WO2016076023A1

WO2016076023A1 - Schedule managing device, schedule managing method, and program

Info

Publication number: WO2016076023A1
Application number: PCT/JP2015/077273
Authority: WO
Inventors: ▲高▼野　善之; 正齋藤
Original assignee: Ｎｅｃソリューションイノベータ株式会社
Priority date: 2014-11-14
Filing date: 2015-09-28
Publication date: 2016-05-19
Also published as: JP6323890B2; JPWO2016076023A1

Abstract

A schedule managing device (10) comprises: an extracting unit (11) which extracts one manufacturing order at a time sequentially from among a plurality of manufacturing orders; and a generating unit (12) which takes each manufacturing order, in the order in which the manufacturing orders have been extracted by the extracting unit (11), as a manufacturing order to be processed, and executes a process whereby the manufacturing order to be processed is allocated to one manufacturing facility. The generating unit (12) calculates for each manufacturing facility a predicted operating time required to execute the manufacturing order to be processed, and on the basis of a relationship between the manufacturing order to be processed, and the manufacturing order to be executed immediately before said manufacturing order, calculates, for each manufacturing facility, a predicted operating time required for setting up prior to executing the manufacturing order to be processed. On the basis of the sum of the predicted operating time for executing the manufacturing order and the predicted operating time for setting up, the generating unit (12) then determines one manufacturing facility to which the manufacturing order to be processed is to be allocated.

Description

Schedule management device, schedule management method, and program

The present invention relates to a schedule management device, a schedule management method, and a program.

Cited Document 1 discloses a line selection method in which one line is selected from a plurality of lines each producing a component mounting board using a computer. In this line selection method, the board to be produced is produced based on the characteristics of the board to be produced and the power consumption calculated based on the characteristics of each line, the stability of mounting accuracy, the ease of setup, etc. Determine the line to be played.

JP 2008-47835 A

The line selection method described in the cited document 1 calculates the ease of setup based on the characteristics of the substrate to be produced and the characteristics of each line. However, the ease of setup varies greatly depending on other factors. In the case of the calculation method of Cited Document 1, the ease of setup may not be sufficiently evaluated. As a result, there is a risk of selecting an inappropriate line for the substrate to be produced.

This invention makes it a subject to provide the technique which distributes a several manufacturing order to several manufacturing equipment by the method which is not in the past, and produces | generates a manufacturing schedule.

According to the present invention,
A schedule management device that distributes a plurality of manufacturing orders to a plurality of manufacturing facilities and generates a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities,
Extraction means for extracting one of the production orders in order from a plurality of the production orders;
(1) The manufacturing order is a processing target in the order extracted by the extraction means, the processing order to be processed is distributed to one manufacturing facility, and (2) the order of distribution to each manufacturing facility is Generating means for executing the process of generating the manufacturing schedule as an execution order;
Have
In the process of (1), the generation unit calculates at least one of a predicted work time, a predicted power consumption amount, and a predicted power consumption fee required for executing the manufacturing order to be processed for each manufacturing facility. In addition, based on the relationship between the manufacturing order to be processed and the manufacturing order most recently assigned to each of the manufacturing facilities, the estimated work time required for the setup before executing the manufacturing order to be processed, the predicted use Calculate at least one of the electric power amount and the predicted electric power usage fee for each manufacturing facility, and execute the manufacturing order to be processed and the total predicted work time required for the setup before the manufacturing order is executed, the prediction A schedule management device that determines one manufacturing facility that distributes the manufacturing order to be processed based on the amount of power used or the predicted power consumption is provided. It is.

Moreover, according to the present invention,
The computer distributes a plurality of manufacturing orders to a plurality of manufacturing facilities, and generates a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities.
The computer is
An extraction step of extracting one of the production orders in order from the plurality of the production orders;
(1) The manufacturing order is processed in the order extracted in the extraction step, the manufacturing order to be processed is distributed to one manufacturing facility, and (2) the order of distribution to each manufacturing facility is A generation step of executing the process of generating the manufacturing schedule as an execution order;
Run
In the generating step, in the process of (1), at least one of a predicted work time, a predicted power consumption amount and a predicted power consumption fee required for executing the manufacturing order to be processed is calculated for each manufacturing facility. In addition, based on the relationship between the manufacturing order to be processed and the manufacturing order most recently assigned to each of the manufacturing facilities, the estimated work time required for the setup before executing the manufacturing order to be processed, the predicted use Calculate at least one of the electric power amount and the predicted electric power usage fee for each manufacturing facility, and execute the manufacturing order to be processed and the total predicted work time required for the setup before the manufacturing order is executed, the prediction A schedule management method for deciding one manufacturing facility that distributes the manufacturing order to be processed based on a power consumption amount or a predicted power consumption amount. It is subjected.

Moreover, according to the present invention,
A program for causing a computer to distribute a plurality of manufacturing orders to a plurality of manufacturing facilities and to generate a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities,
The computer,
Extraction means for extracting one of the manufacturing orders in order from a plurality of the manufacturing orders;
(1) The manufacturing order is a processing target in the order extracted by the extraction means, the processing order to be processed is distributed to one manufacturing facility, and (2) the order of distribution to each manufacturing facility is Generating means for executing the process of generating the manufacturing schedule as an execution order;
Function as
In the process of (1), the generation unit is configured to calculate at least one of the predicted work time, the predicted power consumption, and the predicted power consumption required for executing the manufacturing order to be processed for each manufacturing facility. In addition, based on the relationship between the manufacturing order to be processed and the manufacturing order most recently assigned to each of the manufacturing facilities, the estimated work time required for the setup before executing the manufacturing order to be processed, the predicted use Calculate at least one of the electric power amount and the predicted power usage fee for each manufacturing facility, and execute the manufacturing order to be processed and the total estimated work time and the prediction required for the setup before the execution of the manufacturing order Provided is a program for determining one manufacturing facility for distributing the manufacturing orders to be processed based on the amount of power used or the predicted power consumption. That.

Moreover, according to the present invention,
A schedule management device that distributes a plurality of manufacturing orders to a plurality of manufacturing facilities and generates a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities,
Extraction means for extracting one of the production orders in order from a plurality of the production orders;
(1) ′ a process in which the manufacturing orders are processed in the order extracted by the extraction means, and the manufacturing order to be processed is allocated to one manufacturing facility; and (2) ′ the order allocated to each manufacturing facility. Generating means for generating the manufacturing schedule by setting the execution start time and the execution end time of each of the manufacturing orders,
Have
The generation unit calculates a prediction start time and a prediction end time when executing the manufacturing order to be processed in the processing of (1) ′ for each manufacturing facility, and a power unit price that is different for each time zone. In consideration of the above, schedule management for calculating a predicted power usage fee required to execute the manufacturing order to be processed and determining one manufacturing facility to which the manufacturing order to be processed is allocated based on the predicted power usage fee An apparatus is provided.

Moreover, according to the present invention,
The computer distributes a plurality of manufacturing orders to a plurality of manufacturing facilities, and generates a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities.
The computer is
An extraction step of extracting one of the production orders in order from the plurality of the production orders;
(1) ′ a process in which the manufacturing orders are processed in the order extracted in the extraction step, and the manufacturing order to be processed is distributed to one of the manufacturing facilities; and (2) ′ the order of distribution to the manufacturing facilities. A process of generating the manufacturing schedule by setting the execution start time and the execution end time of each of the manufacturing orders,
Run
In the generation step, in the process of (1) ′, a prediction start time and a prediction end time when the manufacturing order to be processed is executed are calculated for each manufacturing facility, and the power unit price varies depending on the time zone. In consideration of the above, schedule management for calculating a predicted power usage fee required to execute the manufacturing order to be processed and determining one manufacturing facility to which the manufacturing order to be processed is allocated based on the predicted power usage fee A method is provided.

Moreover, according to the present invention,
A program for causing a computer to distribute a plurality of manufacturing orders to a plurality of manufacturing facilities and to generate a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities,
The computer,
Extraction means for extracting one of the manufacturing orders in order from a plurality of the manufacturing orders;
(1) ′ a process in which the manufacturing orders are processed in the order extracted by the extraction means, and the manufacturing order to be processed is allocated to one manufacturing facility; and (2) ′ the order allocated to each manufacturing facility. Generating means for generating the manufacturing schedule by setting the execution start time and the execution end time of each of the manufacturing orders.
Function as
In the process of (1) ′, the generation unit calculates a predicted start time and a predicted end time when the manufacturing order to be processed is executed for each manufacturing facility, and a power unit price that is different for each time zone In consideration of the above, a program for calculating a predicted power usage fee required for executing the manufacturing order to be processed and determining one manufacturing facility to which the manufacturing order to be processed is allocated based on the predicted power usage fee is calculated. Provided.

According to the present invention, a technique for generating a manufacturing schedule by distributing a plurality of manufacturing orders to a plurality of manufacturing facilities by an unprecedented method is realized.

The above-described object and other objects, features, and advantages will be further clarified by a preferred embodiment described below and the following drawings attached thereto.

It is a figure which shows notionally an example of the hardware constitutions of the apparatus of this embodiment. It is an example of the functional block diagram of the schedule management apparatus 10 of this embodiment. It is a figure which shows typically an example of the manufacturing order which the schedule management apparatus 10 of this embodiment manages. It is a figure for demonstrating an example of the process which extracts the predetermined number of past manufacturing orders from the past performance. It is a figure for demonstrating an example of the process which extracts the predetermined number of past manufacturing orders from the past performance. It is a figure which shows typically an example of the information for determining the level of setup. It is a figure which shows typically an example of the information for determining the estimated work time of a setup, and estimated electric power consumption. It is a figure which shows typically an example of the information managed by the production | generation part. It is a flowchart which shows an example of the flow of the process by the schedule management apparatus 10 of this embodiment. It is a figure which shows typically an example of the information managed by the production | generation part. It is a figure which shows typically an example of the manufacturing schedule produced | generated by the production | generation part. It is a figure which shows typically an example of the information managed by the production | generation part. It is a figure which shows typically an example of the manufacturing schedule produced | generated by the production | generation part. It is a figure which shows typically an example of the manufacturing schedule produced | generated by the production | generation part. It is a figure which shows typically an example of the information which shows a different electric power unit price for every time slot | zone which the schedule management apparatus 10 hold | maintains. It is a flowchart which shows an example of the flow of the process by the schedule management apparatus 10 of this embodiment. It is a figure which shows typically an example of the data (past performance) which shows the time change of the electric power used at the time of execution of the past manufacture order which the schedule management apparatus 10 of this embodiment uses. It is a figure which shows typically an example of the data (prediction data) which shows prediction of the time change of the electric power used at the time of execution of the manufacturing order of a process target. It is an example of the functional block diagram of the schedule management apparatus 10 of this embodiment. It is a figure which shows typically an example of the manufacturing schedule produced | generated by the production | generation part. It is a figure which shows typically an example of the manufacturing schedule produced | generated by the production | generation part.

First, an example of the hardware configuration of the apparatus according to the present embodiment will be described. Each unit included in the apparatus according to the present embodiment includes a CPU (Central Processing Unit) of an arbitrary computer, a memory, a program loaded in the memory (a program stored in the memory from the stage of shipping the apparatus in advance, a CD ( Compact Disc) and other storage media and programs downloaded from servers on the Internet), storage units such as hard disks that store the programs, and any combination of hardware and software, mainly a network connection interface It is realized by. It will be understood by those skilled in the art that there are various modifications to the implementation method and apparatus.

FIG. 1 is a diagram conceptually illustrating an example of a hardware configuration of an apparatus according to the present embodiment. As shown in the figure, the apparatus according to the present embodiment includes, for example, a CPU 1A, a RAM (Random Access Memory) 2A, a ROM (Read Only Memory) 3A, a display control unit 4A, a display 5A, and operation reception that are connected to each other via a bus 10A. Unit 6A, operation unit 7A, communication unit 8A, auxiliary storage device 9A, and the like. Although not shown, other elements such as an input / output interface connected to an external device by wire, a microphone, and a speaker may be provided.

CPU 1A controls the entire computer of the apparatus together with each element. The ROM 3A includes an area for storing programs for operating the computer, various application programs, various setting data used when these programs operate. The RAM 2A includes an area for temporarily storing data, such as a work area for operating a program. The auxiliary storage device 9A is, for example, an HDD (Hard Disc Drive), and can store a large amount of data.

The display 5A is, for example, a display device (LED (Light Emitting Diode) display, liquid crystal display, organic EL (Electro Luminescence) display, etc.). The display 5A may be a touch panel display integrated with a touch pad. The display control unit 4A reads data stored in a VRAM (Video RAM), performs predetermined processing on the read data, and then sends the data to the display 5A to display various screens. The operation reception unit 6A receives various operations via the operation unit 7A. The operation unit 7A includes operation keys, operation buttons, switches, a jog dial, a touch panel display, a keyboard, and the like. The communication unit 8A is wired and / or wirelessly connected to a network such as the Internet or a LAN (Local Area Network) and communicates with other electronic devices.

Hereinafter, this embodiment will be described. Note that the functional block diagram used in the following description of the embodiment shows functional unit blocks rather than hardware unit configurations. In these drawings, each device is described as being realized by one device, but the means for realizing it is not limited to this. That is, it may be a physically separated configuration or a logically separated configuration. In addition, the same code | symbol is attached | subjected to the same component and description is abbreviate | omitted suitably.

<First Embodiment>
First, an outline of the present embodiment will be described. The schedule management apparatus of this embodiment distributes a plurality of manufacturing orders to a plurality of manufacturing facilities. Furthermore, the schedule management apparatus determines an execution order in which the manufacturing orders assigned to the respective manufacturing facilities are executed in the respective manufacturing facilities. In this way, the schedule management device generates a production schedule for a plurality of production orders by a plurality of production facilities.

Multiple production orders can be executed in any of multiple production facilities. The manufactured product is not particularly limited. The product may be an intermediate product or a finished product. For example, the product may be a plastic molded product, a component mounting board, a pigment, a dye, a resin, or the like.

The manufacturing facility may be a manufacturing device itself or a manufacturing system (a manufacturing line or the like) configured by combining a plurality of manufacturing devices. The characteristics of the plurality of manufacturing facilities are different from each other due to, for example, the cumulative years of use, the manufacturer, the lot number (the optimum lot number, the minimum lot number, etc.), and the like. For this reason, even when the same manufacturing order (same product, same quantity) is executed, the work time required to complete, the amount of power used, the power usage fee, and the like can be different from each other.

Also, one manufacturing facility may execute a plurality of manufacturing orders in succession. Then, before executing a subsequent production order, it is necessary to perform a predetermined setup. The contents of the setup are various. For example, cleaning of the manufacturing equipment, replacement of parts of the manufacturing equipment, change of the setting of the manufacturing equipment, change of the material set at a predetermined position of the manufacturing equipment, heating / cooling of the manufacturing equipment, etc. Conceivable. The work time required for this setup, the amount of power used, the power usage fee, and the like may vary due to the relationship between the manufacturing orders.

For example, when the same material is used for both the previous manufacturing order and the subsequent manufacturing order, the work of changing the material set at a predetermined position of the manufacturing equipment may be unnecessary. Also, it may not be necessary to clean the part through which such material passes. On the other hand, when the previous manufacturing order and the subsequent manufacturing order use different materials, it is necessary to change the material to be set at a predetermined position in the manufacturing facility. In addition, it may be necessary to clean a portion through which such material passes.

Thus, due to the relationship between the manufacturing orders that follow, the work content and work amount in the setup can be different from each other. As a result, working times can be different from each other. Further, if the power supply of at least a part of the manufacturing facility is kept ON during such setup, the amount of power used and the amount of power used may differ depending on the working time. Furthermore, when the processing equipment is turned off once for cleaning and then turned on after cleaning, a lot of power and time may be spent on preparation for operation when the power is turned off. is there. As a result, the amount of power used and the amount of power used may increase compared to the case where the manufacturing order is executed continuously with the power of the manufacturing equipment turned on.

The schedule management apparatus of the present embodiment can generate a manufacturing schedule in consideration of such points. The schedule management apparatus according to the present embodiment executes the following process in the process of determining which manufacturing facility a certain manufacturing order is allocated to.

First, based on the characteristics of the manufacturing order of the processing target (target to be assigned to any manufacturing facility), the schedule management device predicts the estimated work time and prediction required when the manufacturing order is executed in each of the plurality of manufacturing facilities. At least one of the used electric energy and the predicted electric power charge is calculated.

In addition, the schedule management device, when the manufacturing order is executed at each manufacturing facility, the relationship between the manufacturing order to be processed and the manufacturing order to be executed immediately before the manufacturing order (the order of execution is different) Based on the relationship between the manufacturing orders to be processed), at least one of the predicted work time, the predicted power consumption, and the predicted power consumption required for the setup before executing the manufacturing order to be processed is calculated for each manufacturing facility. .

The schedule management device then executes the manufacturing order of the processing target based on the total predicted work time, the predicted power consumption, or the predicted power consumption required for the execution of the manufacturing order to be processed and the setup before the execution of the manufacturing order. Determine one manufacturing facility to distribute. For example, the schedule management apparatus allocates the manufacturing order to be processed to a manufacturing facility having the smallest total predicted work time, predicted power consumption, or predicted power consumption.

According to the schedule management apparatus of this embodiment, it is possible to generate a production schedule in which each of a plurality of production orders is allocated to an optimum production facility.

Next, the configuration of the schedule management apparatus of this embodiment will be described in detail. FIG. 2 shows an example of a functional block diagram of the schedule management apparatus 10 of the present embodiment. As shown in the figure, the schedule management apparatus 10 includes an extraction unit 11 and a generation unit 12.

The extraction unit 11 extracts one manufacturing order from a plurality of manufacturing orders in a predetermined order. The production | generation part 12 makes a manufacturing order the process target in the order extracted by the extraction part 11, and distributes the said manufacturing order to one manufacturing equipment. That is, the production | generation part 12 distributes a production order to a production facility in the order extracted by the extraction part 11. Hereinafter, the configuration of the extraction unit 11 and the generation unit 12 will be described in detail.

The extraction unit 11 extracts one manufacturing order in order from a plurality of manufacturing orders. Each production order includes at least a product to be manufactured (hereinafter may be referred to as “order product”), a quantity to be manufactured (hereinafter may be referred to as “order quantity”), and a delivery date (hereinafter referred to as “order delivery date”). Information).

Here, FIG. 3 shows an example of a plurality of production orders managed by the schedule management apparatus 10. The production order shown relates to a plastic molded product.

In the order ID column, identification information for identifying each of the plurality of manufacturing orders is shown. In the product ID column, identification information for identifying the order product is shown. In the delivery date column, the order delivery date is shown. The order delivery date may be a delivery date for delivering the order product to the customer, a delivery date for delivering the order product to a predetermined warehouse that is temporarily stored before delivery to the customer, or otherwise. Also good.

The resin column shows the resin (ABS resin, PP resin, etc.) used in the production of the order product. In the color column, the color of the order product (plastic molded product) is shown. The color column may indicate the type of pigment or dye used for coloring the order product. If the type and color of the resin to be used are stored in a database as product information for each product ID, the resin and color columns may not be included in the manufacturing order. In this case, by searching the database using the product ID included in each of the plurality of production orders as a key, it is possible to specify the resin used in the production of each order product and the color of each order product. As will be described in detail below, the resin and color are used, for example, when predicting the work time required for setup, the amount of power used, and the amount of power used.

The order quantity is displayed in the order quantity column. In the remaining quantity column, the quantity that has not been started at the present time among the ordered quantities is shown. For example, the order ID “10001” indicates the order quantity “1200” and the remaining amount “1200”. From this, it can be seen that the order ID “10001” has not been completely started, and no one is manufactured yet. On the other hand, the order ID “10002” indicates the order quantity “800” and the remaining amount “400”. From this, it is understood that part of the order ID “10002” has been started, that is, 400 pieces have been manufactured, and part of the order ID “10002” has not started, that is, the remaining 400 pieces have not been manufactured yet.

In the column scheduled for the day, the planned quantity to be manufactured on the day (planned production quantity) is shown. For example, the production schedule is generated on a daily basis. The current day here means the day to which the production schedule being generated belongs. For example, when the production schedule of October 1, 2014 is being generated, the current day here means October 1, 2014. Note that the manufacturing schedule may be generated in different units (eg, weekly unit, monthly unit). In this case, the scheduled day column shows the planned quantity to be manufactured in the unit (eg, current week, current month) to which the production schedule being generated belongs.

The value of the field scheduled for the day is determined by the operator. For example, the operator inputs the quantity to be preferentially executed in the column of the production order to be preferentially executed on the day. Although details will be described below, a manufacturing schedule in which the manufacturing order is preferentially executed can be generated by the input.

The priority column shows the priorities of a plurality of production orders. In the illustrated example, the priority is indicated by a number. The smaller the number, the higher the priority.

The operator determines the value in the priority column. For example, the operator inputs a higher priority (in the case of the figure, a smaller number) in the column of the production order to be preferentially executed. Although details will be described below, a manufacturing schedule in which the manufacturing order is preferentially executed can be generated by the input. For example, the operator inputs a predetermined value in the column for the current day schedule of each of the plurality of production orders to be preferentially executed on the current day, and further uses the value in the priority column to set the predetermined value in the column for the current day schedule. Priorities may be assigned to a plurality of manufacturing orders in which the value of is input.

Next, a process in which the extraction unit 11 extracts one manufacturing order in order from such a plurality of manufacturing orders will be described.

The extraction unit 11 includes, for example, at least a delivery date (order delivery date) for each production order, a production quantity for each production order (order quantity and / or scheduled quantity on the day), and a priority for each production order specified by the user. Production orders can be extracted in the order determined based on one (hereinafter, also referred to as “extraction order”).

For example, the extraction unit 11 extracts manufacturing orders in the extraction order determined based on at least one of the following conditions (A) to (D).

(A) Extraction is performed in order from production orders with close delivery dates.
(B) Extract in order from the production order with the largest production quantity.
(C) Extraction is performed in order from the manufacturing order with the highest priority specified by the user.
(D) Extraction is sequentially performed from the production order designated to be executed on the current day by the user.

For example, the extraction unit 11 may extract the production order in the extraction order determined by combining two or more of the above conditions (A) to (D). In this case, for example, priorities are assigned in advance to the conditions (A) to (D). Then, the extraction order is determined by preferentially applying a condition having a high priority. When there are a plurality of manufacturing orders that cannot be ordered only by a certain condition (a plurality of manufacturing orders that have the same order), the next highest priority condition is applied to order the plurality of manufacturing orders.

For example, suppose that condition (A) has the highest priority. In this case, first, the extraction order of a plurality of production orders is determined by applying the condition (A). As a result, the extraction order in which the production orders with close delivery dates are extracted earlier is determined. However, when there are a plurality of production orders having the same delivery date, the same order is assigned to the plurality of production orders. In this case, the next highest priority condition is applied to order a plurality of manufacturing orders with the same order of peers.

For example, when the next highest priority condition is (B), a production with a large production quantity is performed with respect to the plurality of production orders (a plurality of production orders that are in the same order in the ordering in the condition (A)). The order in which orders are extracted earlier is determined. Thereafter, the extraction order of a plurality of production orders can be determined by applying the above conditions in order according to the priority order. For example, the extraction unit 11 can extract the production order according to the extraction order determined in this way.

As another example, when the production order relates to a plastic molded product, the extraction unit 11 specifies the delivery date of each production order (order delivery date), the production quantity of each production order (order quantity and / or scheduled quantity on the day), and the user specified The production orders may be extracted in the order determined based on at least one of the priority of each production order, the type of resin used in the production of the order product, and the color of the order product (plastic molded product). .

For example, the extraction unit 11 extracts the production order according to the extraction order determined based on at least one of the following conditions (A) to (F).

(A) Extraction is performed in order from production orders with close delivery dates.
(B) Extract in order from the production order with the largest production quantity.
(C) Extraction is performed in order from the manufacturing order with the highest priority specified by the user.
(D) Extraction is sequentially performed from the production order designated to be executed on the current day by the user.
(E) Extraction is performed so that production orders using the same resin are continuous.
(F) Extraction in order of darkness or lightness of order products.

For example, the extraction unit 11 may extract the production order according to the extraction order determined by combining two or more of the above conditions (A) to (F). In this case, for example, priorities are assigned in advance to the conditions (A) to (F). Then, the extraction order is determined by preferentially applying a condition having a high priority. When there are a plurality of manufacturing orders that cannot be ordered only by a certain condition (a plurality of manufacturing orders that have the same order), the next highest priority condition is applied to order the plurality of manufacturing orders.

For example, suppose that condition (A) has the highest priority. In this case, first, a condition (A) is applied to order a plurality of production orders. In other words, the extraction order in which the production orders with close delivery dates are extracted earlier is determined. However, when there are a plurality of production orders having the same delivery date, the same order is assigned to the plurality of production orders. In this case, the next highest priority condition is applied to order a plurality of manufacturing orders with the same order of peers.

For example, when the next highest priority condition is (F), the color of the plastic molded product for the plurality of manufacturing orders (a plurality of manufacturing orders whose orders are the same in the ordering in the condition (A)) The extraction order in which the production orders that are darker (or lighter) are extracted earlier is determined. Note that the extraction unit 11 may hold color information indicating the order of dark color and / or light color, and may perform ordering according to the order of dark color and light color based on this color information. .

Here, the ordering to which the condition (E) is applied will be described. When this condition is applied, first, the extraction unit 11 groups a plurality of manufacturing orders to be ordered for each manufacturing order using the same resin. Thereafter, the extraction unit 11 arranges the groups in a predetermined order and determines the extraction order. In such a case, an extraction order in which a plurality of production orders belonging to the same group is consecutive is determined. That is, an extraction order in which production orders using the same resin are consecutive is determined. In ordering the production orders in each group, a condition that the priority order is (E) or later may be applied.

Also, in ordering between groups, a condition having a priority order of (E) or later may be applied. An example will be described below.

When ordering between groups by applying the condition (A), the extraction unit 11 may first point for each group based on the delivery date of each of one or more manufacturing orders belonging to each group. Good. For example, you may point by the method of becoming a high point, so that there are many manufacturing orders with near delivery date. And the extraction part 11 may determine the extraction order extracted in an order from the group with the said high point.

When ordering between groups by applying the condition (B), first, the extraction unit 11 performs point assignment for each group based on the production quantities of one or more production orders belonging to each group. Also good. For example, statistical values of the production quantity (eg, average value, maximum value, mode value, total value, etc.) may be calculated as points of each group. And the extraction part 11 may determine the extraction order extracted in an order from the group with the said high point.

When ordering between groups by applying the condition (C), first, the extraction unit 11 performs point assignment for each group based on the priority of each of one or more manufacturing orders belonging to each group. Also good. For example, you may point by the method of becoming a high point, so that there are many manufacturing orders with high priority. And the extraction part 11 may determine the extraction order extracted in an order from the group with the said high point.

When ordering between groups by applying the condition (D), the extraction unit 11 first sets the number of production orders designated to be executed on the current day among one or a plurality of production orders belonging to each group. Based on this, points may be assigned for each group. For example, the number of production orders designated to be executed on the current day may be calculated as the point. And the extraction part 11 may determine the extraction order extracted in an order from the group with the said high point.

When ordering between groups by applying the condition (F), first, the extraction unit 11 points to each group based on the color of the plastic molded product of each of one or more manufacturing orders belonging to each group. May be performed. For example, the points may be pointed by a method in which the point becomes higher as the number of dark-colored production orders increases, or a method in which the point becomes higher as the number of light-colored production orders increases. And the extraction part 11 may determine the extraction order extracted in an order from the group with the said high point.

Returning to FIG. 2, the generation unit 12 (1) processes the manufacturing orders in the order extracted by the extraction unit 11, distributes the manufacturing orders to be processed to one manufacturing facility, and (2) assigns the manufacturing order to each manufacturing facility. A process of generating a production schedule by determining an execution order in which the distributed production orders are executed in each production facility is executed.

First, the process (1) will be described. The generation unit 12 sets manufacturing orders as processing targets in the order extracted by the extraction unit 11, and performs the following processes (1-1) to (1-3) on the manufacturing orders to be processed.

(1-1) At least one of a predicted work time, a predicted power consumption amount and a predicted power consumption fee required for executing the manufacturing order to be processed is calculated for each manufacturing facility.
(1-2) A relationship between a manufacturing order to be processed and a manufacturing order that is to be executed immediately before the manufacturing order when the manufacturing order is executed at each manufacturing facility (manufacturing with different execution orders) Based on the relationship between the orders, at least one of the predicted work time, the predicted power consumption, and the predicted power consumption required for the setup before executing the manufacturing order to be processed is calculated for each manufacturing facility.
(1-3) Distributing the processing orders to be processed based on the execution of the manufacturing order to be processed and the total predicted work time, the predicted power consumption or the predicted power consumption required for setup before execution of the manufacturing order Determine one manufacturing facility.

The process (1-1) will be described. The predicted work time, predicted power consumption and predicted power consumption required to execute a production order are the estimated work time and predicted power consumption required from the start of the production of the order product to the completion of the production of the order product for the order quantity. And predicted electricity usage rate. In the process (1-1), any method can be employed for the calculation. An example will be described below.

For example, the generation unit 12 includes, based on the past performance of each of the plurality of manufacturing orders in each of the plurality of manufacturing facilities, the predicted work time, the predicted power consumption, and the predicted power consumption charge required for executing the manufacturing order to be processed. Can be calculated for each production facility.

In the case of this example, the actual value (past actual result) when each of a plurality of past manufacturing orders is executed is stored in the schedule management apparatus 10 or other apparatus for each manufacturing facility. For example, for each manufacturing facility, as the results for each manufacturing order, the product ID of the order product, the manufacturing date (production date), the manufacturing number (production number), the setup time, the work time, the power consumption (wh), Records of changes in power consumption (w) (time change), the number of abnormalities that occurred, etc. are accumulated. Then, the generation unit 12 calculates at least one of the predicted work time, the predicted power usage amount, and the predicted power usage fee for each manufacturing facility using the data.

For example, the generation unit 12 extracts the results of one or more predetermined manufacturing orders from the past manufacturing order results for each manufacturing facility, based on the contents of the manufacturing order to be processed. For example, the generation unit 12 may extract the results of a predetermined number of past manufacturing orders from the side where the product IDs of the order products match and the production date is close to the current time. In addition, the generation unit 12 may extract the results of a predetermined number of past manufacturing orders from the order in which the product IDs of the order products match and the number of manufacturing is close to the order quantity of the manufacturing order to be processed. In addition, the generation unit 12 may extract the results of a predetermined number of past production orders from the side where the product IDs of the order products match and the setup time is close to the setup time of the production order to be processed. In addition, the generation unit 12 may extract the results of a predetermined number of past manufacturing orders from the one in which the product IDs of the order products match and the number of abnormalities that have occurred is small.

In addition, the generation unit 12 selects at least two or more of the manufacturing date (production date), the manufacturing number (production number), the setup time, and the number of abnormal cases from the past manufacturing orders with the same product ID of the order product. You may extract the performance of the predetermined number of past manufacturing orders determined based on the element (parameter). For example, you may extract based on conditions as shown in FIG.

FIG. 4 shows a method of attaching points to each past manufacturing order based on the four elements of manufacturing date (production date), manufacturing number (production number), setup time, and number of abnormalities. The four elements are weighted. In FIG. 4, the manufacturing date (production date) is given the highest weight so that a new manufacturing order can be easily selected. Note that the weight values and numerical calculation formulas shown are merely examples, and the present invention is not limited thereto.

FIG. 5 shows a specific example in which the results of one past production order are extracted by the method shown in FIG. FIG. 5 shows the No. executed in the manufacturing facility 1. The results of five past production orders 1 to 5 are shown. The production date “2014/3/14”, the number of productions “2000”, and the setup time “2.00” described in the margins on the upper side of the table indicate details of the manufacturing order to be processed. In the figure, the product ID of the manufacturing order to be processed is not shown. It is assumed that the results of the five past manufacturing orders 1 to 5 match the product IDs of the processing order manufacturing order and the order product.

The product ID, production date, production number, setup time, abnormality (number of cases), and power consumption in the table are the results of past production orders. Although not shown in the figure, the working time, the transition (time change) of power consumption (w) during execution may be accumulated.

The column of similarity in the table shows the numerical calculation formula shown in FIG. 4 and the value calculated based on the actual value of each production order. Points are given in the calculation formula shown in FIG. 4 for each of the four elements of manufacturing date (production date), manufacturing number (production number), setup time, and number of abnormal cases. And the value which totaled the point calculated for every element is shown by the column of total. The “recruitment” mark shown in FIG. This means that the results of one past production order have been extracted. The past production order with the smallest total value is adopted.

Note that the past production orders may be data for the past several years. That is, old data may be erased.

The generation unit 12 extracts the results of one or more past manufacturing orders for each manufacturing facility as described above, for example.

When a past production order result is extracted, the generation unit 12 predicts the predicted work time and prediction of the processing order to be processed based on the work time at the time of execution of the production order and / or the actual value of power consumption. At least one of the used electric energy and the predicted electric power charge is calculated. For example, the generation unit 12 uses the extracted work time and / or power consumption (actual value) P of the past production order based on the production number Vp of the past production order and the order quantity Vc of the production order to be processed. It correct | amends and the value (example: (P / Vp) xVc) after correction | amendment is calculated as prediction work time and / or prediction electric power used.

On the other hand, when the results of a plurality of past manufacturing orders are extracted, the generation unit 12 uses the above-described method, for example, for each past manufacturing order, the corrected value (example: (P / Vp) × Vc) And statistical values thereof (eg, average value, mode value, maximum value, minimum value, etc.) may be calculated. The calculated statistical value may be used as the predicted work time and / or the predicted power consumption of the manufacturing order to be processed.

In addition, when calculating the predicted power usage rate of the manufacturing order to be processed, the generation unit 12 holds information indicating the power unit price (yen / kwh) in advance. And the production | generation part 12 can calculate the product of prediction use electric energy and a unit price as prediction use electric power charge after calculating prediction use electric energy for every manufacturing equipment as mentioned above.

For example, the generation unit 12 can calculate, for each manufacturing facility, at least one of the predicted work time, the predicted power consumption, and the predicted power consumption fee required for executing the manufacturing order to be processed. .

Next, the process (1-2) will be described. In the processing, the generation unit 12 predicts the work time required for the setup before executing the manufacturing order to be processed based on the relationship between the manufacturing order to be processed and the manufacturing order most recently assigned to each manufacturing facility. Then, at least one of the predicted power consumption and the predicted power charge is calculated for each manufacturing facility.

As will be described in detail below, the generation unit 12 sets the order assigned to each manufacturing facility as the execution order in which the manufacturing orders assigned to each manufacturing facility are executed in each manufacturing facility. For this reason, when processing the manufacturing order to be processed, the manufacturing order that was assigned to the manufacturing equipment most recently is immediately before the manufacturing order to be processed when the manufacturing order to be processed is assigned to each manufacturing equipment. Production order to be executed. Based on the relationship between the manufacturing orders (the relationship between the manufacturing orders whose order of execution is different), the generation unit 12 predicts the estimated work time and the estimated electric energy used for the setup before executing the manufacturing order to be processed. And at least one of the predicted electric power charges is calculated for each manufacturing facility.

For example, the generation unit 12 determines the predicted work time, the predicted power consumption, and the predicted power consumption fee required for setup based on the relationship between the materials used in each of the manufacturing orders and the manufacturing equipment most recently assigned to the processing target. At least one of the above may be calculated for each manufacturing facility.

For example, when the production order relates to a plastic molded product, the generation unit 12 determines the relationship between the resin used in each of the production orders assigned to the processing target and the production equipment, and the color relationship of the plastic molded product. Based on at least one of them, at least one of the predicted work time required for the setup, the predicted power consumption, and the predicted power consumption fee may be calculated for each manufacturing facility.

Here, an example will be described. For example, the generation unit 12 determines the manufacturing order to be processed based on the relationship between the manufacturing order to be processed and the manufacturing order most recently assigned to each manufacturing facility (the relationship between the manufacturing orders whose execution order varies). The setup before execution is classified into “large setup” or “small setup”. The larger setup means more time-consuming setup.

For example, as illustrated in FIG. 6, the generation unit 12 retains information indicating a relationship between manufacturing orders classified as a setup size. According to the information shown in FIG. 6, the relationship between production orders whose execution order fluctuates (for example, the type of resin used in each production order, the color of the plastic molded product in each production order) is the column “Previous” and When the relationship between the pairs described in the “after” column is satisfied, it is indicated that the setup before the subsequent manufacturing order is classified as the setup size. If the relationship shown in FIG. 6 is not satisfied, the setup before executing the subsequent production order is classified as a setup small.

According to FIG. 6, when the color of the order product (plastic molded product) performed before is white and the color of the order product (plastic molded product) performed later is black, In the opposite case, it can be seen that the setup prior to the execution of the subsequent production order is classified as a setup large. Furthermore, when the resin used in the manufacturing order performed before is ABS and the resin used in the manufacturing order performed later is PP, the setup before executing the subsequent manufacturing order is greatly set up. You can see that it is classified.

And the production | generation part 12 hold | maintains the information which predetermined the estimated work time (guideline) and the estimated electric power consumption (guideline) of each setup large and setup small, for example, as shown, for example in FIG. Then, after classifying the setup before executing the processing target manufacturing order for each manufacturing facility into the setup large and the setup small, refer to the information shown in FIG. 7 and estimate the setup required before executing the processing target manufacturing order. The work time (guideline) and / or the predicted power consumption (guideline) is calculated for each manufacturing facility.

When calculating the predicted power usage fee, the generation unit 12 holds information indicating the power unit price (yen / kwh) in advance. And the production | generation part 12 can calculate the product of prediction use electric energy and a unit price as prediction use electric power charge after calculating prediction use electric energy for every manufacturing equipment as mentioned above.

In addition, although it classify | categorized into two groups of a setup large and a setup small here, it can also classify | categorize into more groups. For example, it may be classified into three groups of large setup, during setup, and small setup, or may be classified into more groups. Even in such a case, the relationship between the manufacturing orders corresponding to the large, medium, and small setups is specified, and the predicted work time (guideline) and the predicted power consumption (guideline) are set in advance. By setting, it is possible to calculate at least one of the estimated work time of the setup time, the predicted power consumption, and the predicted power consumption fee by the same method as described above.

Next, the process (1-3) will be described. For example, by the processes (1-1) and (1-2), the generation unit 12 calculates the predicted work time, the predicted power consumption, and the predicted power consumption charge required for executing the manufacturing order to be processed for each manufacturing facility. After calculating at least one of at least one of the above, and at least one of the predicted work time, the predicted power consumption and the predicted power consumption required for the setup before executing the manufacturing order to be processed, The total predicted work time, the predicted power consumption or the predicted power charge is calculated. And the production | generation part 12 distributes the manufacturing order of a process target to the manufacturing equipment with the smallest total estimated work time, estimated electric energy consumption, or estimated electric power consumption.

Incidentally, the generation unit 12 may manage and update information as shown in FIG. 8 when executing the processes (1-1) to (1-3). The information shown in FIG. 8 includes columns of order ID (manufacturing order ID), extraction order, manufacturing equipment, and latest distribution.

In the column of order ID (manufacturing order ID), identification information of each of a plurality of manufacturing orders to be scheduled is shown. In the column of extraction order, the order extracted by the extraction unit 11 is shown. As can be seen from FIG. 8, the production order ID “10002”, the production order ID “10001”, and the production order ID “10004” are extracted in this order. It can also be seen that the blank production order ID “10003” has not yet been extracted.

In the column of manufacturing equipment, identification information of the manufacturing equipment distributed by the generation unit 12 is shown. As can be seen from FIG. 8, the production order ID “10001” and the production order ID “10002” are allocated to the production facility 1. Then, it can be seen that the production order ID “10004” is allocated to the production facility 2.

In the latest allocation column, a flag is set for the manufacturing order that was most recently allocated to each manufacturing facility. According to FIG. 8, it is understood that the production order ID “10001” is assigned to the manufacturing equipment 1 most recently, and the manufacturing order ID “10004” is assigned to the manufacturing equipment 2 most recently. The generation unit 12 may specify the manufacturing order most recently distributed to each manufacturing facility based on such information.

Although not shown in FIG. 8, the information includes the predicted work time, the predicted power consumption, and the predicted power consumption fee (calculated by the generation unit 12) required when each production order is executed at the distributed manufacturing facility. May be further included. Although not shown in FIG. 8, the information includes the predicted work time, the predicted power consumption, and the predicted power consumption charge required for the previous setup when each production order is executed at the distributed manufacturing facility. At least one of (the value calculated by the generation unit 12) may be further included.

Next, (2) a process for generating a production schedule by determining an execution order in which the production orders distributed to the respective production facilities are executed in each production facility will be described.

The generation unit 12 sets the order assigned to each manufacturing facility as the execution order in which the manufacturing order assigned to each manufacturing facility is executed in each manufacturing facility.

For example, based on the information shown in FIG. 8, the generation unit 12 groups a plurality of manufacturing orders into those that have the same manufacturing equipment. Then, for each group, a plurality of production orders are arranged in order from the smallest extraction order. The production | generation part 12 produces | generates a manufacturing schedule by making this arrangement order into the order which performs the manufacturing order allocated to each manufacturing equipment in each manufacturing equipment. Note that the generation unit 12 can set the setup for the time calculated in the process (1-3) immediately before each manufacturing order in the manufacturing schedule.

Next, an example of the flow of processing by the schedule management apparatus 10 of this embodiment will be described using the flowchart of FIG. It is assumed that there are three manufacturing facilities, manufacturing facilities 1 to 3.

First, the schedule management apparatus 10 acquires information on a plurality of production orders to be scheduled (S10). For example, the schedule management apparatus 10 acquires data of a plurality of manufacturing orders as shown in FIG.

Thereafter, the extraction unit 11 extracts one manufacturing order in a predetermined order from the plurality of manufacturing orders acquired in S10 (S11). Since the means for determining the extraction order has been described above, description thereof is omitted here. For example, it is assumed that the extraction unit 11 first extracts the production order with the production order ID “10002” from the data illustrated in FIG. 3.

Next, the generation unit 12 sets the manufacturing order extracted in S11 as a processing target, and distributes the manufacturing order to be processed to one manufacturing facility (S12).

As described above, the generation unit 12 calculates at least one of the predicted work time, the predicted power usage amount, and the predicted power usage fee required for executing the manufacturing order to be processed for each manufacturing facility. Further, the generation unit 12 calculates at least one of the predicted work time, the predicted power consumption, and the predicted power usage fee required for the setup before executing the manufacturing order to be processed for each manufacturing facility. Thereafter, the generation unit 12 calculates the total predicted work time, the predicted power usage amount, or the predicted power usage fee. And the production | generation part 12 distributes the manufacturing order of a process target to the manufacturing equipment with the smallest total estimated work time, estimated electric energy consumption, or estimated electric power consumption.

Incidentally, as described above, the generation unit 12 sets the order assigned to each manufacturing facility as the execution order in which the manufacturing orders assigned to each manufacturing facility are executed in each manufacturing facility. According to this assumption, there is no production order that is executed before the first extracted production order. Hereinafter, the process example of S12 in the case where the manufacturing order executed before does not exist will be described.

As an example, when determining a manufacturing facility to distribute the first extracted manufacturing order as a processing target, that is, when there is no manufacturing order executed before, the setup before executing the manufacturing order is considered. It does not have to be.

In this case, the generation unit 12 calculates at least one of the predicted work time, the predicted power consumption, and the predicted power consumption required for executing the manufacturing order to be processed for each manufacturing facility, and then calculates the calculated value (example : Predicted work time, predicted power consumption or predicted power charge) can be allocated to the manufacturing order to be processed. Here, it is assumed that the production order ID “10002” is allocated to the production facility 1. As a result, as illustrated in FIG. 10, the extraction order “1” and the manufacturing equipment “1” are associated with the manufacturing order ID “10002”. In addition, a flag is set for the latest distribution.

Fig. 11 schematically shows the manufacturing schedule determined so far. The production order “10002” is assigned to the production facility 1. Note that, as described above, the generation unit 12 can calculate the predicted work time required for executing the manufacturing order to be processed. Based on this calculated value, the length of the production order ID “10002” shown in FIG. 11 is determined. The work start time (8 o'clock in the case of FIG. 11) is determined in advance.

As another example, when there is no previously executed manufacturing order, at least one of the predicted work time, the predicted power usage amount, and the predicted power usage fee required for setup based on the contents of the manufacturing order. May be calculated for each manufacturing facility.

For example, the generation unit 12 predicts work required for setup for the types and combinations of materials (eg, resins, dyes, pigments, solvents, etc.) used at the time of execution of each production order, order quantities, or combinations thereof. A table in which at least one of time and predicted power consumption is associated may be stored in advance. Or, input the type of material (eg, resin, dye, pigment, solvent, etc.) used at the time of execution of each manufacturing order, the combination of materials, the order quantity, or a combination of these, and the estimated work time or prediction required for setup A function that outputs the amount of power used may be stored in advance.

The table and function may be a table and function common to all manufacturing facilities. Or the production | generation part 12 may hold | maintain the several table and function from which content differs for every manufacturing equipment. In the case of the example, the generation unit 12 uses the contents of the manufacturing order to be processed and the predicted work time and the predicted power consumption required for setup when there is no previously executed manufacturing order based on the table or function. At least one of the quantities can be specified. Moreover, the production | generation part 12 can hold | maintain the information which shows an electric power unit price (yen / kwh) previously, and can calculate a prediction use electric power charge based on the said information and the specified prediction electric power consumption.

In the case of this example, the generation unit 12 calculates at least one of the predicted work time, the predicted power usage amount, and the predicted power usage fee required for executing the processing target manufacturing order for each manufacturing facility. In addition, the generation unit 12 may include at least one of a predicted work time, a predicted power consumption amount, and a predicted power consumption fee required for setup before executing the processing target manufacturing order based on the content of the processing target manufacturing order. Is calculated for each manufacturing facility. Then, the generation unit 12 performs processing on a manufacturing facility that has the smallest total predicted work time, predicted power consumption, or predicted power consumption required for execution of the manufacturing order to be processed and setup before execution of the manufacturing order. Target production orders can be distributed.

In the case of this example, the production schedule may be generated in consideration of the setup time calculated here. FIG. 20 schematically shows the manufacturing schedule determined so far in this example. Compared to FIG. 11, there is a difference in whether a setup time exists before the first manufacturing order.

After S12, the generation unit 12 determines whether to continue the process (S13). For example, when there is no manufacturing order that has not been extracted in S11 among the manufacturing orders acquired in S10, the generation unit 12 may determine that the process is to be ended (No in S13). In other words, when the processes of S11 and S12 are performed for all the production orders acquired in S10, the process may be terminated. As another example, when all of the plurality of manufacturing facilities satisfy a predetermined condition, the generation unit 12 may determine that the process is to be ended (No in S13). For example, when all of a plurality of manufacturing facilities have their schedules filled up to a predetermined time due to the distributed manufacturing orders and arrangements (that is, when the current day's schedule is full), the generation unit 12 ends the processing. You may judge.

When the process is continued (Yes in S13), the extraction unit 11 extracts the next one manufacturing order in a predetermined order from the plurality of manufacturing orders acquired in S10 (S11). For example, it is assumed that the extraction unit 11 extracts the manufacturing order with the manufacturing order ID “10001” from the data illustrated in FIG. 3.

Note that at this time, no one production order is assigned to the production equipment 2 and the production equipment 3. On the other hand, a production order with a production order ID “10002” is assigned to the production facility 1. The production order ID “10002” is the production order assigned to the production facility 1 most recently. The generation unit 12 can specify the situation by referring to the information illustrated in FIG. 10, for example.

Thus, in the case where there is no manufacturing order executed before (the manufacturing equipment 2 and the manufacturing equipment 3), the above-described processing example can be adopted. As an example, when determining a manufacturing facility to which a manufacturing order with a manufacturing order ID “10001” is allocated, the

manufacturing facilities

2 and 3 do not need to consider setup. On the other hand, in the manufacturing facility 1, based on the relationship between the manufacturing order ID “10002” and the manufacturing order ID “10001”, at least one of the predicted work time, the predicted power usage amount, and the predicted power usage fee required for setup. Is calculated for each manufacturing facility.

Specifically, the generation unit 12 calculates at least one of the predicted work time, the predicted power usage amount, and the predicted power usage fee required for execution of the processing target manufacturing order for each manufacturing facility. Further, the generation unit 12 predicts a setup work time and a prediction required when the manufacturing equipment 1 executes the manufacturing order ID “10001” based on the relationship between the manufacturing order ID “10002” and the manufacturing order ID “10001”. At least one of the used electric energy and the predicted electric power charge is calculated.

And the production | generation part 12 is "the total estimated work time required for the execution of the manufacturing order of the process target in the manufacturing equipment 1, and the setup before execution of the said manufacturing order, an estimated electric power consumption or an estimated electric power consumption", and , “Estimated work time, predicted power consumption or predicted power consumption required for execution of manufacturing order of processing target in each of

manufacturing facilities

2 and 3” are compared with each other, and the manufacturing facility with the smallest calculated value Sort production orders. Here, it is assumed that the production order ID “10001” is allocated to the production facility 1. As a result, as shown in FIG. 12, the extraction order “2” and the manufacturing equipment “1” are associated with the manufacturing order ID “10001”. Further, a flag is set for the latest allocation of the manufacturing order ID “10001”, and a flag for the latest allocation of the manufacturing order ID “10002” is lowered.

FIG. 13 schematically shows the manufacturing schedule determined so far. The manufacturing order ID “10002” and the manufacturing order ID “10001” are assigned to the manufacturing facility 1 in this order. A setup for the time determined by the generation unit 12 is provided between the production order ID “10002” and the production order ID “10001”.

As another example, as described above, when there is no previously executed manufacturing order, based on the contents of the manufacturing order, the predicted work time, the predicted power consumption, and the predicted power consumption charge required for setup are determined. At least one of them may be calculated for each manufacturing facility. That is, the

manufacturing facilities

2 and 3 may calculate at least one of the predicted work time, the predicted power usage amount, and the predicted power usage fee required for setup based on the contents of the manufacturing order to be processed. In the manufacturing facility 1, based on the relationship between the manufacturing order ID “10002” and the manufacturing order ID “10001”, at least one of the predicted work time, the predicted power consumption, and the predicted power consumption charge required for the setup. May be calculated for each manufacturing facility.

In the case of this example, the generation unit 12 has the smallest total estimated work time, predicted power consumption, or predicted power consumption fee required for execution of the manufacturing order to be processed and setup before execution of the manufacturing order. In addition, the manufacturing order to be processed can be sorted.

Thereafter, the same processing is repeated until it is determined in S13 that the processing is not continued (No). As a result, for example, a manufacturing schedule as shown in FIG. 14 or FIG. 21 is generated.

Note that at an arbitrary timing, the operator may perform an input for determining one to be considered in generating the production schedule from the predicted work time, the predicted power consumption, and the predicted power consumption fee. And the production | generation part 12 may determine the manufacturing equipment which distributes the manufacturing order of a process target based on the prediction amount of the designated element in the process of S12.

Next, the function and effect of this embodiment will be described.

According to the present embodiment, a technique for generating a manufacturing schedule by distributing a plurality of manufacturing orders to a plurality of manufacturing facilities by an unprecedented method is realized.

For example, according to the present embodiment, when a manufacturing order to be processed is allocated to any of a plurality of manufacturing facilities, the manufacturing order to be processed and a manufacturing order executed at each manufacturing facility immediately before the manufacturing order. Based on the relationship, it is possible to calculate at least one of the predicted work time, the predicted power consumption, and the predicted power consumption fee required for the setup before execution of the manufacturing order to be processed. Then, in consideration of the calculation result, it is possible to determine a production facility that distributes a production order to be processed.

As described above, according to the present embodiment, it is possible to determine a manufacturing facility suitable for execution of a manufacturing order to be processed in consideration of a relationship between manufacturing orders whose order of execution varies. As a result, it is possible to generate a production schedule that is truly advantageous in terms of working hours, power consumption, or power consumption charges.

In addition, according to the present embodiment, the estimated work time and the estimated power consumption required for the setup before the execution of the manufacturing order to be processed based on the relationship between the material, resin, color, etc. At least one of the quantity and the predicted electricity usage charge can be calculated. For this reason, the accuracy of the prediction can be increased.

Further, according to the present embodiment, a plurality of manufacturing orders are extracted in a predetermined order, processed in this order, and distributed to each manufacturing facility. Then, the order assigned to each manufacturing facility is set as the execution order in which the manufacturing order assigned to each manufacturing facility is executed in each manufacturing facility.

For this reason, when a manufacturing order to be processed is allocated to any of a plurality of manufacturing facilities, the manufacturing order to be executed immediately before the manufacturing order is allocated to each manufacturing facility is fixed. For this reason, it is possible to calculate, for each manufacturing facility, a measurement work time, a predicted power consumption amount, a predicted power consumption fee, and the like required for setup before execution of a manufacturing order to be processed by simple calculation and processing.

Further, according to the present embodiment, the extraction unit 11 can extract the production orders in a desired extraction order. And the production | generation part 12 incorporates a manufacturing order in the schedule of the day in the order extracted. That is, the previously extracted production order is preferentially incorporated into the schedule of the day.

For example, the extraction unit 11 can sequentially extract (A) a production order with a short delivery date. In this case, a production order with a close delivery date is preferentially incorporated into the schedule of the day, and a production schedule that tends to be executed earlier is generated. As a result, inconveniences such as delayed delivery can be reduced.

As another example, the extraction unit 11 can sequentially extract (B) from a production order with a large production quantity. In this case, the production schedule is incorporated in order from the production order with the largest production quantity. Production orders with a large production quantity tend to be incorporated in the early hours of the day, and production orders with a small production quantity tend to be incorporated into the later hours of the day, or remain in the schedule for the day. Become.

By the way, a production order with a small production quantity is relatively easy to adapt flexibly (schedule adjustment), such as being incorporated in the gap time, and is therefore easy to use in adjusting the production schedule after completion. In this example, production orders with a small production quantity tend to be included in the later hours of the day, so the impact of changing the schedule of a completed production order (the schedule after the changed production order) should be reduced. Can do. In addition, since it is easy to leave a manufacturing order that can easily be put into the gap time, it is easy to make fine adjustments such as putting a predetermined manufacturing order in the gap time without changing the schedule of the manufacturing order already incorporated in the finished manufacturing schedule. .

As another example, the extraction unit 11 can sequentially extract from (C) a production order with a high priority specified by the user. In this case, a production order having a high priority is preferentially incorporated in the schedule of the day, and a production schedule that tends to be executed earlier is generated. As a result, it is possible to preferentially execute a production order having a high priority.

As another example, the extraction unit 11 can sequentially extract from (D) a production order designated by the user to be executed on the day. In this case, the production order designated to be executed on the current day by the user is preferentially incorporated in the schedule for the current day, and a production schedule that tends to be executed earlier is generated. As a result, such a production order can be executed with priority.

As another example, the extraction unit 11 can perform extraction so that (E) production orders using the same resin are continuous. In this case, it becomes easy to generate a production schedule for continuously executing production orders using the same resin. As a result, it is possible to reduce the trouble of setup between production orders.

As another example, the extraction unit 11 can extract (F) a plastic molded product in order of darkness or lightness. In this case, a production schedule for executing the production order tends to be generated in the order of darkness or lightness of the plastic molded product. When the color of the order product of the manufacturing order whose execution order is different is greatly different, the color used when executing the previous manufacturing order is likely to affect the execution of the subsequent manufacturing order. For this reason, in the setup before performing the subsequent manufacturing order, the labor is increased such as careful cleaning. If the production orders are arranged in the order of darkness or thinness of the color of the plastic molded product as in this example, it is possible to reduce the inconvenience that the difference in the color of the order products in the production order whose execution order is before and after increases. As a result, it is possible to reduce the trouble of setup between production orders.

<Second Embodiment>
A functional block diagram of the schedule management apparatus 10 of the present embodiment is shown in FIG. 2 as in the first embodiment.

In the first embodiment, the extraction unit 11 determines one manufacturing order to be extracted from a plurality of manufacturing orders for each process of extracting one manufacturing order, and extracts the determined manufacturing order. In the present embodiment, the extraction unit 11 determines the extraction order for a plurality of manufacturing orders in advance. Then, one production order is extracted according to the determined extraction order. The other configuration of the extraction unit 11 and the configuration of the generation unit 12 are the same as those in the first embodiment.

FIG. 16 is a flowchart showing an example of the flow of processing by the schedule management device 10 of the present embodiment. Compared with the flowchart of FIG. 9 described in the first embodiment, after the schedule management apparatus 10 acquires information on a plurality of manufacturing orders to be scheduled in S20 (S10 and S20), the extraction unit 11 has a plurality of manufacturing orders. Whether or not to include the process of determining the extraction order (S21) and whether or not to extract according to the predetermined extraction order when extracting one manufacturing order (S11 and S22) Different. Other processing is the same.

According to the present embodiment, it is possible to realize the same operational effects as those of the first embodiment.

<Third Embodiment>
A functional block diagram of the schedule management apparatus 10 of the present embodiment is shown in FIG. 2 as in the first and second embodiments.

The generation unit 12 according to the present embodiment determines a manufacturing facility to which a processing target manufacturing order is allocated based on a predicted power consumption rate, and a prediction start time and a prediction end time when the processing target manufacturing order is executed. Is calculated for each manufacturing facility. Then, in consideration of the power unit price that differs for each time zone, the predicted power consumption required for execution of the manufacturing order to be processed and the setup before execution of the manufacturing order is calculated for each manufacturing facility. And the production | generation part 12 determines one manufacturing equipment which distributes the manufacturing order of a process target based on the calculated estimated electric power usage charge.

First, a process in which the generation unit 12 calculates a prediction start time and a prediction end time for each manufacturing facility when the manufacturing order to be processed is executed will be described.

As described in the first embodiment, the generation unit 12 can calculate the predicted work time required for executing the manufacturing order to be processed for each manufacturing facility. Moreover, the production | generation part 12 can calculate the estimated operation | work time required for the setup before performing the manufacturing order of a process target for every manufacturing equipment. And the production | generation part 12 makes the order allocated to each manufacturing equipment the execution order which performs the manufacturing order allocated to each manufacturing equipment in each manufacturing equipment.

For this reason, the generation unit 12 performs a predetermined work for each calculated predicted work time in the order in which the production orders and setups assigned to the respective manufacturing equipments before the processing of the manufacturing order to be processed are assigned to the respective manufacturing equipments. By continuously assigning sequentially from the start time (example: 8 o'clock), a production schedule based on the production orders processed so far can be generated (eg, see FIGS. 11 and 13). And the production | generation part 12 produces | generates the manufacturing schedule (for example: refer FIG. 11, FIG. 13) produced | generated in this way, the estimated work time required for execution of the manufacturing order of the process target calculated for every manufacturing equipment, and manufacturing Based on the estimated work time required for setup before execution of the processing target manufacturing order calculated for each equipment, the setup start time and forecast end time, and the manufacturing order when the processing target manufacturing order is executed at each manufacturing equipment The prediction start time and the prediction end time can be calculated.

For example, it is assumed that the manufacturing schedule determined before the processing of the manufacturing order to be processed is in the state shown in FIG. 11, and the processing target is the manufacturing order ID “10001”. Then, it is assumed that setup is required before the manufacturing facility 1, and this predicted work time is calculated as 2 hours. Further, it is assumed that the estimated work time of the manufacturing order at the manufacturing facility 1 is calculated as 4 hours. In this case, the predicted start time of setup at the manufacturing facility 1 is 11:00, and the predicted end time is 13:00. The predicted start time of execution of the manufacturing order at the manufacturing facility 1 is 13:00, and the predicted end time is 17:00.

On the other hand, no setup is required before the production facility 2. Then, it is assumed that the predicted work time of the manufacturing order at the manufacturing facility 2 is calculated as 7 hours. In this case, the predicted start time of execution of the manufacturing order in the manufacturing facility 2 is 8:00, and the predicted end time is 15:00.

Next, the calculation process of the predicted electric power charge considering the electric power unit price that is different for each time zone will be described.

The generation unit 12 holds information indicating the power unit price for each time zone as shown in FIG. And the production | generation part 12 calculates an estimated electric power charge for every manufacturing equipment using the said information. Hereinafter, a specific example will be described in which a predicted electric power charge for a certain manufacturing facility is calculated in consideration of a different power unit price for each time zone.

For example, when the manufacturing order to be processed is executed at the manufacturing facility 1, the predicted power consumption required for setup is A (kwh), the predicted work time is 2 hours, the predicted start time is 11:00, and the predicted end time is 13:00. Suppose there was. In addition, when the production order to be processed is executed at the production facility 1, the predicted electric power consumption required is A ′ (kwh), the predicted work time is 4 hours, the predicted start time is 13:00, and the predicted end time is 17:00. Suppose there was.

First, the process for calculating the predicted power consumption required for setup will be described. For example, the generation unit 12 apportions the predicted power consumption required for setup by the predicted work time. As a result, the predicted power consumption per unit time is calculated. For example, by dividing the predicted power consumption A (kwh) by the predicted work time of 2 hours, the predicted power consumption per unit time is calculated as A / 2 (kwh). That is, the predicted power consumption from 11:00 to 12:00 is calculated as A / 2 (kwh), and the predicted power consumption from 12:00 to 13:00 is calculated as A / 2 (kwh).

From FIG. 15, the power unit price is Y2 (yen / kwh) in any time zone from 11:00 to 12:00 and from 12:00 to 13:00. Therefore, the predicted power usage fee for each time zone is calculated as (A / 2) × Y2 (yen). And these are totaled and the prediction electric power charge AxY2 (yen) required for setup is calculated.

Next, a process for calculating a predicted electric power charge required for executing the manufacturing order to be processed will be described. For example, the generation unit 12 apportions the predicted power consumption required for execution of the manufacturing order by the predicted work time. As a result, the predicted power consumption per unit time is calculated. For example, by dividing the predicted power consumption A ′ (kwh) between the predicted work times 4, the predicted power consumption per unit time is calculated as A ′ / 4 (kwh). That is, the predicted power consumption from 13:00 to 14:00 is A ′ / 4 (kwh), the predicted power consumption from 14:00 to 15:00 is A ′ / 4 (kwh), and the predicted power consumption from 15:00 to 16:00 Is A ′ / 4 (kwh), and the predicted power consumption from 16:00 to 17:00 is calculated as A ′ / 4 (kwh).

From FIG. 15, the unit price of power during the time period from 13:00 to 14:00 and from 14:00 to 15:00 is Y2 (yen / kwh). Therefore, the predicted power usage fee for each time zone is calculated as (A ′ / 4) × Y2 (yen). On the other hand, the power unit price in the time zone from 15:00 to 16:00 and from 16:00 to 17:00 is Y3 (yen / kwh). Therefore, the predicted power usage fee for each time zone is calculated as (A ′ / 4) × Y3 (yen). And these are totaled and the prediction electric power charge (A '/ 2) xY2 + (A' / 2) xY3 (yen) required for execution of the production order is calculated.

As a modified example, the following process may be executed instead of the process of apportioning the predicted power consumption required for execution of the manufacturing order by the predicted work time.

First, as past track record of production orders, data (example: FIG. 17) indicating the transition (time change) of power consumption (w) during each past production order is stored. The data in FIG. 17 shows a transition pattern of power consumption from the start timing to the end timing of the production order.

And the production | generation part 12 extracts the results of one or several past manufacturing orders for every manufacturing equipment with the method demonstrated in 1st Embodiment.

When the generation unit 12 extracts the results of one past manufacturing order, the generation unit 12 adopts the pattern of transition (time change) of the power used (w) at the time of execution of the manufacturing order as it is and when the manufacturing order to be processed is executed. The transition of the power consumption (w) in (the time change within the predicted work time) is calculated. In other words, a pattern similar to the adopted pattern is applied to create data (e.g., FIG. 18) of power usage transition from the prediction start time to the prediction end time. And the production | generation part 12 calculates the prediction electric power consumption in each unit time slot | zone based on the said data.

On the other hand, when the generation unit 12 extracts the results of a plurality of past production orders, for example, the average of the transition pattern (time change) of the power used (w) during each of the plurality of production orders is processed. This is adopted as the transition (time change) of power consumption (w) during the execution of the manufacturing order. Then, the same processing as described above is performed.

In this way, the generation unit 12 executes the production order for each manufacturing facility in consideration of the unit price of power that differs for each time zone, the manufacturing order that differs for each manufacturing facility, and the predicted start time and predicted end time of the setup. In addition, it is possible to calculate a predicted electric power charge required for setup. Then, the manufacturing order to be processed can be allocated to a manufacturing facility that has the smallest total estimated power consumption required for execution and setup of the manufacturing order.

According to the present embodiment described above, the same operational effects as those of the first and second embodiments can be realized.

In addition, according to the present embodiment, the generation unit 12 takes into account the unit price of power that is different for each time zone, the production order that is different for each production facility, and the predicted start time and the predicted end time of the setup for each production facility. In addition, the predicted electric power charge can be calculated. Then, the production order to be processed can be allocated to the production facility with the lowest estimated power usage fee. According to the present embodiment as described above, the manufacturing schedule can be generated by distributing the manufacturing order to the manufacturing facility where the total of the predicted power consumption required for executing and setting up the manufacturing order is truly reduced.

In the present embodiment, the generation unit 12 calculates the predicted power consumption for each hour, and calculates the predicted power consumption fee based on the calculation result. However, other unit times (for example, every 30 minutes, 2 You may calculate the prediction electric energy consumption for every time).

<Fourth Embodiment>
The schedule management apparatus 10 of the present embodiment has a function of analyzing the generated manufacturing schedule and outputting the analysis result.

FIG. 19 shows an example of a functional block diagram of the schedule management apparatus 10 of the present embodiment. As illustrated, the schedule management device 10 includes an extraction unit 11, a generation unit 12, and an analysis unit 14. The configurations of the extraction unit 11 and the generation unit 12 are the same as those in the first to third embodiments.

The analysis unit 14 analyzes the production schedule generated by the generation unit 12, and is a time zone in which the total predicted power consumption at a plurality of manufacturing facilities exceeds a predetermined value, and the total predicted power consumption exceeds a predetermined value. Extract timing and output extraction results.

As described in the first to third embodiments, the generation unit 12 can generate a manufacturing schedule as shown in FIG. In the manufacturing schedule, the start time and end time of each production order and the start time and end time of each setup are determined.

Further, as described in the third embodiment, the generation unit 12 can calculate the predicted power consumption for each unit time (eg, 30 minutes, 1 hour, 2 hours) in the execution and setup of the manufacturing order. .

The analysis unit 14 adds the predicted power consumption of each of the plurality of manufacturing facilities in the same time zone (for example, from 13:00 to 14:00), thereby summing the predicted power consumption of the plurality of manufacturing facilities in the time zone. Can be calculated. Then, by comparing the calculated total with a predetermined value, it is possible to determine whether or not the total of the predicted power consumption at the plurality of manufacturing facilities in the time period exceeds the predetermined value.

When the analysis unit 14 extracts a time zone (for example, from 13:00 to 14:00, from 16:00 to 17:00) in which the total amount of predicted power consumption in a plurality of manufacturing facilities exceeds a predetermined value, information indicating the time zone is obtained. Can be output to an operator or another administrator. As the output means, means such as a display, a printer, and mail can be considered, but the output means is not limited thereto.

Also, as described in the third embodiment, the generation unit 12 can create prediction data (see FIG. 18) of the transition of power usage from the start time to the end time at the time of manufacturing order execution. By connecting the prediction data in order of time for each manufacturing facility, the prediction data of the transition of the power consumption of each manufacturing facility on the schedule date is completed. Based on the prediction data, the analysis unit 14 can extract a timing at which the total predicted power consumption exceeds a predetermined value. And the analysis part 14 can output the information which shows the extracted timing (time) toward an operator, another administrator, etc.

According to the present embodiment described above, the same operational effects as those of the first to third embodiments can be realized.

In addition, according to the present embodiment, based on the created manufacturing schedule, a time zone in which the power consumption may be excessive and a timing in which the power consumption may be excessive are extracted and notified to the operator. be able to. Based on the notification, the operator should not use other devices very often during the time when there is a possibility that the manufacturing schedule will be corrected, the power consumption may be excessive, or the power consumption may be excessive. It is possible to make power saving efforts such as.

<Fifth Embodiment>
The schedule management apparatus 10 according to the present embodiment distributes a plurality of manufacturing orders to a plurality of manufacturing facilities, and generates a manufacturing schedule that defines the execution order of the manufacturing orders in each of the manufacturing facilities.

An example of a functional block diagram of the schedule management apparatus 10 is shown in FIG.

The extraction unit 11 extracts one manufacturing order in order from a plurality of manufacturing orders. The configuration of the extraction unit 11 is the same as in the first to fourth embodiments.

The generation unit 12 (1) ′ processes the manufacturing orders in the order extracted by the extraction unit 11, distributes the manufacturing orders to be processed to one manufacturing facility, and (2) ′ distributes to each manufacturing facility. A process for generating a production schedule by setting the execution start time and the execution end time for each production order is executed. Since these processes have been described in the first to fourth embodiments, description thereof is omitted here.

And the production | generation part 12 calculates the prediction start time and prediction end time in the case of performing the manufacturing order of a process target for every manufacturing equipment in the process of (1) '. After that, the generation unit 12 calculates a predicted power usage fee required for executing the manufacturing order to be processed in consideration of a power unit price that is different for each time zone. And the production | generation part 12 determines one manufacturing equipment which distributes the manufacturing order of a process target based on an estimated electric power usage charge. That is, the production | generation part 12 distributes the manufacturing order of a process target to the manufacturing equipment with the least estimated electric power charge.

The generation unit 12 of the schedule management apparatus 10 of the present embodiment differs from the generation unit 12 of the schedule management apparatus 10 of the third embodiment in the following points.

The generation unit 12 according to the third embodiment considers the unit price of power that varies for each time zone, the production order that differs for each production facility, and the predicted start time and the end time of setup for each production facility. Calculate the predicted electricity usage fee required for execution and setup. Then, the manufacturing order to be processed is distributed to the manufacturing facility that has the smallest total estimated power consumption required for execution and setup of the manufacturing order.

On the other hand, the generation unit 12 of the present embodiment does not consider the predicted power usage fee required for setup. That is, the generation unit 12 according to the present embodiment executes the production order for each manufacturing facility in consideration of the power unit price that is different for each time zone and the prediction start time and prediction end time of the production order that is different for each manufacturing facility. Calculate the estimated power consumption required for Then, the manufacturing order to be processed is distributed to the manufacturing facility that has the smallest total estimated electric power consumption required to execute the manufacturing order.

Other points of the generation unit 12 of this embodiment are the same as those of the first to fourth embodiments.

Note that the schedule management device 10 of this embodiment may further include the analysis unit 14 described in the fourth embodiment. Since the structure of the analysis part 14 is the same as that of 4th Embodiment, description here is abbreviate | omitted.

According to the present embodiment, it is possible to generate a production schedule by allocating a production order to a production facility where the predicted power consumption required for executing the production order is truly reduced.

Hereinafter, examples of the reference form will be added.
1. A schedule management device that distributes a plurality of manufacturing orders to a plurality of manufacturing facilities and generates a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities,
Extraction means for extracting one of the production orders in order from a plurality of the production orders;
(1) The manufacturing order is a processing target in the order extracted by the extraction means, the processing order to be processed is distributed to one manufacturing facility, and (2) the order of distribution to each manufacturing facility is Generating means for executing the process of generating the manufacturing schedule as an execution order;
Have
In the process of (1), the generation unit calculates at least one of a predicted work time, a predicted power consumption amount, and a predicted power consumption fee required for executing the manufacturing order to be processed for each manufacturing facility. In addition, based on the relationship between the manufacturing order to be processed and the manufacturing order most recently assigned to each of the manufacturing facilities, the estimated work time required for the setup before executing the manufacturing order to be processed, the predicted use Calculate at least one of the electric power amount and the predicted electric power usage fee for each manufacturing facility, and execute the manufacturing order to be processed and the total predicted work time required for the setup before the manufacturing order is executed, the prediction A schedule management apparatus that determines one manufacturing facility that distributes the manufacturing order to be processed based on a power consumption amount or a predicted power consumption fee.
2. In the schedule management apparatus according to 1,
In the process of (1), the generation unit is configured to calculate a predicted work time required for the setup based on a relationship of materials used in the manufacturing orders that are allocated to the manufacturing order and the manufacturing equipment that are most recently distributed. A schedule management device that calculates at least one of the predicted power consumption and the predicted power charge for each manufacturing facility.
3. In the schedule management apparatus according to 1 or 2,
In the processing of (1), when determining the one manufacturing facility that distributes the manufacturing order to be processed based on the predicted power consumption rate,
The generating means includes
In the process (2), an execution start time and an execution end time for each of the manufacturing orders are further determined,
In the process of (1), the process calculates the predicted start time and predicted end time when executing the manufacturing order to be processed for each manufacturing facility, and considers the power unit price that differs for each time zone. A schedule management device that calculates a predicted power usage fee required for execution of the target manufacturing order and setup before execution of the manufacturing order.
4). In the schedule management device according to any one of 1 to 3,
The extraction means includes the manufacturing orders in the order determined based on at least one of the delivery date of each of the manufacturing orders, the manufacturing quantity of each of the manufacturing orders, and the priority of each of the manufacturing orders specified by the user. A schedule management device that extracts data.
5. In the schedule management device according to 4,
The said extraction means is a schedule management apparatus which extracts the said manufacturing order in the order determined based on at least one of the following conditions (A) thru | or (D).
(A) Extraction is performed in order from the manufacturing order with the closest delivery date.
(B) Extract in order from the production order with the largest production quantity.
(C) Extraction is performed in order from the manufacturing order with the highest priority specified by the user.
(D) Extraction is sequentially performed from the manufacturing order designated to be executed on the current day by the user.
6). In the schedule management device according to any one of 1 to 3,
The production order relates to a plastic molded product,
The extraction means includes a delivery date for each production order, a production quantity for each production order, a priority for each production order specified by a user, a type of resin used in the production order, and a color of the plastic molded product. A schedule management apparatus that extracts the manufacturing orders in an order determined based on at least one of the manufacturing orders.
7). In the schedule management device according to 6,
The said extraction means is a schedule management apparatus which extracts the said manufacturing order in the order determined based on at least one of the following conditions (A) thru | or (F).
(A) Extraction is performed in order from the manufacturing order with the closest delivery date.
(B) Extract in order from the production order with the largest production quantity.
(C) Extraction is performed in order from the manufacturing order with the highest priority specified by the user.
(D) Extraction is sequentially performed from the manufacturing order designated to be executed on the current day by the user.
(E) Extraction is performed so that the production orders using the same resin are continuous.
(F) Extraction in the order of darkness or lightness of the plastic molded product.
8). In the schedule management device according to any one of 1 to 7,
The generating means further determines an execution start time and an execution end time of each of the manufacturing orders in the process of (2),
Analyzing the manufacturing schedule generated by the generating means, and extracting a time zone in which the total predicted power consumption at the plurality of manufacturing facilities exceeds a predetermined value, and a timing at which the total predicted power consumption exceeds a predetermined value And a schedule management device further comprising analysis means for outputting the extraction result.
9. The computer distributes a plurality of manufacturing orders to a plurality of manufacturing facilities, and generates a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities.
The computer is
An extraction step of extracting one of the production orders in order from the plurality of the production orders;
(1) The manufacturing order is processed in the order extracted in the extraction step, the manufacturing order to be processed is distributed to one manufacturing facility, and (2) the order of distribution to each manufacturing facility is A generation step of executing the process of generating the manufacturing schedule as an execution order;
Run
In the generating step, in the process of (1), at least one of a predicted work time, a predicted power consumption amount and a predicted power consumption fee required for executing the manufacturing order to be processed is calculated for each manufacturing facility. In addition, based on the relationship between the manufacturing order to be processed and the manufacturing order most recently assigned to each of the manufacturing facilities, the estimated work time required for the setup before executing the manufacturing order to be processed, the predicted use Calculate at least one of the electric power amount and the predicted electric power usage fee for each manufacturing facility, and execute the manufacturing order to be processed and the total predicted work time required for the setup before the manufacturing order is executed, the prediction A schedule management method for determining one manufacturing facility that distributes the manufacturing order to be processed based on a power consumption amount or a predicted power consumption fee.
9-2. 9. In the schedule management method according to 9,
In the generating step, in the process of (1), the estimated work time required for the setup based on the relationship between the materials used in the manufacturing order and the manufacturing order most recently distributed to the manufacturing equipment to be processed. A schedule management method for calculating at least one of the predicted power consumption and the predicted power charge for each manufacturing facility.
9-3. In the schedule management method according to 9 or 9-2,
In the processing of (1), when determining the one manufacturing facility that distributes the manufacturing order to be processed based on the predicted power consumption rate,
In the generating step,
In the process (2), an execution start time and an execution end time for each of the manufacturing orders are further determined,
In the process of (1), the process calculates the predicted start time and predicted end time when executing the manufacturing order to be processed for each manufacturing facility, and considers the power unit price that differs for each time zone. A schedule management method for calculating a predicted electric power charge required for execution of the target manufacturing order and setup before execution of the manufacturing order.
9-4. In the schedule management method according to any one of 9 to 9-3,
In the extraction step, the manufacturing orders are in the order determined based on at least one of the delivery date of each of the manufacturing orders, the manufacturing quantity of each of the manufacturing orders, and the priority of each of the manufacturing orders specified by the user. A schedule management method for extracting files.
9-5. In the schedule management method described in 9-4,
In the extraction step, a schedule management method for extracting the manufacturing orders in an order determined based on at least one of the following conditions (A) to (D).
(A) Extraction is performed in order from the manufacturing order with the closest delivery date.
(B) Extract in order from the production order with the largest production quantity.
(C) Extraction is performed in order from the manufacturing order with the highest priority specified by the user.
(D) Extraction is sequentially performed from the manufacturing order designated to be executed on the current day by the user.
9-6. In the schedule management method according to any one of 9 to 9-3,
The production order relates to a plastic molded product,
In the extraction step, the delivery date of each manufacturing order, the manufacturing quantity of each manufacturing order, the priority of each manufacturing order specified by the user, the type of resin used in the manufacturing order, and the color of the plastic molded product A schedule management method for extracting the manufacturing orders in an order determined based on at least one of them.
9-7. In the schedule management method described in 9-6,
In the extraction step, a schedule management method for extracting the manufacturing orders in an order determined based on at least one of the following conditions (A) to (F).
(A) Extraction is performed in order from the manufacturing order with the closest delivery date.
(B) Extract in order from the production order with the largest production quantity.
(C) Extraction is performed in order from the manufacturing order with the highest priority specified by the user.
(D) Extraction is sequentially performed from the manufacturing order designated to be executed on the current day by the user.
(E) Extraction is performed so that the production orders using the same resin are continuous.
(F) Extraction in the order of darkness or lightness of the plastic molded product.
9-8. In the schedule management method according to any one of 9 to 9-7,
In the generating step, in the process of (2), an execution start time and an execution end time of each of the manufacturing orders are further determined,
The computer analyzes the manufacturing schedule generated in the generating step, and the time period in which the total predicted power consumption at the plurality of manufacturing facilities exceeds a predetermined value, and the total predicted power consumption reaches a predetermined value. A schedule management method for further executing an analysis step of extracting the timing exceeding and outputting the extraction result.
10. A program for causing a computer to distribute a plurality of manufacturing orders to a plurality of manufacturing facilities and to generate a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities,
The computer,
Extraction means for extracting one of the manufacturing orders in order from a plurality of the manufacturing orders;
(1) The manufacturing order is a processing target in the order extracted by the extraction means, the processing order to be processed is distributed to one manufacturing facility, and (2) the order of distribution to each manufacturing facility is Generating means for executing the process of generating the manufacturing schedule as an execution order;
Function as
In the process of (1), the generation unit is configured to calculate at least one of the predicted work time, the predicted power consumption, and the predicted power consumption required for executing the manufacturing order to be processed for each manufacturing facility. In addition, based on the relationship between the manufacturing order to be processed and the manufacturing order most recently assigned to each of the manufacturing facilities, the estimated work time required for the setup before executing the manufacturing order to be processed, the predicted use Calculate at least one of the electric power amount and the predicted power usage fee for each manufacturing facility, and execute the manufacturing order to be processed and the total estimated work time and the prediction required for the setup before the execution of the manufacturing order A program for determining one manufacturing facility for distributing the manufacturing order to be processed based on a power consumption amount or a predicted power consumption fee.
10-2. In the program described in 10,
In the process of (1), the generation means estimates the estimated work time required for the setup based on the relationship of the materials used in each of the manufacturing orders most recently assigned to the manufacturing order and the manufacturing equipment to be processed. A program for calculating at least one of the predicted power consumption and the predicted power charge for each manufacturing facility.
10-3. In the program described in 10 or 10-2,
In the processing of (1), when determining the one manufacturing facility that distributes the manufacturing order to be processed based on the predicted power consumption rate,
In the generating means,
In the process (2), the execution start time and the execution end time of each of the manufacturing orders are further determined.
In the process of (1), the process calculates the predicted start time and predicted end time when executing the manufacturing order to be processed for each manufacturing facility, and considers the power unit price that differs for each time zone. A program for calculating a predicted electric power charge required for execution of the target manufacturing order and setup before execution of the manufacturing order.
10-4. In the program according to any one of 10 to 10-3,
In the extraction means, the manufacturing orders are in the order determined based on at least one of the delivery date of each of the manufacturing orders, the manufacturing quantity of each of the manufacturing orders, and the priority of each of the manufacturing orders specified by the user. A program to extract
10-5. In the program described in 10-4,
A program for causing the extraction means to extract the manufacturing orders in an order determined based on at least one of the following conditions (A) to (D).
(A) Extraction is performed in order from the manufacturing order with the closest delivery date.
(B) Extract in order from the production order with the largest production quantity.
(C) Extraction is performed in order from the manufacturing order with the highest priority specified by the user.
(D) Extraction is sequentially performed from the manufacturing order designated to be executed on the current day by the user.
10-6. In the program according to any one of 10 to 10-3,
The production order relates to a plastic molded product,
The extraction means includes the delivery date of each manufacturing order, the manufacturing quantity of each manufacturing order, the priority of each manufacturing order specified by the user, the type of resin used in the manufacturing order, and the color of the plastic molded product. A program for extracting the manufacturing orders in an order determined based on at least one of them.
10-7. In the program described in 10-6,
A program for causing the extraction means to extract the manufacturing orders in an order determined based on at least one of the following conditions (A) to (F).
(A) Extraction is performed in order from the manufacturing order with the closest delivery date.
(B) Extract in order from the production order with the largest production quantity.
(C) Extraction is performed in order from the manufacturing order with the highest priority specified by the user.
(D) Extraction is sequentially performed from the manufacturing order designated to be executed on the current day by the user.
(E) Extraction is performed so that the production orders using the same resin are continuous.
(F) Extraction in the order of darkness or lightness of the plastic molded product.
10-8. In the program according to any one of 10 to 10-7,
In the process of (2), the generating unit further determines an execution start time and an execution end time for each of the manufacturing orders.
The computer further analyzes the manufacturing schedule generated by the generating means, and a time zone in which the total of the predicted power consumption at the plurality of manufacturing facilities exceeds a predetermined value and a total of the predicted power consumption are predetermined. A program that functions as an analysis means for extracting timings that exceed values and outputting the extraction results.
11. A schedule management device that distributes a plurality of manufacturing orders to a plurality of manufacturing facilities and generates a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities,
Extraction means for extracting one of the production orders in order from a plurality of the production orders;
(1) ′ a process in which the manufacturing orders are processed in the order extracted by the extraction means, and the manufacturing order to be processed is allocated to one manufacturing facility; and (2) ′ the order allocated to each manufacturing facility. Generating means for generating the manufacturing schedule by setting the execution start time and the execution end time of each of the manufacturing orders,
Have
The generation unit calculates a prediction start time and a prediction end time when executing the manufacturing order to be processed in the processing of (1) ′ for each manufacturing facility, and a power unit price that is different for each time zone. In consideration of the above, schedule management for calculating a predicted power usage fee required to execute the manufacturing order to be processed and determining one manufacturing facility to which the manufacturing order to be processed is allocated based on the predicted power usage fee apparatus.
12 The computer distributes a plurality of manufacturing orders to a plurality of manufacturing facilities, and generates a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities.
The computer is
An extraction step of extracting one of the production orders in order from the plurality of the production orders;
(1) ′ a process in which the manufacturing orders are processed in the order extracted in the extraction step, and the manufacturing order to be processed is distributed to one of the manufacturing facilities; and (2) ′ the order of distribution to the manufacturing facilities. A process of generating the manufacturing schedule by setting the execution start time and the execution end time of each of the manufacturing orders,
Run
In the generation step, in the process of (1) ′, a prediction start time and a prediction end time when the manufacturing order to be processed is executed are calculated for each manufacturing facility, and the power unit price varies depending on the time zone. In consideration of the above, schedule management for calculating a predicted power usage fee required to execute the manufacturing order to be processed and determining one manufacturing facility to which the manufacturing order to be processed is allocated based on the predicted power usage fee Method.
13 A program for causing a computer to distribute a plurality of manufacturing orders to a plurality of manufacturing facilities and to generate a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities,
The computer,
Extraction means for extracting one of the manufacturing orders in order from the plurality of manufacturing orders;
(1) ′ a process in which the manufacturing orders are processed in the order extracted by the extraction means, and the manufacturing order to be processed is allocated to one manufacturing facility; and (2) ′ the order allocated to each manufacturing facility. Generating means for generating the manufacturing schedule by setting the execution start time and the execution end time of each of the manufacturing orders.
Function as
In the process of (1) ′, the generation unit calculates a predicted start time and a predicted end time when the manufacturing order to be processed is executed for each manufacturing facility, and a power unit price that is different for each time zone In consideration of the above, a program that calculates a predicted power usage fee required to execute the manufacturing order to be processed and determines one manufacturing facility that distributes the manufacturing order to be processed based on the predicted power usage fee.

This application claims priority based on Japanese Patent Application No. 2014-231914 filed on November 14, 2014, the entire disclosure of which is incorporated herein.

Claims

A schedule management device that distributes a plurality of manufacturing orders to a plurality of manufacturing facilities and generates a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities,
Extraction means for extracting one of the production orders in order from a plurality of the production orders;
(1) The manufacturing order is a processing target in the order extracted by the extraction means, the processing order to be processed is distributed to one manufacturing facility, and (2) the order of distribution to each manufacturing facility is Generating means for executing the process of generating the manufacturing schedule as an execution order;
Have
In the process of (1), the generation unit calculates at least one of a predicted work time, a predicted power consumption amount, and a predicted power consumption fee required for executing the manufacturing order to be processed for each manufacturing facility. In addition, based on the relationship between the manufacturing order to be processed and the manufacturing order most recently assigned to each of the manufacturing facilities, the estimated work time required for the setup before executing the manufacturing order to be processed, the predicted use Calculate at least one of the electric power amount and the predicted electric power usage fee for each manufacturing facility, and execute the manufacturing order to be processed and the total predicted work time required for the setup before the manufacturing order is executed, the prediction A schedule management apparatus that determines one manufacturing facility that distributes the manufacturing order to be processed based on a power consumption amount or a predicted power consumption fee.
The schedule management device according to claim 1,
In the process of (1), the generation unit is configured to calculate a predicted work time required for the setup based on a relationship of materials used in the manufacturing orders that are allocated to the manufacturing order and the manufacturing equipment that are most recently distributed. A schedule management device that calculates at least one of the predicted power consumption and the predicted power charge for each manufacturing facility.
In the schedule management apparatus according to claim 1 or 2,
In the processing of (1), when determining the one manufacturing facility that distributes the manufacturing order to be processed based on the predicted power consumption rate,
The generating means includes
In the process (2), an execution start time and an execution end time for each of the manufacturing orders are further determined,
In the process of (1), the process calculates the predicted start time and predicted end time when executing the manufacturing order to be processed for each manufacturing facility, and considers the power unit price that differs for each time zone. A schedule management device that calculates a predicted power usage fee required for execution of the target manufacturing order and setup before execution of the manufacturing order.
In the schedule management device according to any one of claims 1 to 3,
The extraction means includes the manufacturing orders in the order determined based on at least one of the delivery date of each of the manufacturing orders, the manufacturing quantity of each of the manufacturing orders, and the priority of each of the manufacturing orders specified by the user. A schedule management device that extracts data.
In the schedule management device according to claim 4,
The said extraction means is a schedule management apparatus which extracts the said manufacturing order in the order determined based on at least one of the following conditions (A) thru | or (D).
(A) Extraction is performed in order from the manufacturing order with the closest delivery date.
(B) Extract in order from the production order with the largest production quantity.
(C) Extraction is performed in order from the manufacturing order with the highest priority specified by the user.
(D) Extraction is sequentially performed from the manufacturing order designated to be executed on the current day by the user.
In the schedule management device according to any one of claims 1 to 3,
The production order relates to a plastic molded product,
The extraction means includes a delivery date for each production order, a production quantity for each production order, a priority for each production order specified by a user, a type of resin used in the production order, and a color of the plastic molded product. A schedule management apparatus that extracts the manufacturing orders in an order determined based on at least one of the manufacturing orders.
The schedule management device according to claim 6,
The said extraction means is a schedule management apparatus which extracts the said manufacturing order in the order determined based on at least one of the following conditions (A) thru | or (F).
(A) Extraction is performed in order from the manufacturing order with the closest delivery date.
(B) Extract in order from the production order with the largest production quantity.
(C) Extraction is performed in order from the manufacturing order with the highest priority specified by the user.
(D) Extraction is sequentially performed from the manufacturing order designated to be executed on the current day by the user.
(E) Extraction is performed so that the production orders using the same resin are continuous.
(F) Extraction in the order of darkness or lightness of the plastic molded product.
In the schedule management device according to any one of claims 1 to 7,
The generating means further determines an execution start time and an execution end time of each of the manufacturing orders in the process of (2),
Analyzing the manufacturing schedule generated by the generating means, and extracting a time zone in which the total predicted power consumption at the plurality of manufacturing facilities exceeds a predetermined value, and a timing at which the total predicted power consumption exceeds a predetermined value And a schedule management device further comprising analysis means for outputting the extraction result.
The computer distributes a plurality of manufacturing orders to a plurality of manufacturing facilities, and generates a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities.
The computer is
An extraction step of extracting one of the production orders in order from the plurality of the production orders;
(1) The manufacturing order is processed in the order extracted in the extraction step, the manufacturing order to be processed is distributed to one manufacturing facility, and (2) the order of distribution to each manufacturing facility is A generation step of executing the process of generating the manufacturing schedule as an execution order;
Run
In the generating step, in the process of (1), at least one of a predicted work time, a predicted power consumption amount and a predicted power consumption fee required for executing the manufacturing order to be processed is calculated for each manufacturing facility. In addition, based on the relationship between the manufacturing order to be processed and the manufacturing order most recently assigned to each of the manufacturing facilities, the estimated work time required for the setup before executing the manufacturing order to be processed, the predicted use Calculate at least one of the electric power amount and the predicted electric power usage fee for each manufacturing facility, and execute the manufacturing order to be processed and the total predicted work time required for the setup before the manufacturing order is executed, the prediction A schedule management method for determining one manufacturing facility that distributes the manufacturing order to be processed based on a power consumption amount or a predicted power consumption fee.
A program for causing a computer to distribute a plurality of manufacturing orders to a plurality of manufacturing facilities and to generate a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities,
The computer,
Extraction means for extracting one of the manufacturing orders in order from a plurality of the manufacturing orders;
(1) The manufacturing order is a processing target in the order extracted by the extraction means, the processing order to be processed is distributed to one manufacturing facility, and (2) the order of distribution to each manufacturing facility is Generating means for executing the process of generating the manufacturing schedule as an execution order;
Function as
In the process of (1), the generation unit is configured to calculate at least one of the predicted work time, the predicted power consumption, and the predicted power consumption required for executing the manufacturing order to be processed for each manufacturing facility. In addition, based on the relationship between the manufacturing order to be processed and the manufacturing order most recently assigned to each of the manufacturing facilities, the estimated work time required for the setup before executing the manufacturing order to be processed, the predicted use Calculate at least one of the electric power amount and the predicted power usage fee for each manufacturing facility, and execute the manufacturing order to be processed and the total estimated work time and the prediction required for the setup before the execution of the manufacturing order A program for determining one manufacturing facility for distributing the manufacturing order to be processed based on a power consumption amount or a predicted power consumption fee.
A schedule management device that distributes a plurality of manufacturing orders to a plurality of manufacturing facilities and generates a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities,
Extraction means for extracting one of the production orders in order from a plurality of the production orders;
(1) ′ a process in which the manufacturing orders are processed in the order extracted by the extraction means, and the manufacturing order to be processed is allocated to one manufacturing facility; and (2) ′ the order allocated to each manufacturing facility. Generating means for generating the manufacturing schedule by setting the execution start time and the execution end time of each of the manufacturing orders,
Have
The generation unit calculates a prediction start time and a prediction end time when executing the manufacturing order to be processed in the processing of (1) ′ for each manufacturing facility, and a power unit price that is different for each time zone. In consideration of the above, schedule management for calculating a predicted power usage fee required to execute the manufacturing order to be processed and determining one manufacturing facility to which the manufacturing order to be processed is allocated based on the predicted power usage fee apparatus.
The computer distributes a plurality of manufacturing orders to a plurality of manufacturing facilities, and generates a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities.
The computer is
An extraction step of extracting one of the production orders in order from the plurality of the production orders;
(1) ′ a process in which the manufacturing orders are processed in the order extracted in the extraction step, and the manufacturing order to be processed is distributed to one of the manufacturing facilities; and (2) ′ the order of distribution to the manufacturing facilities. A process of generating the manufacturing schedule by setting the execution start time and the execution end time of each of the manufacturing orders,
Run
In the generation step, in the process of (1) ′, a prediction start time and a prediction end time when the manufacturing order to be processed is executed are calculated for each manufacturing facility, and the power unit price varies depending on the time zone. In consideration of the above, schedule management for calculating a predicted power usage fee required to execute the manufacturing order to be processed and determining one manufacturing facility to which the manufacturing order to be processed is allocated based on the predicted power usage fee Method.
A program for causing a computer to distribute a plurality of manufacturing orders to a plurality of manufacturing facilities and to generate a manufacturing schedule that defines an execution order of the manufacturing orders in each of the manufacturing facilities,
The computer,
Extraction means for extracting one of the manufacturing orders in order from a plurality of the manufacturing orders;
(1) ′ a process in which the manufacturing orders are processed in the order extracted by the extraction means, and the manufacturing order to be processed is allocated to one manufacturing facility; and (2) ′ the order allocated to each manufacturing facility. Generating means for generating the manufacturing schedule by setting the execution start time and the execution end time of each of the manufacturing orders.
Function as
In the process of (1) ′, the generation unit calculates a predicted start time and a predicted end time when the manufacturing order to be processed is executed for each manufacturing facility, and a power unit price that is different for each time zone In consideration of the above, a program that calculates a predicted power usage fee required to execute the manufacturing order to be processed and determines one manufacturing facility that distributes the manufacturing order to be processed based on the predicted power usage fee.