Information processing system and non-transitory computer readable

Abstract

To provide an information processing system and an information processing program for predicting man-hours required for a production process for determining specifications or design of a printed matter on the basis of order information of the printed matter.SOLUTION: When order information of a printed material is input, the estimation unit 106 inputs new order information of the printed material to a learned model learned in advance so as to output information on man-hours required for a production process for determining a specification or a design of the printed material, thereby outputting information on man-hours required for the production process corresponding to the new order information.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present disclosure relates to an information processing system and an information processing program. [Background technology]

[0002] Patent document 1 discloses a print ordering system that places an order for printing with a factory, which identifies the type and amount of paper used at the factory based on information collected from the factory to which the order is placed, and sends the identified type and amount of paper to the supplier of the paper used. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-26535 Summary of the Invention [Problem to be solved by the invention]

[0004] Printed materials are made up of multiple parts, and the manufacturing flow is complex because each part is manufactured through its own production flow.

[0005] In particular, in large factories, there are a large number of resources (machines, people) within the factory, so there are a large number of patterns for which resources to use for production, and it is important to create a production plan.

[0006] In the printing industry, customers often request changes to the specifications or designs of printed materials, and each time this occurs, it is necessary to frequently change production plans.

[0007] Currently, it is uncertain whether changes will occur to the specifications or design of printed materials, and it is difficult to estimate the man-hours required for the production process to determine the specifications or design, which places a heavy burden on workers when they have to recreate manufacturing plans.

[0008] Therefore, the present disclosure aims to provide an information processing system and an information processing program that can predict the man-hours required for the production process of determining the specifications or design of a printed matter based on order information for the printed matter. [Means for solving the problem]

[0009] In order to achieve the above object, the information processing system of the first aspect includes a processor, and when order information for printed matter is input, the processor inputs new order information for printed matter into a trained model that has been trained in advance to output information regarding the amount of labor required for the production process that determines the specifications or design of the printed matter, thereby outputting information regarding the amount of labor required for the production process that corresponds to the new order information.

[0010] An information processing system according to a second aspect is the information processing system according to the first aspect, wherein the order information and the new order information include information on order details from an orderer regarding specifications or design of printed matter.

[0011] An information processing system according to a third aspect is the information processing system according to the second aspect, wherein the information relating to the order contents includes text or voice input in an exchange between an orderer and a contractor.

[0012] An information processing system according to a fourth aspect is an information processing system according to the second aspect, wherein the information relating to the order contents includes information relating to the presence or absence of predetermined keywords in the text or voice entered in the exchange between the orderer and the contractor.

[0013] An information processing system according to a fifth aspect is the information processing system according to the first aspect, wherein the order information and the new order information include information for identifying an orderer.

[0014] An information processing system according to a sixth aspect is the information processing system according to the first aspect, wherein the order information and the new order information include information relating to a delivery date for printed materials.

[0015] An information processing system according to a seventh aspect is the information processing system according to the first aspect, wherein the order information and the new order information include an image relating to specifications or a design of a printed matter.

[0016] In the information processing system of the eighth aspect, in the information processing system of the first aspect, the information regarding the man-hours required for the production process includes the man-hours required for the entire production process, the number of changes to the specifications or design of the printed matter, or the man-hours required by the creator to create the design of the printed matter.

[0017] The information processing program of the ninth aspect causes a computer to input new order information for printed matter into a trained model that has been trained in advance to output information regarding the amount of labor required for the production process that determines the specifications or design of printed matter when order information for printed matter is input, and thereby output information regarding the amount of labor required for the production process that corresponds to the new order information. [Effects of the Invention]

[0018] According to the first aspect, it is possible to predict the number of steps required for the production process from the order information for the printed matter.

[0019] According to the second aspect, it is possible to predict the number of steps required for the production process based on the order details from the client.

[0020] According to the third aspect, it is possible to predict the man-hours required for the production process based on the text or voice input during the exchange between the orderer and the order recipient.

[0021] According to the fourth aspect, it is possible to predict the man-hours required for the production process based on the text or voice input during the exchange between the orderer and the order recipient.

[0022] According to the fifth aspect, it is possible to predict the number of steps required for the production process based on the information identifying the orderer.

[0023] According to the sixth aspect, it is possible to predict the number of steps required for the production process, taking into account the delivery date of the printed matter.

[0024] According to the seventh aspect, it is possible to estimate the number of steps required for the production process based on images relating to the specifications or design of the printed matter.

[0025] According to the eighth aspect, it is possible to predict the man-hours required for the entire production process, the number of changes to the specifications or design of the printed matter, or the man-hours required by the creator to create the design of the printed matter, from the order information for the printed matter.

[0026] According to the ninth aspect, it is possible to predict the number of steps required for the production process from the order information for the printed matter. [Brief explanation of the drawings]

[0027] [Figure 1] 1 is a diagram showing a schematic configuration of an information processing system according to an embodiment of the present invention; [Figure 2] FIG. 2 is a block diagram showing the main configuration of an electrical system of a printing device in the information processing system according to the present embodiment. [Figure 3] 2 is a block diagram showing the configuration of a main part of an electrical system of a server and a management device in the information processing system according to the present embodiment. FIG. [Figure 4] FIG. 2 is a functional block diagram showing the functional configuration of a management device in the information processing system according to the present embodiment. [Figure 5] FIG. 2 is a functional block diagram showing the functional configuration of a server in the information processing system according to the present embodiment. [Figure 6] FIG. 10 is a diagram illustrating an example of a trained neural network model. [Figure 7] 10 is a flowchart showing an example of the flow of a learning process performed by the server of the information processing system according to the present embodiment. [Figure 8] 10 is a flowchart showing an example of the flow of an estimation process performed by the server of the information processing system according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0028] An example of this embodiment will be described in detail below with reference to the drawings. In this embodiment, an information processing system in which a management device, a printing device, a client computer, etc. are connected to each other via communication lines such as various networks will be described as an example. Figure 1 is a diagram showing the schematic configuration of an information processing system 10 according to this embodiment.

[0029] 1, an information processing system 10 according to this embodiment includes a server 11, a printing device 12, and a management device 14. The server 11, the printing device 12, and the management device 14 are connected to each other via a communication line 18 such as a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, or an intranet. The server 11, the printing device 12, and the management device 14 are capable of transmitting and receiving various data to and from each other via the communication line 18. In this embodiment, the management device 14 instructs the printing device 12 to print, causing the printing device 12 to form an image in accordance with the print instruction.

[0030] Although FIG. 1 shows one server 11, one printing device 12, and one management device 14, there may be a plurality of each, or there may be a plurality of any of them.

[0031] The printing device 12 according to this embodiment has multiple functions, such as a printing function for performing print processing, a post-processing function for performing post-processing on printed paper, etc. The multiple functions may include a reading function for reading an original to obtain image information representing the original, a copying function for copying an image recorded on the original onto paper, a facsimile function for sending and receiving various data via a telephone line (not shown), a transfer function for transferring original information such as image information read by the reading function, etc., and a storage function for storing original information such as read image information.

[0032] In the following description, the facsimile function may be referred to as fax, the reading function as scan, the printing function as print, and the copying function as copy.

[0033] FIG. 2 is a block diagram showing the main configuration of the electrical system of the printing device 12 in the information processing system 10 according to this embodiment.

[0034] 2, the printing device 12 according to this embodiment includes a control unit 20. The control unit 20 may include a CPU (Central Processing Unit), a ROM (Read Only Memory), and a RAM (Random Access Memory).

[0035] Meanwhile, the printing device 12 according to this embodiment includes a hard disk drive (HDD) 26 that stores various data, application programs, and the like. The printing device 12 is also connected to a user interface 22 and includes a display control unit 28 that controls the display of various operation screens and the like on the display of the user interface 22. The printing device 12 is also connected to the user interface 22 and includes an operation input detection unit 30 that detects operation instructions input via the user interface 22. In the printing device 12, the HDD 26, the display control unit 28, and the operation input detection unit 30 are electrically connected to a system bus 42. While the printing device 12 according to this embodiment uses the HDD 26 as a storage unit, this is not a limitation and a non-volatile storage unit such as a flash memory may also be used. Furthermore, while this embodiment uses a touch panel capable of displaying and inputting operations as the user interface 22, this is not a limitation and a user interface having a display and an operation unit that are separate may also be used.

[0036] The printing device 12 according to this embodiment also includes a print control unit 34 that controls the printing process performed by the printing unit 24, the transport of paper to the printing unit 24 by the transport unit 25, and the post-processing process performed by the post-processing unit 46. The printing device 12 may also include a read control unit that controls the optical image reading operation performed by the document reading unit and the document feeding operation performed by the document transport unit. The printing device 12 also includes a communication line I / F (interface) unit 36 ​​that is connected to the communication line 18 and transmits and receives communication data to and from other external devices, such as the management device 14, that are connected to the communication line 18. The printing device 12 may also include a facsimile I / F (interface) unit that is connected to a telephone line (not shown) and transmits and receives facsimile data to and from a facsimile device connected to the telephone line. The printing device 12 may also include a transmission / reception control unit that controls the transmission and reception of facsimile data via the facsimile I / F unit 38. In the printing device 12, the print control unit 34 and the communication line I / F unit 36 ​​are electrically connected to a system bus 42.

[0037] With the above configuration, the printing device 12 according to this embodiment uses the control unit 20 to control the display of information such as operation screens and various messages on the display of the user interface 22 via the display control unit 28. The printing device 12 also uses the control unit 20 to control the operation of the printing unit 24, conveying unit 25, and post-processing unit 46 via the print control unit 34, and to control the sending and receiving of communication data via the communication line I / F unit 36. Furthermore, the printing device 12 uses the control unit 20 to grasp the operation content of the user interface 22 based on the operation information detected by the operation input detection unit 30, and executes various controls based on this operation content.

[0038] In this embodiment, an example of an application stored in the HDD 26 includes an application that executes a function such as printing.

[0039] Next, the main configuration of the electrical system of the server 11 and management device 14 according to this embodiment will be described. Fig. 3 is a block diagram showing the main configuration of the electrical system of the server 11 and management device 14 in the information processing system 10 according to this embodiment. Note that since the server 11 and management device 14 have a general computer configuration, the following description will be given using the server 11 as a representative.

[0040] As shown in FIG. 3, the server 11 according to this embodiment includes a CPU 11A as an example of a processor, a ROM 11B, a RAM 11C, a storage 11D, an operation unit 11E, a display unit 11F, and a communication line I / F (interface) unit 11G. The CPU 11A controls the overall operation of the server 11. The ROM 11B stores various control programs and parameters in advance. The RAM 11C is used as a work area when the CPU 11A executes various programs. The storage 11D stores various data and application programs. The operation unit 11E is used to input various information. The display unit 11F is used to display various information. The communication line I / F unit 11G is connected to a communication line 18 and transmits and receives various data to and from other devices connected to the communication line 18. The communication line I / F unit 11G may also be configured to be capable of directly communicating with each device using various well-known wireless communications. The above-described components of the server 11 are electrically connected to each other via a system bus 11I. In the server 11 according to this embodiment, the storage 11D is used as a storage unit, and examples of storage include non-volatile storage units such as HDDs (Hard Disk Drives) and flash memories.

[0041] With the above configuration, the server 11 according to this embodiment uses the CPU 11A to access the ROM 11B, RAM 11C, and storage 11D, to obtain various data via the operation unit 11E, and to display various information on the display unit 11F. In addition, the server 11 uses the CPU 11A to control the transmission and reception of communication data via the communication line I / F unit 11G.

[0042] In the information processing system 10 configured as above, the management device 14 manages a series of manufacturing processes, which include, for example, a production process, a prepress process, a plate making process, a printing process, a processing process, and a delivery process.

[0043] Next, a description will be given of the functional configuration of the management device 14. Fig. 4 is a block diagram showing an example of the functional configuration of the management device 14.

[0044] As shown in FIG. 4, the management device 14 is functionally configured to include an order history database (DB) 51, a manufacturing history database (DB) 52, a learning data creation unit 53, an input unit 54, a planning unit 56, a prepress processing unit 57, and a job sending unit 58.

[0045] The order record database (DB) 51 stores record information on orders for printed materials. The record information on orders for printed materials includes, for example, information identifying the ordering company, information identifying the person in charge at the ordering company, delivery date information, and information on the order contents. The information on the order contents includes text or voice input during communication between the ordering company and the order recipient.

[0046] The production performance database (DB) 52 stores performance information on the production of printed matter. The performance information on the production of printed matter includes information on the number of steps required for the production process. The information on the number of steps required for the production process includes, for example, the number of steps required for the entire production process, the number of changes made to the specifications or design of the printed matter, or the number of steps required by the creator to create the design of the printed matter.

[0047] The performance information for the production of printed materials includes text or audio regarding changes to the specifications or design of the printed material entered during communication between the client and the recipient, and data file information before and after changes to the specifications or design of the printed material. The performance information for the production of printed materials includes difference information that indicates the extent to which changes to the specifications or design of the printed material have affected the planned production schedule. The performance information for the production of printed materials includes production performance information such as which devices, paper, and equipment were used for production.

[0048] The learning data creation unit 53 creates learning data including pairs of order information for printed matter that has been ordered in the past and information on the man-hours required for the production process that corresponds to the order information.

[0049] The order information may include information about the order contents from the orderer regarding the specifications or design of the printed matter. The information about the order contents may include text or voice entered in the exchange between the orderer and the order recipient. For example, it may include free text entered in the exchange of emails or order forms between the orderer and the order recipient, or voices in a telephone exchange between the orderer and the order recipient.

[0050] Information about order details may include information about the presence or absence of predetermined keywords in text or voice input during communication between the purchaser and the contractor. Predetermined keywords are specifically keywords predefined by the purchaser as expressions requesting changes to specifications or designs. More specifically, predetermined keywords may include words that clearly belong to the production process, such as "typo" or "position of xx." Predetermined keywords may also include words that clearly belong to the manufacturing process, such as "paper," "printing," "printing," and "register." Predetermined keywords may also include words that can belong to either the production process or the manufacturing process, such as "brightness" or "color," or phrases that refer to corrections in the production process or the manufacturing process (e.g., "xx's," "color the whole thing"), respectively.

[0051] By performing a pre-processing to extract predetermined keywords from the text or voice input during the exchange between the orderer and the contractor, information regarding the presence or absence of the predetermined keywords can be obtained.

[0052] The learning data creation unit 53 collects information on the order contents from the order record database 51 of the management device 14 .

[0053] The order information may also include information identifying the orderer, which may include information identifying the company that is the orderer and information identifying the person in charge at the company that is the orderer.

[0054] Specifically, the information for identifying the company that is the orderer includes the name of the company that is the orderer, the ID of the company that is the orderer, and the like.

[0055] The learning data creation unit 53 collects information identifying the orderer from the order record database 51 of the management device 14 .

[0056] The order information may include information relating to the delivery date of the printed matter, such as a period or date indicating the delivery date of the printed matter.

[0057] The learning data creation unit 53 collects information on the delivery dates of printed materials from the order record database 51 of the management device 14.

[0058] The order information may include an image relating to the specifications or design of the printed matter, such as a rough image representing the specifications or design of the printed matter.

[0059] The learning data creation unit 53 collects images relating to the specifications or designs of printed matter from the order record database 51 of the management device 14.

[0060] Information about the number of steps required for the production process is calculated by the learning data creation unit 53 from information about the performance of the printing device 12 that processes a plurality of print jobs.

[0061] Information regarding the number of steps required for the production process includes the number of steps required for the entire production process, the number of changes to the specifications or design of the printed matter, or the number of steps required by the creator to create the design of the printed matter.

[0062] Specifically, for the printing of the printed matter that a worker is in charge of, the number of man-hours required for the entire production process, the number of changes to the specifications or design of the printed matter, and the man-hours required by the creator to create the design of the printed matter are input into the management device 14 as performance information, and these are managed in the manufacturing performance database 52 of the management device 14 as history information.

[0063] The learning data creation unit 53 collects information on the number of steps required for the production process from the manufacturing performance database 52 of the management device 14.

[0064] The input unit 54 accepts new order information input by the user. For example, the user accesses the WebUI from a browser displayed on the user terminal and inputs new order information via the WebUI.

[0065] The planning unit 56 communicates with the server 11 regarding the new order information and acquires information regarding the number of man-hours required for the production process. At this time, the server 11 uses the trained model to output information regarding the number of man-hours required for the production process.

[0066] Based on the information regarding the number of steps required for the production process acquired from the server 11, the planning unit 56 determines the manufacturing process, materials, and schedule for the new order information.

[0067] The prepress processing unit 57 performs prepress such as preflight, imposition, barcode application, or watermark application.

[0068] The job sending unit 58 sends the printing information and information about the print job to the printing device 12.

[0069] Next, a description will be given of the functional configuration of the server 11. Fig. 5 is a block diagram showing an example of the functional configuration of the server 11.

[0070] As shown in FIG. 5, the server 11 is functionally configured to include a collection unit 101, a learning data storage unit 102, a learning unit 103, a model storage unit 104, a reception unit 105, an estimation unit 106, and an output unit 107.

[0071] The collection unit 101 collects learning data including pairs of order information for printed materials that have been ordered in the past and information on the man-hours required for the production process that corresponds to the order information.

[0072] The learning data storage unit 102 stores a plurality of pieces of learning data collected by the collection unit 101.

[0073] The learning unit 103 receives order information as an input and constructs a neural network model for estimating information relating to the number of man-hours required for the production process, which corresponds to the order information, based on a plurality of learning data.

[0074] Specifically, the trained neural network model accepts input of order information including at least one of information about the order content, information identifying the orderer, information about delivery date, and an image related to the specifications or design, and outputs at least one of the following as information about the man-hours required for the production process corresponding to the order information: the man-hours required for the entire production process, the number of changes to the specifications or design of the printed matter, and the man-hours required by the creator who creates the design (see Figure 6). Deep learning can be used as an example of a learning algorithm, and the neural network model may be constructed so that when order information for training data is input, information about the man-hours required for the production process for the training data is output.

[0075] More specifically, the order information of the learning data is used as input, and information regarding the labor hours required for the production process is estimated as the model output. The estimated information regarding the labor hours required for the production process is compared with the information regarding the labor hours required for the production process of the learning data, the error in the information regarding the labor hours required for the production process is calculated, and the model parameters are updated so as to minimize the value of the error.

[0076] Here, the correlation between the order information and the information regarding the number of steps required for the production process will be described.

[0077] First, from the information about the order contents, it is possible to determine whether the order is related to the production process or the manufacturing process after the printing process, and whether the customer tends to be particular about content production or manufacturing. Also, it is preferable to create a schedule that allocates margins preferentially to processes that the customer is particularly particular about. In this way, there is a correlation between information about the order contents and information about the man-hours required for the production process.

[0078] Furthermore, from the information identifying the client, it is possible to determine whether the client is more interested in content creation or manufacturing. In this way, there is a correlation between the information identifying the client and information regarding the number of man-hours required for the production process.

[0079] Furthermore, information about delivery dates can be used to determine whether the customer is particular about content creation or manufacturing, and whether they want early delivery. In this way, there is a correlation between information about delivery dates and information about the number of man-hours required for the production process.

[0080] Furthermore, it is possible to determine whether the customer is more interested in content creation or manufacturing from the images of specifications or designs. Thus, there is a correlation between the images of specifications or designs and information regarding the number of man-hours required for the production process.

[0081] The model storage unit 104 stores a trained neural network model.

[0082] The receiving unit 105 receives new order information for printed matter to be estimated.

[0083] The order information may include information about the order content from the orderer, such as the specifications or design of the printed matter. The information about the order content may include text or voice input during communication between the orderer and the order recipient. For example, the reception unit 105 receives free text input during communication between the orderer and the order recipient via email or an order form, or voice input during a telephone conversation between the orderer and the order recipient, input via the input unit 54 of the management device 14.

[0084] Furthermore, the information about the order content may include information about the presence or absence of predetermined keywords in the text or voice input during the exchange between the orderer and the order recipient. For example, the receiving unit 105 receives information about the presence or absence of predetermined keywords obtained by performing a pre-processing to extract predetermined keywords from the text or voice input during the exchange between the orderer and the order recipient.

[0085] The order information may also include information identifying the orderer. The information identifying the orderer may include information identifying the company that is the orderer and information identifying the person in charge at the company that is the orderer. For example, the receiving unit 105 receives the name of the company that is the orderer, the ID of the company that is the orderer, etc., input via the input unit 54 of the management device 14.

[0086] The order information may also include information related to the delivery date of the printed matter. The information related to the delivery date of the printed matter may include, for example, a period or date indicating the delivery date of the printed matter. For example, the accepting unit 105 may accept, via the input unit 54 of the management device 14, a period such as "the 14th" or a date such as "March 30th" indicating the delivery date of the printed matter.

[0087] The order information may also include an image relating to the specifications or design of the printed matter. The image relating to the specifications or design of the printed matter may include, for example, an image representing the specifications or design of the printed matter. For example, the accepting unit 105 accepts an image representing the specifications or design of the printed matter input via the input unit 54 of the management device 14.

[0088] The estimation unit 106 uses the trained neural network model stored in the model storage unit 104 to estimate information related to the number of man-hours required for the production process corresponding to the received order information.

[0089] Specifically, the various information contained in the received order information is converted into a data structure (e.g., scalar values, vectors, etc.) that can be input into a trained neural network model, and then input into the trained neural network model, and information regarding the labor hours required for the production process is estimated from the output of the trained model.

[0090] The output unit 107 transmits the estimated information on the man-hours required for the production process to the management device 14. As a result, the planning unit 56 of the management device 14 acquires information on the man-hours required for the production process for the new order information. The planning unit 56 can plan a schedule for each process after the production process based on the information on the delivery date of the printed matter and the information on the man-hours required for the production process.

[0091] Next, specific processing performed in the information processing system 10 according to this embodiment configured as described above will be described.

[0092] First, in the management device 14, order information of past printed matter is stored in the order record database 51, and past production records of printed matter are stored in the production record database 52.

[0093] The learning data creation unit 53 creates learning data including pairs of order information for past printed materials and information relating to the man-hours required for the production process corresponding to the order information.

[0094] Next, in the server 11, the CPU 14A reads out the learning program from the ROM 14B or the storage 14D, loads it into the RAM 14C, and executes it, thereby performing the learning process shown in FIG.

[0095] In step S100, the CPU 14A, as the collection unit 101, collects learning data including pairs of past printed matter order information and information regarding the labor hours required for the production process corresponding to the order information, created by the learning data creation unit 53 of the management device 14, and stores the data in the learning data storage unit 102.

[0096] In step S102, the CPU 14A, as the learning unit 103, inputs the order information based on a plurality of learning data, learns a neural network model for estimating information related to the man-hours required for the production process corresponding to the order information, stores the model in the model storage unit 104, and terminates the learning process.

[0097] Next, in the management device 14, the input unit 54 receives new order information input by the user.

[0098] The planning unit 56 transmits the new order information to the server 11.

[0099] At this time, in the server 11, the CPU 14A reads out the estimation program from the ROM 14B or the storage 14D, loads it into the RAM 14C, and executes it, thereby performing the estimation process shown in FIG.

[0100] In step S110, CPU 14A functions as reception unit 105 to receive order information for new printed matter, which is input by the user and is to be estimated.

[0101] In step S112, CPU 14A functions as estimation unit 106 and uses the trained neural network model stored in model storage unit 104 to estimate information related to the number of man-hours required for the production process corresponding to the received order information.

[0102] In step S114, CPU 14A functions as output unit 107 to transmit information relating to the estimated man-hours required for the production process to management device 14, and ends the estimation process.

[0103] The planning unit 56 of the management device 14 acquires information about the man-hours required for the production process for the new order information. The planning unit 56 can plan a schedule for each process after the production process based on the information about the delivery date of the printed matter and the information about the man-hours required for the production process.

[0104] By performing this processing, it is possible to predict the man-hours required for the production process of determining the specifications or design of the printed matter based on the order information for the printed matter, and to use the predicted man-hours required for the production process to plan a schedule for each process after the production process.

[0105] <Modification> The present invention is not limited to the above-described embodiment, and various modifications and applications are possible without departing from the spirit and scope of the present invention.

[0106] In the above embodiment, an example was described in which various pieces of order information were accepted and information regarding the man-hours required for the production process was estimated, but it is also possible to accept only a portion of the various pieces of order information rather than accepting all of the various pieces of order information and estimate information regarding the man-hours required for the production process.

[0107] In addition, although the example has been described in which the server 11 learns a model and estimates information regarding the man-hours required for the production process, it may also be configured as being divided into a learning device that learns the model and an estimation device that estimates information regarding the man-hours required for the production process.

[0108] Furthermore, in the above embodiments, the term "processor" refers to a processor in a broad sense, and includes general-purpose processors (e.g., CPUs, etc.) and dedicated processors (e.g., GPU: Graphics Processing Unit, ASIC: Application Specific Integrated Circuit, FPGA: Field Programmable Gate Array, programmable logic device, etc.).

[0109] Furthermore, the operations of the processors in the above embodiments may not only be performed by a single processor, but may also be performed by multiple processors located at physically separate locations working together. Furthermore, the order of the operations of the processors is not limited to the order described in the above embodiments, and may be changed as appropriate.

[0110] Furthermore, although the "system" in this embodiment is described as being composed of multiple devices as an example, it may also be composed of a single device that has some of the functions of the multiple devices.

[0111] The processing performed by the printing device 12 according to the above embodiment may be software-based, hardware-based, or a combination of both. The processing performed by the printing device 12 may also be stored as a program on a storage medium and distributed.

[0112] Furthermore, the present disclosure is not limited to the above, and it goes without saying that various modifications can be made without departing from the spirit of the present disclosure.

[0113] The following additional notes are provided regarding the above-described embodiments. (((1))) a processor, the processor comprising: When order information for a printed matter is input, the trained model is trained in advance to output information about the man-hours required for the production process that determines the specifications or design of the printed matter. By inputting new order information for a printed matter into the trained model, information about the man-hours required for the production process that corresponds to the new order information is output. Information processing system.

[0114] (((2))) The information processing system according to ((1))), wherein the order information and the new order information include information about the order content from the orderer regarding the specifications or design of the printed matter.

[0115] (((3))) The information processing system according to (((2))) wherein the information regarding the order content includes text or voice input during communication between the orderer and the order recipient.

[0116] (((4))) The information processing system described in (((2))) in which the information regarding the order content includes information regarding the presence or absence of predetermined keywords in the text or voice entered in the exchange between the orderer and the order recipient.

[0117] (((5))) The information processing system according to any one of ((1))) to ((4))), wherein the order information and the new order information include information for identifying an orderer.

[0118] (((6))) The information processing system according to any one of ((1))) to ((5))), wherein the order information and the new order information include information relating to a delivery date for printed matter.

[0119] (((7))) The order information and the new order information include images related to specifications or designs of printed materials. The information processing system according to any one of (((1))) to (((6))).

[0120] (((8))) The information regarding the number of steps required for the production process includes the number of steps required for the entire production process, the number of changes to the specifications or design of the printed matter, or the number of steps required by the creator to create the design of the printed matter. The information processing system according to any one of (((1))) to (((7))).

[0121] (((9))) When order information for a printed matter is input, the trained model is trained in advance to output information about the man-hours required for the production process that determines the specifications or design of the printed matter. By inputting new order information for a printed matter into the trained model, information about the man-hours required for the production process that corresponds to the new order information is output. An information processing program that causes a computer to perform certain tasks.

[0122] According to (((1))), it is possible to predict the man-hours required for the production process from the order information for printed materials.

[0123] According to (((2))), it is possible to predict the man-hours required for the production process based on the order details from the client.

[0124] According to (((3))), it is possible to predict the man-hours required for the production process based on the text or voice input during the exchange between the client and the contractor.

[0125] According to (((4))), it is possible to predict the man-hours required for the production process based on the text or voice input during the exchange between the client and the contractor.

[0126] According to (((5))), it is possible to predict the man-hours required for the production process based on information identifying the client.

[0127] According to (((6))), it is possible to predict the man-hours required for the production process based on the delivery date of the printed matter.

[0128] According to (((7))), it is possible to predict the number of steps required for the production process based on images related to the specifications or design of the printed matter.

[0129] According to (((8))), it is possible to predict the man-hours required for the entire production process, the number of changes to the specifications or design of the printed matter, or the man-hours required by the creator to create the design of the printed matter, from the order information for the printed matter.

[0130] According to (((9))), it is possible to predict the man-hours required for the production process from the order information for printed materials. [Explanation of symbols]

[0131] 10 Information Processing Systems 11 Management device 12 Printing device 14 client computers 24 Printing Department 51 Order history database 52 Manufacturing performance database 53 Learning Data Creation Department 54 Input section 56 Planning Department 101 Collection Department 102 Learning data storage unit 103 Learning Department 104 Model Memory Unit 105 Reception 106 Estimation part 107 Output section

Claims

1. a processor, the processor comprising: When order information for a printed matter is input, the trained model is trained in advance to output information about the man-hours required for the production process that determines the specifications or design of the printed matter. By inputting new order information for a printed matter into the trained model, information about the man-hours required for the production process that corresponds to the new order information is output. Information processing system.

2. 2. The information processing system according to claim 1, wherein the order information and the new order information include information about the order contents from the orderer regarding the specifications or design of the printed matter.

3. 3. The information processing system according to claim 2, wherein the information about the order content includes text or voice input during communication between the orderer and the order recipient.

4. 3. The information processing system according to claim 2, wherein the information about the order content includes information about the presence or absence of a predetermined keyword in text or voice input during communication between the orderer and the order recipient.

5. The information processing system according to claim 1 , wherein the order information and the new order information include information for identifying an orderer.

6. The information processing system according to claim 1 , wherein the order information and the new order information include information about a delivery date for the printed matter.

7. The order information and the new order information include images related to specifications or designs of printed materials. The information processing system according to claim 1 .

8. The information regarding the number of steps required for the production process includes the number of steps required for the entire production process, the number of changes to the specifications or design of the printed matter, or the number of steps required by the creator to create the design of the printed matter. The information processing system according to claim 1 .

9. When order information for a printed matter is input, the trained model is trained in advance to output information about the man-hours required for the production process that determines the specifications or design of the printed matter. By inputting new order information for a printed matter into the trained model, information about the man-hours required for the production process that corresponds to the new order information is output. An information processing program that causes a computer to perform certain tasks.

Images