_mixing device X4, raw material purchase (milk) _milk_mixing device (1)
And create.

The LP model uses these internal variables and the processing data of the table data 51,
Maximize
100X1 + 120X2-6X4-4X3
Subject To
s1: 0.9X1 + 0.6X2-X3 = 0
s2: 0.1X1 + 0.4X2-X4 = 0
Bounds
150 <= X2
X4 <= 100
End (2)
And created.

  An optimization calculation is performed based on such an LP model, and LP solution data is set. In this case, X1 = 400.00, X2 = 150.00, X3 = 450.00, and X4 = 100.00 are calculated as LP solution data.

  The calculated LP solution data is displayed superimposed on the production process flow line shown in FIG. FIG. 9 is a diagram showing a display example in which an optimization calculation result is added to a production process flow of a production process in which two kinds of raw materials are mixed.

  The LP solution data obtained from the optimization calculation result is displayed on the corresponding line. In the example of the figure, LP solution of regular 46 (X1 = 400.00), LP solution of cafe au lait 48 (X2 = 150.00), LP solution of coffee 43 (X3 = 450.00) and LP solution of milk 44 (X4 = 100.00) is displayed.

(2) Matebara Development Processing Next, the processing of the materialization processing unit 140 will be described. FIG. 10 is a flowchart showing the materialization processing procedure of the present embodiment.

Processing is started in response to the materialization deployment instruction.
[Step S21] An element input to the product box of the target production process flow, that is, FROM_NAME (L) _TO in the converted data file is searched, and an input element having the name of the product sales box in TO is searched. Then, the following processing is sequentially performed on all input elements.

  [Step S22] One of the input elements retrieved in step S21 is set as an allocation element for reverse development of the production process flow, and the allocation value is set from the LP solution data.

  [Step S23] The conversion data corresponding to the allocation element (conversion data in which the allocation element is NAME (L) and the current box is set in TO) is read from the conversion data file 133, and FROM is converted from the conversion data FROM_NAME (L) _TO. Gets the name of the next box set to. The box set in the FROM is a box indicating the previous process of the production process flow, and becomes the next box at the time of reverse development.

[Step S24] Based on the name of the next box acquired in step S23, the process flow data is searched and its attribute information is acquired.
[Step S25] The process is branched according to the attribute of the box. If the box attribute is an attribute having a data sheet, such as a disassembling device, an assembling device, or a mixing device, the process proceeds to step S26. If the box attribute is an attribute that does not have a data sheet, such as a branch, the process proceeds to step S27. If the box attribute is raw material purchase, the process proceeds to step S28.

  [Step S26] When the box attribute has a data sheet (with a data sheet), a materialized processing is performed to calculate materialized expansion data related to the box and set it in the materialized expansion file. Then, the process returns to step S23, and the processing from the procedure for searching for the next box at the time of reverse expansion related to the allocation element is performed.

  [Step S27] When the attribute of the box does not have a data sheet (no data sheet), a materialized calculation process is performed to calculate materialized expansion data related to the box and set it in the materialized expansion file. Then, the process returns to step S23, and the processing from the procedure for searching for the next box at the time of reverse expansion related to the allocation element is performed.

  [Step S28] If the attribute of the box is purchase of raw materials, this box is the final box in the reverse development, so it is determined that the materialization expansion for this allocation element has ended. Then, it is determined whether there is another product box input element. If there is, the process returns to step S22, and materialization of the allocation element that has not yet been materialized is performed. If not, the materialized deployment is terminated.

  By executing the above processing procedure, the processing from step S23 to step S27 is repeated for each input element of the product box (by product) until the next box reaches “raw material purchase”. This reverses the production process flow. At the same time, the materialized calculation is performed for each box by the materialized material calculation processing in step S26 and step S27, and the necessary amount of intermediate products constituting the product is calculated.

Here, the materialized calculation in step S26 and step S27 will be described.
FIG. 11 is a flowchart showing a processing procedure of the materialized arithmetic processing with a data sheet according to the present embodiment.

  [Step S261] Based on the name of the box specified in the preprocessing (the next box in the reverse expansion related to the allocation element), all input elements input to the box are searched. That is, the conversion data file is searched, and an input element in which the box name designated by TO is set is searched in FROM_NAME (L) _TO. Then, the following processing is sequentially performed on all input elements.

  [Step S262] One of the input elements searched in Step S261 is set as an allocated element to be allocated by the allocation element, and the allocation basic value is set from the LP solution data.

[Step S263] The processing data for the element is acquired from the data sheet of the box.
[Step S264] A materialization calculation process for the allocated element is performed. That is, the provision value of the provisioned element is calculated using the provision value of the provision element, the provision basic value set in step S262 and the processing data read in step S263. The calculation result is set in the materialized development data.

  [Step S265] The allocated element set in step S262 is set as the allocated element in the next reverse expansion, and the allocated value of the allocated element calculated in step S264 is set as the allocated value of the allocated element.

  [Step S266] It is checked whether there is another box input element. If there is, the process returns to step S262, and the material box calculation process of the next box input element that has not been processed is performed. If not, the materialized operation for this box is terminated.

FIG. 12 is a flowchart showing the processing procedure of the materialized calculation process without a data sheet according to the present embodiment.
[Step S271] Based on the name of the box specified in the preprocessing, all input elements input to the box are searched. That is, the conversion data file is searched, and an input element in which the box name designated by TO is set is searched in FROM_NAME (L) _TO. Then, the following processing is sequentially performed on all input elements.

  [Step S272] One of the input elements searched in step S271 is set as an allocated element to be allocated by the allocation element, and the allocation basic value is set from the LP solution data.

  [Step S273] A materialized calculation process related to the allocated element is performed. That is, the provision value of the provisioned element is calculated using the provision value of the provision element and the provision basic value set in step S272. The calculation result is set in the materialized development data.

  [Step S274] The allocation element set in step S272 is set as the allocation element in the next reverse expansion, and the allocation value of the allocation element calculated in step S273 is set as the allocation value of the allocation element.

  [Step S275] Check whether there is another box input element. If there is, the process returns to step S272 and the material box calculation process of the next box input element is performed. If not, the materialized operation for this box is terminated.

By executing the above processing procedure, the materialized calculation is performed on the box searched by the materialized expansion, and the amount of allocated elements constituting the product is calculated.
Furthermore, the necessary amount of the intermediate product raw material that constitutes the intermediate product can be obtained from the necessary amount of the intermediate product that is generated during the process from the raw material to the product by the materialized development.

Here, the plan optimization calculation process will be described with a specific example.
In the optimization calculation result display of the production process flow for mixing two kinds of raw materials (coffee and milk) shown in FIG. 9, the total usage amount of each raw material and the amount of products to be generated are displayed. However, the amount of raw material used for each product is not calculated. Therefore, if the material flow is developed to create a production process flow for each product and back-calculate from the LP solution data, the raw material usage amounts for regular and cafe au lait can be calculated.

  For example, when the product (cafe au lait) 49 is expanded, the mixing device 45 is searched for the previous block. Since the required amount of café au lait (48) output from the mixing device 45 is 150.00, the total usage amount 150.00 of the coffee 43 and milk 44 input to the mixing device 45 is calculated. Since the mixing ratio of the café au lait of the mixing device 45 is 0.4 for milk with respect to 0.6 for coffee with reference to the table 50, the raw material usage is calculated to be 90.00 for coffee and 60.00 for milk. Is done. The same calculation can be made for regular.

Since this example is simple, it can be easily calculated from the table 50 of the mixing device 45, but it is difficult to calculate when the model becomes large.
Hereinafter, an example of a production process flow close to an actual application example will be described.

FIG. 13 is a diagram illustrating an example of a production process flow for petroleum refining. Only the blocks and lines related to the explanation will be numbered and explained.
Crude oil 201 as a raw material block, product 207 as a product block, TOP202 and PLAT 206 as device blocks, and TOPNB 203, TOPSW 204, and TOPLPG 205 as branch blocks are connected by lines. In addition, the numerical value before the name of the line of a figure is LP solution data.

  In the converted data of each line, the line 210 becomes “X1 = crude oil_CR1_TOP, crude oil_CR2_TOP, crude oil_CR3_TOP”. Similarly, the line 211 is “X2 = TOP_SW_TOPSW”, the line 212 is “X3 = TOP_TNAP_TOPNB”, the line 213 is “X4 = TOPSW_SN_TOPNB”, the line 214 is “X5 = TOPNB_PNAP_PLAT”, the line 215 is “X6 = TOP_TLPG_TOPLPG”, the line 2 Is “X7 = PLAT_PLPG_TOPLPG”, line 217 is “X8 = TOPLPG_LPG_product”, line 218 is “X9 = TOPNB_NAP_product”, line 219 is “X10 = MIXG_GASO_product”, line 220 is “X11 = UNIF_KERO_product”, and line 221 is “X12 = BLF_FUEL_product” is written.

Regarding this production process flow, the case where the amount of raw material used is calculated for each product will be described.
First, the input element of the product 207 is searched. When the conversion data TO searches for the conversion data of the product, “X1 = TOPLPG_LPG_product”, “X2 = TOPNB_NAP_product”, “X3 = MIXG_GASO_product”, “X4 = UNIF_KERO_product”, “X5 = BLF_FUEL_product” are searched. The That is, there are products LPG, NAP, GASO, KERO, and FUEL as input elements.

In the following, description will be made assuming that materialized development relating to the product LPG is performed.
When an input element (X1 = TOPLPG_LPG = product) is an allocation element for reverse development of the production process flow, and the allocation value is set from the LP solution data (X1 = 34.61), the allocation element and its value are
TOPLPG_LPG_product = 34.61 (3)
It becomes.

  Next, the name “TOP_LPG” of the next box (FROM of conversion data) in the reverse expansion is acquired from the allocation element, and attribute information (branch) is acquired from the process flow data. Since the attribute is a branch, the box “TOPLPG” does not have a data sheet.

  Subsequently, the input element of the box “TOPLPG” 205 is searched. When conversion data to be set in TO is searched, “X6 = TOP_TLPG_TOPLPG” and “X7 = PLAT_PLPG_TOPLPG” are extracted. The extracted “TOP_TLPG_TOPLPG” and “PLAT_PLPG_TOPLPG” are the allocated elements, and the LP solution data is the allocated basic value. Here, TOP_TLPG_TOPLPG = 23.84 is obtained as the provisioned basic value for the provisioned element “TOP_TLPG_TOPLPG”. In TOPLPG, the provisioned value is the same as the provisioned basic value, so the provisioned value is TOP_TLPG_TOPLPG = 23.84.

Thereafter, the next block is searched using TOP_TLPG_TOPLPG as an allocation element and 23.84 as an allocation value, and the same processing is performed.
By repeating the above processing, it is possible to obtain a necessary amount of intermediate product generated until the final product LPG is generated and a generation process flow from the raw material through the intermediate product to the product LPG. In addition, by highlighting the production process flow line on the production process flow, the process until a predetermined product is produced can be easily understood. Further, at this time, detailed generation process information can be provided to the user by displaying the necessary amount of the intermediate product.

  As described above, when the intermediate product is traced and developed based on the conversion data, the material LPG configuration diagram of the product LPG can be created. The required amount of raw material in the intermediate product can be further calculated using the materialized block diagram.

FIG. 14 is a diagram illustrating an example of a materialized configuration diagram of the present embodiment. In the figure, numerical values in parentheses indicate LP calculation results, and <> indicates table data (yield) at the time of LP calculation.
By tracing the conversion data in reverse, the intermediate product generated in the product LPG generation process is reversely developed.

  Taking a TOP device as an example, TLPG is made from raw materials C1, C2, and C3 via the TOP device. The yield of TLPG in the TOP device is 0.03, 0.02, 0 (C1, C2, C3), and the input amount to the TOP device is 583.7, 316.3, 100 (C1, C2, C3).

Here, since the TLPG generated by the TOP device is all the product LPG, the usage amounts CR1 ′, CR2 ′, CR3 ′ of CR1, CR2, and CR3 used to generate TLPG23.84 are:
CR1 ′ = 583.7 * 0.03 = 17.51
CR2 ′ = 316.3 * 0.02 = 6.33
CR3 ′ = 100 * 0 = 0
become.

  On the other hand, the yield of TNAP in the TOP device is 0.19, 0.25, 0.13 (C1, C2, C3), and the input amount to the TOP device is 583.7, 316.3, 100 ( C1, C2, C3).

Here, since the TNAP generated by the TOP device partially becomes a product LPG, the usage amounts CR1 ′, CR2 ′, CR3 ′ of CR1, CR2, CR3 used to generate TNAP 10.42 are:
CR1 ′ = (583.7 * 0.19) * 10.42 / (583.7 * 0.19 + 316 * 0.25 + 100 * 0.13) = 5.89
CR2 ′ = (316.3 * 0.25) * 10.42 / (583.7 * 0.19 + 316 * 0.25 + 100 * 0.13) = 4.05
CR3 ′ = (100 * 0.13) * 10.42 / (583.7 * 0.19 + 316 * 0.25 + 100 * 0.13) = 5.89
become.

  In this way, in the materialization calculation, the required amount of the intermediate product constituting the product is obtained from the production amount of the product that is the LP calculation result using the configuration diagram and the yield data of the device via each, and the intermediate value obtained there This is done by repeating recursive calculations, such as determining the required amount of intermediate products and raw materials that make up the intermediate product from the required amount of product.

In the above description, the application example to the process industry is shown, but the application of the present invention is not limited to the process industry. For example, the present invention can be applied to optimization of a production system production plan.
The above processing functions can be realized by a computer. In that case, a program describing the processing contents of the functions that the plan optimization apparatus should have is provided. By executing the program on a computer, the above processing functions are realized on the computer. The program describing the processing contents can be recorded on a computer-readable recording medium. Examples of the computer-readable recording medium include a magnetic recording device, an optical disk, a magneto-optical recording medium, and a semiconductor memory. Examples of the magnetic recording device include a hard disk device (HDD), a flexible disk (FD), and a magnetic tape. Examples of the optical disc include a DVD (Digital Versatile Disc), a DVD-RAM (Random Access Memory), a CD-ROM (Compact Disc Read Only Memory), and a CD-R (Recordable) / RW (ReWritable). Magneto-optical recording media include MO (Magneto-Optical disk).

  When distributing the program, for example, portable recording media such as a DVD and a CD-ROM in which the program is recorded are sold. It is also possible to store the program in a storage device of a server computer and transfer the program from the server computer to another computer via a network.

  The computer that executes the program stores, for example, the program recorded on the portable recording medium or the program transferred from the server computer in its own storage device. Then, the computer reads the program from its own storage device and executes processing according to the program. The computer can also read the program directly from the portable recording medium and execute processing according to the program. Further, each time the program is transferred from the server computer, the computer can sequentially execute processing according to the received program.

(Supplementary Note 1) In a production planning program that creates a production process flow and obtains a production plan that optimizes the production process flow using linear programming,
Computer
Process flow data describing a production process flow representing the production process by processing steps for processing various elements in the production process, and flows of the various elements passing through the processing steps, and processing performed in the processing steps LP model creating means for creating an LP model of the production process flow together with conversion data using the flow of the element on the production process flow as a variable using related processing data;
Optimization calculation means for calculating LP solution data by performing optimization calculation based on the LP model;
The flow of a predetermined element in the production process flow is reversely developed from a product based on the conversion data to create a production process flow for each product, and the amount of the predetermined element is calculated by back calculating from the LP solution data Flow reverse expansion means,
Production planning program characterized by functioning as

(Supplementary Note 2) In the LP model creating means,
As the conversion data, based on the process flow data, all the element flows become the processing step identification information, the element flow identification information, and the element flow end point. Generated by converting to a variable with processing process identification information,
The production planning program according to appendix 1, wherein the process is executed.

(Supplementary Note 3) In the LP model creating means,
Generate formula data based on LP format using the conversion data and the processing data, and create an LP model including the flow of the elements as variables.
The production planning program according to appendix 1, wherein the process is executed.

(Supplementary Note 4) In the flow reverse expansion means,
The processing process indicating the final product is the processing process to be searched,
Search the conversion data for setting the processing step to be searched on the end point side,
Identify the next processing step in the reverse expansion from the converted data searched,
Repeat the processing from the search of the conversion data as the processing step to be searched for the specified next processing step until the next processing step is not searched,
The production planning program according to appendix 1, wherein the process is executed.

(Supplementary Note 5) In the flow reverse expansion means,
When reversely developing the production process flow from the product, for each processing step, by sequentially calculating back the amount of input elements of the processing step necessary to generate the required amount of output elements of the processing step Calculating the required amount of input elements of the processing steps necessary to configure the product;
The production planning program according to appendix 1, wherein the process is executed.

(Supplementary Note 6) In the flow reverse expansion means,
Based on the production process flow for each product, to calculate the amount of raw materials included in the required amount of input elements of the processing step calculated for each processing step,
The production planning program according to appendix 1, wherein the process is executed.

(Supplementary note 7)
GUI processing means for creating a display screen of the production process flow using the processing step as a block and the element flow as a connecting line connecting the blocks;
The production planning program according to appendix 1, wherein

(Supplementary Note 8) In the GUI processing means,
On the production process flow display screen corresponding to the flow of the elements included in the generation process flow for each product based on the generation process flow for each product related to the arbitrary product created by the flow reverse development means Highlight connecting lines,
The production planning program according to appendix 7, wherein the process is executed.

(Supplementary Note 9) In the GUI processing means,
The necessary amount of the input element for each processing step of the production process flow for each product, which is calculated backward from the LP solution data by the flow reverse development means, is displayed on the display screen of the production process flow.
The production planning program according to appendix 8, wherein the process is executed.

(Supplementary Note 10) In a production planning method for creating a production process flow and obtaining a production plan that optimizes the production process flow using linear programming,
LP model creation means, process flow data describing a production process flow representing the production process by a processing step of processing various elements in the production process, and a flow of the various elements passing through the processing step, and the processing Using the processing data related to the processing performed in the process, and creating the LP model of the production process flow together with the conversion data having the flow of the element on the production process flow as a variable,
The optimization calculation means calculates the LP solution data by performing optimization calculation based on the LP model,
A flow reverse expansion means reversely expands a flow of a predetermined element in the production process flow from a product based on the conversion data to create a production process flow for each product, and reversely calculates from the LP solution data to perform the predetermined flow Calculate the amount of elements of
A production planning method comprising a procedure.

(Supplementary Note 11) In a production planning apparatus that creates a production process flow and obtains a production plan that optimizes the production process flow using linear programming,
Process flow data describing a production process flow representing the production process by processing steps for processing various elements in the production process, and flows of the various elements passing through the processing steps, and processing performed in the processing steps LP model creation means for creating an LP model of the production process flow together with conversion data using the flow of the element on the production process flow as a variable using related processing data;
Optimization calculation means for performing optimization calculation based on the LP model to calculate LP solution data;
The flow of a predetermined element in the production process flow is reversely developed from a product based on the conversion data to create a production process flow for each product, and the amount of the predetermined element is calculated by back calculating from the LP solution data Material balance development means to
A production planning apparatus characterized by comprising:

It is a conceptual diagram of the invention applied to embodiment. It is the figure which showed the flow of the data in the optimization process of a production plan. It is the figure which showed creation of LP model. It is a figure showing an example of composition of a plan optimization system of an embodiment. It is a block diagram which shows the hardware structural example of the plan optimization apparatus of this Embodiment. It is the flowchart which showed the LP calculation processing procedure of this Embodiment. It is the figure which showed the production process flow of the production process which mixes two types of raw materials. It is the figure which showed the table sheet | seat of the box which mixes two types of raw materials. It is the figure which showed the example of a display which added the optimization calculation result to the production process flow of the production process which mixes two types of raw materials. It is the flowchart which showed the materialize expansion | deployment processing procedure of this Embodiment. It is the flowchart which showed the process sequence of the materialized calculation process with a data sheet of this Embodiment. It is the flowchart which showed the process sequence of the materialize calculation process without the data sheet of this Embodiment. It is the figure which showed an example of the production process flow of oil refining. It is the figure which showed an example of the materialized block diagram of this Embodiment. It is the figure which showed an example of the production process flow in a chemical process. It is the figure which showed the conventional LP model creation method.

Explanation of symbols

11 LP model creation means 12 Optimization calculation means 13 Flow reverse expansion means 21 Process flow data file 22 Table data file 23 LP model file 24 Conversion data file 25 LP solution file 26 Flow reverse expansion file

Claims (5)

Create a production process flow, linear programming; in the production planning program to determine the production plan with (LP Linear Programming),
Computer
As elements that used or generated until the product is produced from Oite raw materials in the production process, and a box representing the process step of treating said element, prior to passing through the processing steps to connect the box Symbol and process flow data describing a manufacturing process flow showing the manufacturing process by the connection lines representing the flow of elements, the input of the processing data describing conditions and cost of processing and processing performed in the processing step the box The process flow data and the box related data are read out from storage means for storing the element indicated by the side connection line and the box related data associated with the element indicated by the output side connection line of the box , and the process flow data is read out. Analyzing to identify a starting box and an ending box of the connecting line; And it generates a conversion data that associates box serial endpoint element indicated by the connection line stored in the storage means, for all the boxes of the production process flow, the box processing of the box by using the process data The amount of elements indicated by the input-side connection line and the output-side connection line connected to the input-side connection line is used as a decision variable, and a decision variable corresponding to an element of the input-side connection line and a decision variable corresponding to an element of the output-side connection line LP model creating means that expresses relations and costs as relational expressions, and uses the generated relational expression group and the converted data as an LP model of the production process flow,
An optimization calculation of the relational expression group is performed using the linear programming method, and a value of the decision variable that maximizes the profit based on the relational expression is calculated to obtain an optimal solution of an element indicated by the connection line Optimization calculation means,
For each product of the production process, the connection line including the element indicating the product by searching the conversion data is detected as a box connected as the output side connection line, and is an optimum corresponding to the product. The input-side connection line used to generate the required amount in the box based on the box-related data of the box, extracting the input-side connection line connected to the target box as a required amount And calculating the amount of use of the element indicated by the second box, obtaining the next box for preprocessing the box based on the conversion data corresponding to the input side connection line, and obtaining the amount of use of the element indicated by the input side connection line. Repeat the process from the extraction of the input side connecting line connecting the required amount, the next box as the target box to the target box, and the next box Flow reverse developing means for reverse developing the manufacturing process flow until a raw material purchases,
Production planning program characterized by functioning as The flow reverse expansion means includes
  The process data is searched for a box indicating product sales in the production process flow, the conversion data for searching the conversion data and setting the extracted box as the end point box is extracted,
  The starting box set in the extracted conversion data is identified as the target box;
  The production planning program according to claim 1, wherein: The flow reverse expansion means includes
  When the production process flow is reversely developed from the product, for each target box, the necessary amount is an allocation value in the target box, and an element corresponding to the necessary amount is an allocation element, and the conversion data is searched. Extracting the conversion data in which the target box is set as the end point box;
  Based on the extracted conversion data, calculate an allocation basic value that can be allocated from an optimal solution of the element as an allocated element allocated by the allocation value for the element corresponding to the conversion data,
  Back-calculating the relational expression based on the processing data of the target box to calculate a provisioned value to be allocated to the allocation element from the allocation basic value as the usage amount,
  The production planning program according to claim 1, wherein: The flow reverse expansion means includes
  When the next box is a box indicating raw material purchase, it is determined that the element indicated by the input side connecting line of the target box connecting the next box and the target box is a raw material, The usage amount of the element indicated by the calculated input side connecting line is used as the usage amount of the raw material used by the product.
  The production planning program according to claim 1, wherein: Among the elements indicated by the connecting line traced from the box corresponding to the product to the box indicating the raw material purchase based on the conversion data in the flow reverse development means, the elements excluding the product and the raw material are intermediate. As a product, the usage amount of the element calculated by the flow reverse development means as the usage amount of the intermediate product,
  The material balance configuration diagram is generated by arranging the use amount of the intermediate product and the intermediate element generated from the raw material and the use amount of the raw material and the raw material in reverse order from the product until the product is generated.
  The production planning program according to claim 1, wherein:

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