JP5359311B2 - Workpiece manufacturing time prediction method, manufacturing date prediction method, arrival time prediction method, arrival date prediction method, workpiece manufacturing time prediction device, and arrival time prediction device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a manufacturing time prediction method of a work for highly precisely predicting the manufacturing time or arrival time of a work. <P>SOLUTION: The manufacturing time prediction method of a work includes: a required processing time obtaining step for obtaining an average required processing time including a non-processing time calculated from the processing history of each processor 2 since a work is faced to the processor 2 until the processing ends; and a predicted manufacturing time obtaining step for obtaining a cumulative value obtained by successively accumulating the average required processing time of each processor to which the work is faced after the current point of time as a predicted manufacturing time in the manufacturing process of the work. <P>COPYRIGHT: (C)2010,JPO&amp;INPIT

Description

  The present invention relates to a manufacturing time prediction method, a manufacturing date prediction method, and an arrival time of a work line for obtaining a predicted manufacturing time from the present time until the work is manufactured, on a manufacturing line that processes the work on a plurality of processing devices. The present invention relates to a prediction method, an arrival date prediction method, a workpiece manufacturing time prediction device, and an arrival time prediction device.

  2. Description of the Related Art Conventionally, as a manufacturing management system that performs manufacturing management of a manufacturing line, a system that creates a schedule and predicts the completion date of each work (lot) based on the progress status in the manufacturing line is known (Patent Document 1) reference).

JP-A-6-266413

By the way, when creating a schedule or predicting a completion date, it is necessary to accurately predict the manufacturing time until the workpiece is manufactured and the arrival time until the workpiece reaches the target process. As a method for predicting the manufacturing time and the arrival time, a method of predicting and calculating by accumulating the actual processing time per work of each processing apparatus can be considered.
However, in such a method, when the processing device is processing another workpiece or when the processing device is defective, if the workpiece has a waiting time, the manufacturing time and the arrival time are accurate. There was a problem that could not be predicted.

  The present invention relates to a workpiece manufacturing time prediction method, a manufacturing date prediction method, an arrival time prediction method, an arrival date prediction method, and a workpiece manufacturing time prediction apparatus and arrival capable of accurately predicting a workpiece manufacturing time or arrival time. It is an object to provide a time prediction device.

The workpiece manufacturing time prediction method of the present invention is a workpiece manufacturing time prediction method for obtaining an estimated manufacturing time from the current time until a workpiece is manufactured, on a manufacturing line in which the workpiece is processed with a plurality of processing devices. A required processing time acquisition step for acquiring an average required processing time including a non-processing time from the time when the workpiece is exposed to the processing device until the processing is completed, obtained from the processing history of each processing device; In the manufacturing process, an estimated manufacturing time acquisition step of acquiring, as predicted manufacturing time, a cumulative value obtained by sequentially accumulating the average required processing time of each processing apparatus that faces a workpiece after the present time, and weighting is given to processing history data It is characterized by being set .

  In this case, in the required processing time acquisition step, an actual processing time acquisition step for acquiring the average actual processing time of the processing device from the processing history, and an average with respect to the actual processing time in the work to be brought to the processing device from the processing history A processing magnification acquisition step for acquiring a processing magnification, and a value obtained by multiplying the average actual processing time and the average processing magnification is preferably acquired as the average required processing time.

The workpiece manufacturing time predicting apparatus according to the present invention is a workpiece manufacturing time predicting apparatus that acquires an estimated manufacturing time from the present time until a workpiece is manufactured, on a manufacturing line that processes the workpiece with a plurality of processing devices. The required processing time acquisition means for acquiring the average required processing time including the non-processing time from the time when the workpiece is exposed to the processing device until the processing is completed, obtained from the processing history of each processing device, In the manufacturing process, it is provided with predicted manufacturing time acquisition means for acquiring, as predicted manufacturing time, a cumulative value obtained by sequentially accumulating the average required processing time of each processing apparatus that faces a workpiece after the present time, and weight of processing history data is provided It is characterized by being set .

  According to these configurations, the average processing time including the non-processing time of each processing device is acquired from the processing history, and the average processing time of each processing device facing the workpiece after the current time is sequentially accumulated to predict manufacturing. Get time. Thereby, since the manufacturing time which considered the unexpected waiting time can be estimated, manufacturing time can be estimated accurately. In addition, since the average required processing time after the present time is accumulated, not only the manufacturing time for all the processes but also the manufacturing time required after a certain time can be appropriately acquired.

  In the workpiece manufacturing time prediction method described above, the processing history is preferably data of several months retroactive from the present time.

  According to this configuration, by obtaining the average required processing time from long-term data of several months, it is possible to reduce the error in the processing time required data.

  The workpiece manufacturing date and time prediction method of the present invention is characterized in that an estimated manufacturing date and time at which workpiece manufacturing is completed is acquired from the predicted manufacturing time acquired by the workpiece manufacturing time prediction method and the current date and time. .

  According to this configuration, the manufacturing date and time can be accurately predicted by predicting the predicted manufacturing date and time based on the prediction result of the manufacturing time prediction method capable of accurately predicting the manufacturing time. Instead of the production date and time, a production date and production time may be predicted.

The workpiece arrival time predicting method of the present invention is a workpiece arrival time predicting method for obtaining a predicted arrival time from the present time until the workpiece reaches the target process in a production line in which the workpiece is processed with a plurality of processing devices. A processing time acquisition step for acquiring an average processing time including a non-processing time from the time when the workpiece is exposed to the processing device until the processing is completed, obtained from the processing history of each processing device; In the manufacturing process, a predicted arrival time acquisition step for acquiring a cumulative value obtained by sequentially accumulating the average required processing time of each processing apparatus that allows a workpiece to face from the current time to the target process as a predicted arrival time, and a processing history A feature is that weights are set for the data .

The workpiece arrival time predicting apparatus according to the present invention is a workpiece arrival time predicting apparatus that acquires a predicted arrival time from the present time until the workpiece reaches a target process in a production line that processes the workpiece with a plurality of processing devices. And a required processing time acquisition means for acquiring an average required processing time including a non-processing time from when the workpiece is exposed to the processing device until the processing is completed, obtained from the processing history of each processing device, in the manufacturing process, the accumulated value of the average required processing times for each processing unit and accumulated in the order in which to face the workpiece from after the current time to the target process, and a predicted arrival time acquisition means for acquiring a predicted arrival time, processing history A feature is that weights are set for the data .

  According to these configurations, the average processing time including the non-processing time of each processing device is acquired from the processing history, and the average processing time of each processing device that causes the workpiece to face from the current time to the target process is accumulated in order. To obtain the predicted arrival time. Thereby, since the arrival time in consideration of the unexpected waiting time can be predicted, the arrival time can be predicted with high accuracy. In addition, since the average required processing time from the current time to the target process is accumulated, not only the arrival time from the start of manufacturing but also the arrival time from a certain time can be appropriately acquired.

  The workpiece arrival date and time prediction method of the present invention is characterized in that the predicted arrival date and time when the workpiece reaches the target process is obtained from the predicted arrival time obtained by the workpiece arrival time prediction method and the current date and time. To do.

  According to this configuration, the arrival date and time can be predicted with high accuracy by predicting the predicted arrival date and time based on the prediction result of the arrival time prediction method that can predict the arrival time with high accuracy. Instead of the arrival date and time, an arrival date and arrival time may be predicted.

It is a system configuration figure of a process management system concerning an embodiment. It is the figure which showed the process management screen.

  Hereinafter, a process management system for a production line to which a method for predicting a production time of a workpiece according to the present invention is applied will be described with reference to the accompanying drawings. This process management system implements process management for a production line that processes a plurality of lots (workpieces) to be processed in sequence, facing each processing device (each processing device group). For each lot on the line, process time is estimated by predicting the manufacturing time until it is manufactured. The lot is a set of a plurality of workpieces.

  As shown in FIG. 1, the process management system 1 includes a production line 3 composed of a plurality of processing devices 2, a plurality of information terminals 4 that manage information of one or more processing devices 2, and each information terminal 4. And a process management server (manufacturing time prediction device) 5 that connects and manages information of each information terminal 4. The connection between each information terminal 4 and the process management server 5 may be a wired LAN connection or a wireless LAN connection.

  The production line 3 includes a plurality of processing devices 2 that perform each process of the manufacturing line 3, and the plurality of processing devices 2 includes a plurality of processing devices including one or more processing devices 2 that perform a common process. A device group 6 is configured. Each processing device group 6 has a common storage section 7 (for example, a work stocker such as a storage shelf) that can store a plurality of lots before processing. The lots that are allowed to face the processing device group 6 from the previous process are once stored in the storage unit 7, and then transferred from the storage unit 7 to each processing device 2 to process the lots. The storage unit 7 also stores lots in a waiting state (lots exceeding the capacity (allowable number) that can be processed simultaneously). Further, a common storage unit 7 may be used in the plurality of processing device groups 6.

  The processing device 2 and the storage unit 7 are equipped with a lot recognition mechanism for recognizing and identifying the lot being processed and the stored lot. For example, the lot recognition mechanism includes a reading mechanism that reads an identifier such as a barcode provided in each lot, and acquires the identification number of each lot and the number of workpieces based on the read data of the identifier. As a result, the number of lots facing each processing device group 6, the identification number of each lot, and the number of workpieces are acquired.

  Each information terminal 4 is arranged for each process of the workpiece manufacturing process, and the processing apparatus group 6 that performs the corresponding process is used as the corresponding apparatus. Each information terminal 4 includes a connection unit 11 connected to each corresponding device (hereinafter referred to as a corresponding device group), a storage unit 12 that stores various types of information on the corresponding device group, and update information on the corresponding device group. And a communication unit 13 for receiving process management data from the process management server 5, a display unit 14 for displaying a process management screen (see FIG. 2) based on various input screens and process management data, and the like. And a control unit 15 for controlling.

  The storage unit 12 stores the identification code, operation status information, and lot information of the corresponding device group. The operating status information is data indicating the operating status of each corresponding device such as “processing in progress”, “standby”, and “functional recovery” at the present time. The lot information is data indicating the number of lots facing the corresponding device group, the identification number of each lot, status information (standby state: waiting, processing: running, etc.) and the number of workpieces. The control unit 15 acquires these pieces of information from the corresponding devices via the connection unit 11 and stores them in the storage unit 12. In the present embodiment, the control unit 15 is configured to automatically acquire such information from the corresponding device via the connection unit 11. However, the control unit 15 includes an input unit, and a person in charge of each processing device group 6 It is good also as a structure which inputs each said information.

  The communication unit 13 transmits the update information of the corresponding device group to the process management server 5 in a form synchronized with the operation of the device (in real time). Specifically, each time the operation status information and lot information are acquired, update information obtained by adding the identification code of the corresponding device group to these information is transmitted to the process management server 5. Further, the communication unit 13 receives updated process management data from the process management server 5.

  Next, the process management server 5 will be described. The process management server 5 includes an input unit 21, a display unit 22, a communication unit 23, and a control unit 24 for controlling them. The input means 21 is composed of a keyboard, a mouse, and the like, and is a means for inputting the delivery date, the target number, the delivery date for each lot, etc. of the entire production line 3 with the display means 22. The display means 22 displays various input screens and a process management screen based on process management data. The communication unit 23 receives update information of each corresponding device group from each information terminal 4 and transmits process management data to each information terminal 4.

  The control unit 24 includes a CPU (Central Processing Unit) 31, a ROM (Read Only Memory) 32, a RAM (Random Access Memory) 33, and a hard disk (HDD: Hard disk drive) 34. The CPU 31 is a central processing unit that controls the process management server 5. The ROM 32 stores a control program for the CPU 31 to perform various controls, and the RAM 33 is used as a work area. The hard disk 34 stores various data and various programs so that they can be rewritten. The control unit 24 executes various operations by the CPU 31 performing various arithmetic processes according to programs stored in the ROM 32 and the hard disk 34.

  Here, the process management data update operation and the process management screen based on the process management data will be described. FIG. 2 is a diagram showing a process management screen. The control means 24 receives update information transmitted from each information terminal 4 and acquires / updates process management data. Thereafter, the control means 24 transmits the updated process management data to each information terminal 4, and the display unit 14 of each information terminal 4 and the display means 22 of the management server display a process management screen based on this process management data. To do. Of the process management data, an average actual processing time and an average required processing time, which will be described later, and data using these are calculated and updated at a predetermined cycle (for example, every 15 minutes).

  The control means 24 includes, as process management data, line progress information 41 that is data on the progress of the entire production line 3, performance information 42 that is performance data for each day, and lot progress that is data on the progress status of each lot. Information 43 is updated. As shown in FIG. 2, each piece of information is displayed on the process management screen. As shown in FIG. 2, on the process management screen, in addition to the above-mentioned information, display selection for displaying only lots with specific conditions, such as those with late delivery date and those with today's delivery date, among the lot progress information 43 It is preferable to display the item 44.

  As the lot progress information 43, the control means 24 identifies, for each process of the production line 3, the identification code (MC1, MC2, etc.) of the corresponding processing device group 6, the operating status information of each processing device 2, the average actual value. Processing time (actual CT), average required processing time (CT * magnification), number of lots (number of lots), total number of workpieces (number of WF) and lot data are acquired and calculated.

  An identification code corresponding to each process is obtained by user input. That is, the control unit 24 requests the user to input an identification code by using the input unit 21 and the input screen, and acquires the identification code.

  The operation status information, the number of lots, and the total number of workpieces are acquired from the update information of each information terminal 4. That is, the control unit 24 obtains the operation status information and the lot number corresponding to the processing device group 6 of each process by referring to the identification code of the corresponding device group in each update information. Further, the control means 24 calculates the total number of workpieces by adding up the number of workpieces in the lot information in the update information.

  The average actual processing time and the average required processing time are calculated based on each processing history obtained from each update information. The processing history is a history for each processing device group 6, and the actual processing time and the lot corresponding to the actual processing time for each lot for the past several months are presented (stored in the storage unit 7). To) is the data consisting of the processing magnification until the processing is completed. That is, first, the control means 24 obtains a processing history (actual processing time and processing magnification for each lot) from update information for the past several months, and stores it in the hard disk 34. Next, from the processing history stored in the hard disk 34, the control unit 24 calculates the average actual processing time for the above several months over all the processing devices 2 in the processing device group 6 and the above several months for all the processing devices 2. The average machining magnification of minutes is calculated (actual processing time acquisition step and processing magnification acquisition step). Further, the control means 24 multiplies the average actual processing time and the average processing magnification to calculate an average required processing time from when the lot is exposed to the processing device group 6 until the processing of the lot is completed (required) Processing time acquisition step, required processing time acquisition means). That is, the average required processing time is a time including a non-processing time such as a waiting time.

  Here, the lot data will be described. As shown in FIG. 2, the lot data is data of each lot facing each processing device group 6, and 0 or 1 or more lot data is acquired for each process. The control means 24 acquires and calculates the identification number, status information, delivery date, required machining magnification, progress (difference between predicted date and time), and the number of workpieces as lot data.

  The lot identification number, the status information, and the number of workpieces are acquired from the lot information of each update information. That is, the control means 24 obtains the lot identification number, the state information, and the number of workpieces facing the processing device group 6 in each process by referring to the identification code of the corresponding device group in each update information. The delivery date of each lot indicates the completion instruction date of the lot and is acquired by user input. That is, the control unit 24 causes the user to input the delivery date of each lot using the input unit 21 and the input screen, and acquires the delivery date of each lot.

  The required processing magnification indicates the processing magnification required until the lot delivery date, and is acquired from the lot delivery date and the average actual processing time of each process. That is, the control means 24 sequentially accumulates the average actual processing time of each processing device group 6 (each process) that the lot faces after the current time in the work manufacturing process, and this accumulated value is used as the manufacturing time from the current time to the delivery date. To calculate the required processing magnification.

  The progress indicates the progress of the lot, and is the difference between the lot delivery date and the expected production date and time of the lot. That is, the control means 24 calculates the expected manufacturing time by sequentially accumulating the average required processing time of each processing device group 6 (each process) that the lot faces after the current time in the work manufacturing process (predicted manufacturing time acquisition step). , Predicted production time acquisition means). Thereafter, the estimated production date is calculated by adding the calculated expected production time to the acquired current date and time. Further, the progress is obtained by subtracting the expected production date from the delivery date.

  The control means 24 acquires / calculates the delivery date, the target number, the number of deliveries, the remaining number of sheets, the final lot process, the required processing magnification, the remaining number of days, and the remaining CT of the entire production line 3 as the line progress information 41.

  The delivery date of the entire production line 3 indicates the completion instruction date of the entire production line 3, and the target number indicates the planned quantity until the delivery date. The delivery date and target number are obtained by user input. That is, the control unit 24 causes the user to input the delivery date and the target number by using the input unit 21 and various input screens, and acquires the delivery date and the target number.

  The number of delivered items indicates the number of completed workpieces, and the remaining number indicates the remaining number of sheets with respect to the target number. The number of products to be sent and the remaining number are acquired from the update information of the processing device group 6 corresponding to the final process of the production line 3. That is, the control means 24 calculates the cumulative processing number of the processing device group 6 from the update information, and acquires this as the number of deliveries. Further, the remaining number is acquired by subtracting the number of products from the target number.

  The final lot process indicates the process that the final production lot reaches in the target number, and is acquired from the number of workpieces of the lot that faces the processing device group 6 in each process. That is, the control means 24 accumulates the number of workpieces of the lot facing the processing device group 6 in each process based on the lot progress information 43, and the process when the accumulated number of workpieces reaches the number of deliveries. Is acquired as the final lot process.

  The necessary processing magnification of the entire production line 3 indicates the processing magnification necessary for manufacturing the target number by the delivery date of the entire manufacturing line 3, and the remaining days indicate the remaining days until the delivery date. The remaining CT indicates the cumulative value of the average actual processing time (days) from the final lot process to the final process. The remaining days are acquired from the delivery date of the entire production line 3 and the current date (today). The remaining CT is acquired from the average actual processing time of each process in the lot progress information 43. The required processing magnification is calculated from the remaining number of days and the remaining CT. That is, the control unit 24 acquires the remaining number of days, and acquires the remaining CT from the lot progress information 43 by accumulating the average actual processing time after the final lot process. Further, the required machining magnification is calculated by dividing the remaining CT from the remaining number of days.

  The control means 24 acquires the planned number, actual number, and the difference between today and yesterday as the actual information 42. The planned number indicates the planned quantity to be completed on each date, and the actual number indicates the number of actually completed workpieces. The control means 24 inputs the number of plans by using the input means 21 and the input screen, and acquires the number of plans. Also, the number of processes for each date is calculated from the update information of the processing device group 6 corresponding to the final process, and this is acquired as the actual number of each date. Further, the difference is calculated by subtracting the planned number from the actual number.

  Next, a lot priority determination method in each processing apparatus group 6 will be described. In each processing device group 6, when a plurality of lots are waiting in the storage unit 7, the priority is judged, and the lot with the higher priority is given priority and is loaded into the processing device 2 to be processed. . In the priority determination method of this embodiment, the priority of each lot is determined based on the required processing magnification of each lot data in the process management data. That is, the processing device group 6 takes in the process management data and carries in processing by giving priority to a lot having a low required processing magnification. The person in charge of each processing device group 6 may determine the priority based on the required processing magnification, and the person in charge may manually carry in the lot according to the priority.

  According to the configuration as described above, the average processing time including the non-processing time of each processing device group 6 (processing device 2) is acquired from the processing history, and each processing device group facing the lot (work) after the present time. By accumulating the average required processing time of 6 (processing device 2) in order and obtaining the predicted manufacturing time, it is possible to predict the manufacturing time with an unexpected waiting time, so the manufacturing time is accurately predicted. be able to. In addition, since the average required processing time after the present time is accumulated, not only the manufacturing time for all the processes but also the manufacturing time required after a certain time can be appropriately acquired.

  In addition, by using the data for several months retroactive to the current time as the processing history, it is possible to reduce the error in the data for the required processing time by obtaining the average required processing time from the long-term data of several months. it can. Although the above effect cannot be obtained, data for the past 1 day or 3 days may be used, or weights (importance) may be set for these data, and these may be used in combination.

  Furthermore, the production date and time can be accurately predicted by predicting the predicted production date and time based on the prediction result of the production time prediction method capable of accurately predicting the production time.

  Although not described in the present embodiment, as shown in FIG. 2, as the lot progress information 43, the forecast date and time, the reverse calculation inventory number (back calculation inventory), and the delivery target lot (delivery target) are acquired and displayed. It may be what you do. The predicted date and time is the predicted manufacturing date and time of the lot when a lot newly comes in each process, and the control means 24 accumulates the average processing time after this process in order, and at the current date and time. , And calculating by adding the accumulated values. The number of back-calculated stocks indicates the number obtained by back-calculating the number of workpieces in each lot to be manufactured. The control means 24 accumulates the number of workpieces in the lot data from the final process to the main process. To calculate the back-calculated inventory quantity. The delivery target lot indicates a lot in which the back-calculated inventory number reaches the target number, and the control unit 24 acquires the delivery target lot from the back-calculated inventory quantity.

  In the present embodiment, the process management server 5 predicts the production date and time of each lot. However, the process management server 5 may predict the date and time (arrival date and time) to reach the designated target process (arrival). Time prediction device). That is, the control means 24 sequentially accumulates the average required processing time of the processing device group 6 (processing device 2) that each lot faces after the present time, and calculates the predicted arrival time until the lot reaches the target process ( Predicted arrival time acquisition step, predicted arrival time acquisition means). Thereafter, the predicted arrival date is calculated by adding the predicted arrival time to the current date and time. According to this, since the arrival time can be predicted in consideration of the unexpected waiting time, the arrival time can be predicted with high accuracy. In addition, since the average required processing time from the current time to the target process is accumulated, not only the arrival time from the start of manufacturing but also the arrival time from a certain time can be appropriately acquired. Furthermore, it is possible to predict the arrival date and time accurately by predicting the predicted arrival date and time based on the prediction result of the arrival time prediction method that can accurately predict the arrival time.

  In the present embodiment, each processing apparatus group 6 corresponds to each process of the production line 3, but the same processing apparatus 2 or processing apparatus group 6 is used in different processes. Also good. In such a case, each information terminal 4 transmits, as update information, the identification code, operating status information, and lot information of the corresponding device group for each process.

  In the present embodiment, each process is performed by the processing apparatus group 6 including one or more processing apparatuses 2, but each process may be performed by one processing apparatus 2.

  In the present embodiment, the average actual processing time and the average machining magnification are calculated in the process management server 5, but these may be calculated by a subsystem connected to the process management server 5.

  2: processing device, 3: production line, 5: process management server, 24: control means

Claims (8)

A production time prediction method for a workpiece for obtaining a predicted production time from the present time until the workpiece is manufactured, on a production line that processes the workpiece with a plurality of processing devices.
A required processing time acquisition step for obtaining an average required processing time including a non-processing time from the time when the workpiece is exposed to the processing device until the processing is completed, obtained from the processing history of each processing device;
In the workpiece manufacturing process, a predicted manufacturing time acquisition step of acquiring, as the predicted manufacturing time, a cumulative value obtained by sequentially accumulating the average required processing time of each processing device that faces the workpiece after the current time. ,
A method for predicting a manufacturing time of a workpiece, wherein a weight is set in the data of the processing history . In the processing time acquisition step,
From the processing history, an actual processing time acquisition step of acquiring an average actual processing time of the processing device;
From the processing history, a processing magnification acquisition step of acquiring an average processing magnification for the actual processing time in the workpiece to be exposed to the processing device,
2. The workpiece manufacturing time prediction method according to claim 1, wherein a value obtained by multiplying the average actual processing time and the average machining magnification is acquired as the average required processing time.   The work manufacturing time prediction method according to claim 1, wherein the processing history is data of several months retroactive from the present time.   A predicted production date and time at which the production of the workpiece is completed is obtained from the predicted production time obtained by the workpiece production time prediction method according to any one of claims 1 to 3 and the current date and time. Manufacturing date prediction method for workpieces. A workpiece arrival time prediction method for obtaining a predicted arrival time from the present time until the workpiece reaches a target process in a production line that performs processing by causing a plurality of processing devices to face the workpiece,
A required processing time acquisition step for obtaining an average required processing time including a non-processing time from the time when the workpiece is exposed to the processing device until the processing is completed, obtained from the processing history of each processing device;
In the manufacturing process of the workpiece, a predicted arrival time acquisition that acquires, as the predicted arrival time, a cumulative value obtained by sequentially accumulating the average required processing time of each processing apparatus that causes the workpiece to face from the current time to the target step. includes a step, the,
A work arrival time prediction method, characterized in that a weight is set in the processing history data .   An expected arrival date and time at which the workpiece reaches the target process is acquired from the predicted arrival time acquired by the workpiece arrival time prediction method according to claim 5 and the current date and time. Arrival date prediction method. A production time prediction device for a workpiece that obtains a predicted production time from the present time until the workpiece is produced in a production line that processes the workpiece with a plurality of processing devices.
A required processing time acquisition means for acquiring an average required processing time including a non-processing time from the time when the workpiece is exposed to the processing device until the processing is completed, obtained from the processing history of each processing device;
In the workpiece manufacturing process, a predicted manufacturing time acquisition unit that acquires, as the predicted manufacturing time, a cumulative value obtained by sequentially accumulating the average required processing time of each processing apparatus that faces the workpiece after the current time. ,
A workpiece manufacturing time prediction apparatus, wherein a weight is set in the processing history data . A workpiece arrival time prediction device for obtaining a predicted arrival time from the present time until the workpiece reaches a target process in a production line that performs processing with a workpiece facing a plurality of processing devices,
A required processing time acquisition means for acquiring an average required processing time including a non-processing time from the time when the workpiece is exposed to the processing device until the processing is completed, obtained from the processing history of each processing device;
In the manufacturing process of the workpiece, a predicted arrival time acquisition that acquires, as the predicted arrival time, a cumulative value obtained by sequentially accumulating the average required processing time of each processing apparatus that causes the workpiece to face from the current time to the target step. and means, the,
A workpiece arrival time prediction apparatus, wherein weights are set in the processing history data .

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