JP5712602B2 - Job execution control device, image forming system, job execution control method, and job execution control program - Google Patents

Description

  The present invention relates to a job execution control device, an image forming system, a job execution control method, and a job execution control program.

  Print services and scan services provided by image forming devices such as MFPs (MFPs) can be realized only by combining them with consumables, unlike services realized by a single software service (eg, translation service). It is a service. For example, when realizing a print service by the image forming apparatus, consumables such as toner and paper are required. When these consumables are exhausted, the user cannot execute a desired service.

  On the other hand, in recent years, there has been known an image forming system that connects a plurality of image forming apparatuses to a network, distributes jobs that cannot be executed by one image forming apparatus to other image forming apparatuses, and realizes a service desired by a user. (See, for example, Patent Documents 1 and 2). In such an image forming system, it is important to properly grasp the state of consumables of each image forming apparatus connected to the network so that jobs can be appropriately distributed.

  As a technique for grasping the state of consumables in the image forming apparatus, for example, a technique described in Patent Document 3 is known. In this prior art, a history of the remaining amount of consumables such as ink in a printing apparatus is stored, and a graph display showing the transition of consumables is performed based on the stored history information. In addition, information such as the number of printable sheets, the number of printable orders, and the number of printable days predicted from the average of the most recent used amount of ink and the current remaining amount is displayed together with the graph display. Then, the usage amount of the consumables is estimated for each order for which printing is designated, orders that may run out of consumables are skipped, and other orders that can be output are processed.

  However, in the above prior art, considering only the service by a single printing apparatus, the order that may run out of consumables is skipped and another order that can be output is processed. A process that uses a large amount of is placed in a wait state. For this reason, there is a problem that a user who wants to process a large amount of jobs stops working.

  Further, in the above-described conventional technology, the usage information of consumables for each user is not reflected in the history information used for predicting the remaining amount of consumables. Therefore, there is a problem that prediction accuracy is poor.

  The present invention has been made in view of the above, and accurately predicts the state of consumables of each device that provides services on the network, and appropriately selects a device that executes a job requested by the user. It is an object of the present invention to provide a job execution control device, an image forming system, a job execution control method, and a job execution control program that can be used.

In order to solve the above-described problems and achieve the object, a job execution control apparatus according to the present invention is a job execution control apparatus that is connected to a network together with a plurality of devices and controls execution of a job requested by a user. For each of the plurality of devices, a holding unit that stores history information indicating a history of consumption of consumables for each user who uses each device, and based on the history information, consumables in the plurality of devices A calculation unit that calculates a predicted value that is a value predicted from the usage amount; and a selection unit that selects a device that executes the job from the plurality of devices based on the history information and the predicted value. The calculation means obtains a value obtained by multiplying an average value of the consumable consumption amount when one job is executed by a weight according to the consumable consumption history included in the history information. It characterized that you calculated as the predicted value.

The image forming system according to the present invention is an image forming system in which a plurality of image forming apparatuses and a job execution control apparatus that controls execution of a job requested by a user are connected to a network. A job execution control device, for each of the plurality of image forming devices, based on the history information, holding means for holding history information representing a history of consumable consumption for each user who uses each image forming device, A calculation unit that calculates a predicted value that is a predicted value of the amount of consumables used in the plurality of image forming apparatuses, and the job among the plurality of image forming apparatuses based on the history information and the predicted value. comprising selecting means for selecting an image forming apparatus for performing the said calculation means, with respect to the average value of consumables usage when executing a single job, the history information The value obtained by multiplying the weight according to the history of the consumable usage contained, characterized that you calculated as the predicted value.

The job execution control method according to the present invention is a job execution control method for controlling the execution of a job requested by a user, from each of a plurality of devices connected to a network, for each user who uses each device. Acquiring history information representing a history of consumables usage, calculating a predicted value that is a value predicting the usage of consumables in the plurality of devices based on the history information, and the history based on the information and the predicted value, selecting a device to perform the job of the plurality of devices, only including the step of calculating the predicted value, wasting the time of running one job A value obtained by multiplying the average value of the used amount of goods by a weight corresponding to the history of the used amount of consumables included in the history information is calculated as the predicted value .

In addition, the job execution control program according to the present invention provides history information representing a history of consumable consumption for each user who uses each device for each of the plurality of devices on a computer connected to the network together with the plurality of devices. A function of holding a consumption value based on the history information, a function of calculating a predicted value that is a predicted value of the amount of consumables used in the plurality of devices, and a plurality of the plurality of values based on the history information and the predicted value. A function for selecting a device that executes a job requested by a user from among the devices, and a function for calculating the predicted value is an average value of the amount of consumables used when one job is executed. against it, a value obtained by multiplying the weight according to the history of the consumable usage contained in the history information, characterized that you calculated as the predicted value.

  According to the present invention, it is possible to accurately predict the state of consumables of each device that provides a service on the network and appropriately select a device that executes a job requested by the user.

FIG. 1 is a configuration diagram schematically showing the overall configuration of an image forming system. FIG. 2 is a diagram illustrating a software module configuration in the job execution management apparatus. FIG. 3 is a flowchart showing an outline of a predicted value calculation process executed in the job execution control apparatus. FIG. 4 is a flowchart illustrating an example of a job execution control process executed in the job execution control apparatus. FIG. 5 is a diagram showing a specific example of service history information held in the information table. FIG. 6 is a flowchart illustrating an example of processing for calculating a predicted toner value. FIG. 7 is a diagram illustrating a correspondence relationship between the history value of the total number of output sheets per day and the weight value. FIG. 8 is a diagram illustrating a correspondence relationship between the history value of the document type and the weight value. FIG. 9 is a diagram illustrating the correspondence between the paper size history value and the weight value. FIG. 10 is a diagram showing weight values for the users U1 to U3 calculated using the service history information shown in FIG. FIG. 11 is a diagram in which the history (actually measured value) of the remaining amount of toner in a certain device is plotted on the time axis. FIG. 12 is a diagram showing a toner consumption prediction curve L1 calculated based on the toner predicted value. FIG. 13 is a graph showing the peak output time for each of the three users U1 to U3. FIG. 14 is a diagram showing a prediction curve L2 obtained by reflecting the peak output time of FIG. 13 with respect to the prediction curve L1 shown in FIG. FIG. 15 is a diagram in which the prediction curve L1 and the prediction curve L2 are plotted on a longer time axis than FIG. FIG. 16 is a flowchart illustrating an example of processing for calculating a predicted staple value. FIG. 17 is a diagram illustrating a correspondence relationship between a history value of staple usage per day and a weight value. FIG. 18 is a diagram illustrating weight values for the staple usage amount for each of the users U1 to U3 calculated using the service history information illustrated in FIG. FIG. 19 is a diagram illustrating an example of a UI screen for a user to input a job execution request. FIG. 20 is a diagram illustrating an example of a UI screen displayed on the user terminal when the requested job is executed normally. FIG. 21 is a diagram illustrating an example of a UI screen displayed on the user terminal when the requested job cannot be executed. FIG. 22 is a diagram illustrating an example of a UI screen displayed on the user terminal when there is no service providing device corresponding to the requested job.

  Exemplary embodiments of a job execution control device, an image forming system, a job execution control method, and a job execution control program according to the present invention are explained in detail below with reference to the accompanying drawings.

  FIG. 1 is a configuration diagram schematically showing the overall configuration of the image forming system according to the present embodiment. As shown in FIG. 1, the image forming system according to the present embodiment includes a plurality of image forming apparatuses A to E connected to a network NT, and a job execution control apparatus 100. Further, although not shown, an information processing terminal (hereinafter referred to as a user terminal) such as a personal computer used by the user is connected to the network NT. The image forming apparatuses A to E, the job execution control apparatus 100, and the user terminal on the network NT each have a communication function for performing information communication using the network NT. Although FIG. 1 illustrates an example in which five image forming apparatuses A to E are connected to the network NT, the number of image forming apparatuses connected to the network NT is not limited to this.

  The image forming apparatuses A to C are configured as a multifunction peripheral (MFP) as an example, and provide a scan service and a print service. The scan service of the image forming apparatuses A to C supports color and black and white. The print service of the image forming apparatuses A to C corresponds to color and black and white, the print size corresponds to the A2, A3, and A4 plates, and further supports the staple process as post-processing.

  The image forming apparatus D is configured as a multifunction peripheral (MFP) as an example, and provides a scan service and a print service. The scan service of the image forming apparatus D supports only black and white. The print service of the image forming apparatus D supports only black and white, and the print size supports only the A4 version.

  The image forming apparatus E is configured as a printer as an example, and provides a print service. The print service of the image forming apparatus E supports only black and white, and the print size supports only the A4 version.

  The job execution control apparatus 100 is an information processing apparatus in which the job execution control program according to the present embodiment is installed. The job execution control apparatus 100 has a general personal computer or server configuration as a hardware configuration.

  FIG. 2 is a diagram illustrating a software module configuration in the job execution management apparatus 100. Software modules in the job execution management apparatus 100 are classified into a display unit 110, an application unit 120, and an OS unit 130. Among these, the software module included in the application unit 120 constitutes the job execution control program according to the present embodiment.

  The job execution management apparatus 100 includes a UI presenting unit 111 as a software module of the display unit 110. The job execution management apparatus 100 includes a service management unit 121, an information table 122, a prediction unit 123, and a service control unit 124 as software modules of the application unit 120. In addition, the job execution management apparatus 100 includes a network protocol 131 and a network communication driver 132 as software modules of the OS unit 130.

  The UI presenting unit 111 provides a user interface for performing an operation using the image forming system according to the present embodiment to the user.

  The service management unit 121 includes service information, which is information indicating the contents of services provided by the image forming apparatuses A to E, from the image forming apparatuses A to E on the network NT that provides a scan service and a print service, Service history information (see FIG. 5), which is information indicating the usage history for each end user for the services provided by the image forming apparatuses A to E, is acquired and stored in the information table 122. In the present embodiment, it is assumed that the image forming apparatuses A to E on the network NT generate and hold service history information as shown in FIG. If E does not have such a function, the service management unit 121 acquires log data (data recording the contents of processes executed in the past) from the image forming apparatuses A to E, and acquires the acquired log data. The service history information may be generated by analyzing the service history information, and the generated service history information may be stored in the information table 122.

  In addition, when a job execution request is input from the user, the service management unit 121 uses the content of the requested job, the service information and service history information stored in the information table 122, and the prediction unit 123. Based on the calculated predicted value and the service available time, an optimum service for executing the job is selected.

  Here, when all processes included in a job can be executed by a single image forming apparatus, the service selection method selects a service by a single image forming apparatus and distributes the processes included in the job. When a job can be executed by a plurality of image forming apparatuses, a distributed service by the plurality of image forming apparatuses is selected. In addition, when there are a plurality of image forming apparatuses capable of executing all the processes included in the job, or when a distributed service is performed by a plurality of image forming apparatuses, the predicted value calculated by the prediction unit 123 and the service available time Is used to select an image forming apparatus that executes all or some of the processes included in the job.

  The information table 122 includes service information and service history information acquired from the image forming apparatuses A to E on the network NT by the service management unit 121, and predicted value and service provisionable time information calculated by the prediction unit 123. Hold.

  The prediction unit 123 predicts the consumption amount of consumables in each of the image forming apparatuses A to E on the network NT based on the service history information (such as the usage tendency of the print service for each user) stored in the information table 122. A predicted value that is a value and a service available time are calculated. The predicted value and the service available time calculated by the prediction unit 123 are stored in the information table 122. These predicted values and service available time are used as information for determining whether or not the service can still be used in each device when the service management unit 121 selects an optimum service. Details of the predicted value calculated by the prediction unit 123 and the service available time will be described later.

  The service control unit 124 outputs a service execution request (for example, a color print execution request, a monochrome print execution request, etc.) for executing the service selected by the service management unit 121 using the image forming apparatus on the network NT. To do.

  The network protocol 131 and the network communication driver 132 transmit the service execution request output from the service control unit 124 to the designated image forming apparatus on the network NT. The network protocol 131 and the network communication driver 132 are software modules that realize a communication function for performing information communication using the network NT described above.

  FIG. 3 is a flowchart showing an outline of a predicted value calculation process executed in the job execution control apparatus 100.

  When the process shown in the flowchart of FIG. 3 starts, the service management unit 121 searches for a device that provides a service on the network NT (step S101). In the configuration of the image forming system illustrated in FIG. 1, image forming apparatuses A to E are detected as devices that provide services on the network NT.

  Next, for each device (image forming apparatuses A to E) detected in step S101, the service management unit 121 acquires the service information described above from each device (step S102) and also acquires service history information (step S102). Step S103). The service here refers to a service of a unit used by the user, and specifically, is a service (for example, monochrome printing, color printing, etc.) provided by the image forming apparatuses A to E shown in FIG. Service information and service history information acquired by the service management unit 121 are stored in the information table 122. If each device does not hold service history information, as described above, log data is acquired from each device, the acquired log data is analyzed to generate service history information, and the generated service history information May be stored in the information table 122.

  Next, based on the service history information stored in the information table 122, the prediction unit 123 calculates a predicted value that is a value predicted from the amount of consumables used in each device (step S104). Then, the prediction unit 123 calculates a service provisionable time for each service based on the calculated predicted value (step S105). Information on the predicted value and the service available time calculated by the prediction unit 123 is stored in the service information table 122.

  FIG. 4 is a flowchart illustrating an example of job execution control processing executed in the job execution control apparatus 100. The job execution control process shown in the flowchart of FIG. 4 is started with a job execution request from the user as a trigger.

  The user terminal used by the user displays a UI screen as shown in FIG. 19 according to display control by the UI presenting unit 111 of the job execution control apparatus 100. The user inputs a job execution request according to the UI screen on the user terminal. The job execution request input from the user terminal is notified to the job execution control apparatus 100 via the network NT.

  When the user execution request is notified from the user terminal, the service management unit 121 of the job execution control apparatus 100 first confirms the content of the job requested by the user (hereinafter referred to as “request job”). (Step S201). Then, the service management unit 121 is a service (for example, a color print service, a monochrome print service, a scan service, etc.) that matches the requested job among the devices on the network NT (image forming apparatuses A to E in the example of FIG. 1). Whether or not there is a device providing the service (hereinafter referred to as “service providing device”) (step S202).

  Here, when the service providing device does not exist on the network NT (step S202: NO), the UI screen as shown in FIG. 22, for example, is displayed by the user terminal according to the display control by the UI presenting unit 111 of the job execution control apparatus 100. Is displayed (step S203), and the user is notified that the requested job cannot be executed.

  On the other hand, if a service providing device exists on the network NT (step S202: YES), the service management unit 121 can execute a request job among the service providing devices (hereinafter, “job executable device”). ") Is detected. This process is a process of detecting, among service providing devices on the network NT, a device satisfying “the remaining amount of consumables at the current time” ≧ “the amount of consumables used by executing the request job”.

  That is, the service management unit 121 determines for each service providing device on the network NT whether there is a possibility that the requested job cannot be executed with the remaining amount of consumables at the current time (step S204). If the requested job can be reliably executed with the remaining amount of consumables (step S204: NO), the device is detected as a job executable device (step S205).

  Whether or not the service providing device on the network NT satisfies the above conditions can be determined using the contents of the request job and the service history information held in the information table 122.

  FIG. 5 is a diagram showing a specific example of service history information held in the information table 122. The job execution control apparatus 100 uses the service history information to indicate the usage amount of consumables such as the paper usage amount per day, the toner usage amount per day, and the staple usage amount per day for each user. Manage each device above. In addition to the above items, service consumables such as fixing oil, photoconductors, and waste toner bottles are all managed by service history information. Note that the service history information illustrated in FIG. 5 is service history information for the image forming apparatus A on the network NT. For each of the three users U1 to U3 who mainly use the image forming apparatus A, the service history information is as follows. Information such as daily paper usage, toner usage, and staple usage is stored.

  Here, a specific example of a method for determining whether the image forming apparatus A is a job executable device based on the remaining amount of toner, which is one of the consumables, using the service history information example of FIG. Will be described.

  The remaining amount of toner, which is one of the consumables in the image forming apparatus A, can be obtained as follows based on service history information as shown in FIG. The job execution control apparatus 100 acquires service history information similar to the history information illustrated in FIG. 5 from each of the other image forming apparatuses B to E on the network NT, and stores it in the information table 122. . Therefore, it is possible to determine whether or not the image forming apparatuses B to E are job executable apparatuses by the same method as described below.

  Taking the case of user U3 in FIG. 5 as an example, the total number of output pages per day by the print service is 350 pages, of which 90% are color prints and 10% are black and white prints. Therefore, the output number Pc per day of color printing by the user U3 is Pc = 350 × 0.9 = 315 pages, and the output number Pm per day of monochrome printing is Pm = 350 × 0.1 = 35. It becomes a page. The daily consumption of CMYK color toners of the user U3 is obtained by multiplying the above Pc and Pm by the weight according to the document type (see FIG. 8) and the weight according to the paper size to be used (see FIG. 9). It is proportional to the value (hereinafter referred to as “use amount index value”).

Here, assuming that the daily usage index value of CMY toner is TCc and the daily usage index value of K toner is TKc, these TCc and TKc can be calculated as follows. Note that TCc has the same value in CMY.
TCc = Pc × (weight by document type) × (weight by paper size)
TKc = (Pm + Pc) × (weight by document type) × (weight by paper size)

The user U3 has a document type of high resolution image: 100% and a paper size of A3 version: 100%.
TCc = 315 × 1.5 × 2.0 = 945
TKc = 350 × 1.5 × 2.0 = 1050
It becomes.

  The total sum (ΣTCi, ΣTKi) of the values of the above TCc and TKc for all end users U1 to U3 who use the image forming apparatus A is the actual amount of toner of each color of CMYK per day in the service providing device. Proportional to consumption.

Here, the actual toner consumption amount per day is the difference Δr (unit:%) between the actual measurement value of the remaining amount of toner one day before and the current actual measurement value. The ratios Ac and Ak between the actual toner consumption per day and the daily usage index value can be obtained as follows.
Ac = Δr_c / ΣTCi
Ak = Δr_k / ΣTKi

Since the actual toner remaining amount of the target service providing device can be obtained from the actual measured values Rnow_c and Rnow_k of the current toner remaining amount, an index of usable toner remaining amount is obtained from these Rnow_c and Rnow_k and Ac and Ak. The values TCr and TKr can be obtained as follows.
TCr = Rnow_c / Ac
TKr = Rnow_k / Ak

  On the other hand, the index value of the amount of toner consumed consumed by the requested job is predicted using the above calculation formulas for TCc and TKc based on the contents of the job (number of output sheets, document type, monochrome / color, paper size, etc.). be able to.

  Therefore, the requested job is executed by the image forming apparatus A by comparing the index values TCr and TKr of the remaining usable toner amount calculated as described above with the index value of the toner usage amount consumed in the requested job. It can be determined whether or not.

  The service management unit 121 of the job execution control apparatus 100 performs the above processing for all service providing devices on the network NT, and determines whether or not a job executable device exists on the NT (step S206). ). If the job executable device exists on the network NT (step S206: YES), the process proceeds to step S207.

  In step S207, the service management unit 121 determines whether there are a plurality of job executable devices on the network NT. If there is only one job executable device (step S207: NO), the job executable device is selected as a device that executes the requested job, and the service control unit 124 selects the selected device. A service execution request is output (step S209).

On the other hand, when there are a plurality of job executable devices on the network NT (step S207: YES), the service management unit 121 uses, for example, the following selection criteria 1 to 3, among the plurality of job executable devices. Then, one device for executing the requested job is selected (step S208). Then, the service control unit 124 outputs a service execution request to the selected device (step S209).
Selection criterion 1: The remaining amount of consumables at the present time is relatively large.
Selection criteria 2: The service available time at the present time is relatively long.
Selection criterion 3: The peak output time is far from the current time.

  Various methods are conceivable as a method for selecting one device based on the selection criteria 1 to 3 described above. For example, when the selection criteria 1 to 3 have a priority and one device that matches the selection criterion with a high priority can be specified, a method of selecting the device can be considered. Moreover, the method of judging the selection criteria 1-3 comprehensively and selecting the apparatus with high comprehensive evaluation can be considered. Note that the number of consumables necessary for executing the requested job is not limited to one. For example, when performing color printing, four types of toners of CMYK are necessary. In this case, the remaining amount of toner, which is a consumable item, and the length of service provision time must be selected in consideration of all four types of factors.

  Note that the device selection method described above is an example, and various methods other than the above-described example are conceivable as a method for selecting a device that executes a requested job from a plurality of job executable devices. For example, in the network NT, a method is conceivable in which a job executable device having a physical position closest to a user terminal used by a user who has input a job execution request is selected as a device that executes the requested job. In addition, a method is conceivable in which a device that consumes the least power per unit time among a plurality of job executable devices is selected as a device that executes a requested job. If a device that consumes less power per unit time is selected as the device that executes the requested job, it is possible to reduce the total cost of ownership (TCO) of the entire system.

  When it is determined in step S206 that there is no job executable device on the network NT (step S206: NO), the service management unit 121 next executes a device that can execute a part of the requested job (hereinafter, referred to as “job execution device”). "Job execution candidate device") is detected.

  That is, the service management unit 121 determines whether a part of the requested job can be executed with the current remaining amount of consumables for each service providing device (step S210), and the current consumable amount remaining If a part of the requested job can be executed (step S210: YES), the device is detected as a job execution candidate device (step S211).

  Next, the service management unit 121 determines whether or not all requested jobs can be executed with the combination of job execution candidate devices detected in step S211 (step S212). When all of the requested jobs cannot be executed with the combination of job execution candidate devices (step S212: NO), the user terminal follows the display control by the UI presenting unit 111 of the job execution control device 100, for example, as shown in FIG. A UI screen is displayed (step S203), and the user is notified that the requested job cannot be executed.

  In this case, a device with the least remaining amount of consumables is identified from among the service providing devices, and a message prompting the user to replenish consumables is displayed in the UI screen as shown in FIG. It is desirable to include it and display it on the user terminal. If the user replenishes consumables according to this message, the requested job can be executed only by the device, and the distribution of useless services can be suppressed.

  On the other hand, when all of the requested jobs can be executed by the job execution candidate device (step S212: YES), the service management unit 121 uses the selection criteria 1 to 3 described above to execute the requested job, for example. A combination of devices is selected (step S213). Then, the service control unit 124 outputs a service execution request to the selected device (step S214).

  Various methods are conceivable as a method of selecting a combination of job execution candidate devices that execute a requested job based on the above selection criteria 1 to 3. For example, priority is given to selection criteria 1 to 3, and job execution candidate devices are sequentially selected in descending order of priority, and the total remaining amount of consumables is greater than or equal to the amount of consumable consumption consumed by the requested job. If it becomes, the method of selecting the combination of those apparatuses can be considered. Moreover, the method of judging the selection criteria 1-3 comprehensively and selecting the combination of apparatus with high comprehensive evaluation can be considered. Note that the number of consumables necessary for executing the requested job is not limited to one. For example, when performing color printing, four types of toners of CMYK are necessary. In this case, the remaining amount of toner, which is a consumable item, and the length of service provision time must be selected in consideration of all four types of factors.

  Here, an example of a method of selecting a combination of job execution candidate devices that execute a requested job will be described in detail, taking as an example the case where the image forming apparatuses A to C are detected as job execution candidate devices. . In the example shown below, the requested job is color print, and the consumable is YMCK toner. The remaining amount of toner in the image forming apparatuses A to C is calculated from the output history per unit time (monochrome print: Nm, color print: Nc).

<Image forming apparatus A>
C Toner: Toner remaining amount 10% (Toner remaining amount index value: 500), Service available time: 1.0 hour M Toner: Toner remaining amount 40% (Toner remaining amount index value: 2000), Service available Time: 7.0 hours Y toner: toner remaining amount 20% (toner remaining amount index value: 1000), service available time: 4.5 hours K toner: toner remaining amount 100% (toner remaining amount index value: 50000), service available time: 30.0 hours <Image forming apparatus B>
C toner: toner remaining amount 20% (toner remaining amount index value: 1000), service available time: 5.0 hours M toner: toner remaining amount 30% (toner remaining amount index value: 2000), service available Time: 6.0 hours Y toner: toner remaining amount 25% (toner remaining amount index value 1500), service available time: 5.5 hours K toner: toner remaining amount 15% (toner remaining amount index value: 1000), service available time: 2.0 hours <Image forming apparatus C>
C toner: remaining toner amount 30% (toner remaining index value: 2000), service available time: 5.0 hours M toner: toner remaining amount 10% (toner remaining index value: 500), service available Time: 1.0 hour Y toner: toner remaining amount 25% (toner remaining amount index value: 500), service available time: 1.0 hour K toner: toner remaining amount 10% (toner remaining amount index value: 500), Service available time: 1.0 hour

  Focusing only on the K toner, the image forming apparatus A has the longest remaining amount of K toner and the service available time among the image forming apparatuses A to C. However, since the requested job is color printing, all the CMYK toners are required to execute the requested job, and it is necessary to consider the remaining amount of all CMYK toners and the service available time. Considering all of CMYK, it can be seen that the remaining amount of toner and the service available time of the image forming apparatus B are long. Therefore, in this case, in all of CMYK, the image forming apparatus B having a long remaining toner amount and service available time is selected as a main processing apparatus, and the remaining toner is more than the image forming apparatus B as an apparatus that performs the remaining processing. The image forming apparatus A having a long amount and a long service providing time is selected.

  Note that the device selection method described above is an example, and various methods other than the above-described example are conceivable as a method for selecting a combination of job execution candidate devices that execute a requested job. For example, in the network NT, a method of selecting a combination of job execution candidate devices whose physical positions are close to each other is also conceivable. A method of preferentially selecting job execution candidate devices that consume less power per unit time is also conceivable. If a device that consumes less power per unit time is selected as the device that executes the requested job, it is possible to reduce the total cost of ownership (TCO) of the entire system.

  When the request job is executed by one device or distributed to a plurality of devices, as described above, the service control unit 124 selects the device selected as the device that executes the request job. A service execution request is output (step S209, step S214).

  When the service is executed by the device that has received the service execution request, status information to that effect is transmitted to the job execution control apparatus 100, and is displayed on the user terminal according to display control by the UI presenting unit 111 of the job execution control apparatus 100. For example, a UI screen as shown in FIG. 20 is displayed, and the user is notified that the requested job has been executed (step S215).

  Note that the predicted value calculation process shown in the flowchart of FIG. 3 is periodically executed at predetermined intervals, and the job execution control process shown in the flowchart of FIG. 4 is executed using a job execution request from the user as a trigger. The process shown in the flowchart of FIG. 3 and the process shown in the flowchart of FIG. 4 operate in parallel in the job execution control apparatus 100.

  Next, the predicted value calculated by the prediction unit 123 and the service available time will be described in detail with specific examples.

  As described above, the predicted value is a value obtained by predicting the amount of consumables used in each device. In the following, a predicted value (hereinafter referred to as “toner predicted value”) of the amount of toner used as consumables common to the image forming apparatuses A to E is calculated, and a service can be provided based on the toner predicted value. A case where time is calculated will be described as an example. It should be noted that the remaining amount of toner at the present time in each device can be determined from the predicted toner value calculated by the prediction unit 123. In other words, as described above, the toner management value calculated by the prediction unit 123 and the information on the service availability time are executed by the service management unit 121 from among a plurality of job executable devices or job execution candidate devices. It can be used as a reference for selecting a device.

  The predicted toner value and service available time can be calculated based on the service history information stored in the information table 122. As described above, the service history information includes information indicating the usage amount of consumables such as the paper usage amount (per day), the toner usage amount (per day), and the staple usage amount (per day) for each user. include. Based on the service history information, the prediction unit 123 of the job execution control apparatus 100 calculates a predicted toner value and a service available time for each device on the network NT by the following method.

  Assuming that the average amount of toner used at one time is X (the amount of toner consumed by one predefined printing), the predicted toner value is the average amount of toner used X and a history value (history information for each user). : Peak output time / number of output sheets, document type, black / white / color, paper size, etc.).

  FIG. 6 is a flowchart illustrating an example of processing for calculating a predicted toner value.

  The prediction unit 123 first calculates individual weight values based on the history values for each user included in the service history information (step S301). Here, the individual weight values are weight values corresponding to individual history values such as the number of output sheets (per day), document type, and paper size included in the service history information shown in FIG. Based on these history values included in the service history information and the information shown in FIGS. 7 to 9 (information indicating the correspondence between individual history values and weight values), the prediction unit 123 determines the individual weight values. Is calculated. For the document type and paper size, when the history value has a plurality of values at a certain ratio, the weight value is calculated by proportional distribution according to the ratio. For example, when the paper size history values are A3: 70% and A4: 30%, the weight value corresponding to the paper size is 2.0 × 30/100 + 1.0 × 70/100.

  Next, the prediction unit 123 multiplies the individual weight values calculated in step S301 to calculate the entire weight value (step S302). For example, if the weight value corresponding to the output number (per day) is W1, the weight value corresponding to the document type is W2, and the weight value corresponding to the paper size is W3, the history value of the output number (per day) is obtained. When the history value of 100 sheets, the document type history value is a high-resolution image, and the paper size history value is A3: 100%, W1 = 1.0, W2 = 1.5, and W3 = 2.0 are calculated in step S301. The Assuming that the individual weight values calculated in step S301 are only W1, W2, and W3, the overall weight value Wa is Wa = 1.0 × 1.5 × 2.0 = 3.0. .

  Next, the prediction unit 123 determines the average toner usage amount X according to the user's output method included in the service history information, that is, only monochrome printing, only color printing, or a mixture of monochrome printing and color printing. A toner predicted value is calculated by multiplying the entire weight value Wa (steps S303 to S308).

That is, in step S303, the prediction unit 123 determines whether or not the user's output method is only monochrome printing (step S303: YES). In step S304, the prediction unit 123 applies K toner as described below. Only for this, the average toner usage amount X is multiplied by the weight value Wa, and the result is used as the predicted toner value (step S308).
<For black and white printing only>
K toner usage = Wa x X
C toner consumption = 0.0 × X
M toner usage = 0.0 × X
Y toner usage = 0.0 × X

On the other hand, when the user's output method is not only monochrome printing (step S303: NO), the prediction unit 123 determines whether or not the user's output method is only color printing in step S305. (Step S305: YES) In step S306, the average toner usage amount X is multiplied by the weight value Wa for all KCMY toners as described below, and the result is used as the predicted toner value (step S308).
<For color printing only>
K toner usage = Wa x X
C Toner consumption = Wa x X
M toner usage = Wa × X
Y toner usage = Wa × X

On the other hand, when the user's output method is not only the color print (step S305: NO), that is, when the monochrome print and the color print are mixed, the prediction unit 123 responds to the ratio between the black and white print and the color print in step S307. The weight value (Wcmy) for CMY toners is calculated by multiplying the average toner usage amount X for K toner by the weight value Wa and the average toner usage amount X for CMY toner by the weight value Wcmy, as shown below. Is a toner predicted value (step S308).
<In the case of mixed monochrome and color prints>
Color print z%, black and white print (100-z)%
Wcmy = Wa × z / 100
K toner usage = Wa x X
C toner usage = Wcmy × X
M toner usage = Wcmy × X
Y toner usage = Wcmy × X

  FIG. 10 is a diagram illustrating weight values for the users U1 to U3 calculated using the service history information illustrated in FIG. 10A corresponds to the user U1, FIG. 10B corresponds to the user U2, and FIG. 10C corresponds to the user U3.

  As shown in FIG. 10A, the weight value W1 corresponding to the number of output sheets (per day) corresponding to the user U1 is 6.0, the weight value W2 corresponding to the document type is 1.0, and corresponds to the paper size. The weight value W3 to be calculated is 1.3. Therefore, the overall weight value Wa corresponding to the user U1 is Wa = 6.0 × 1.0 × 1.3 = 7.8. Further, since the output method of the user U1 is only monochrome printing, the predicted toner values corresponding to the user U1 are K toner: 7.8 × X, C toner: 0, M toner: 0, and Y toner: 0. .

  As shown in FIG. 10B, the weight value W1 corresponding to the number of output sheets (per day) corresponding to the user U2 is 8.0, the weight value W2 corresponding to the document type is 1.0, and corresponds to the paper size. The weight value W3 to be used is 1.0. Therefore, the overall weight value Wa corresponding to the user U2 is Wa = 8.0 × 1.0 × 1.0 = 8.0. Further, since the output method of the user U2 is only color printing, the predicted toner values corresponding to the user U2 are K toner: 8.0 × X, C toner: 8.0 × X, M toner: 8.0 ×. X, Y toner: 8.0 × X.

  As shown in FIG. 10C, the weight value W1 corresponding to the number of output sheets (per day) corresponding to the user U3 is 4.0, the weight value W2 corresponding to the document type is 1.5, and corresponds to the paper size. The weight value W3 to be used is 2.0. Therefore, the overall weight value Wa corresponding to the user U3 is Wa = 4.0 × 1.5 × 2.0 = 12.0. The output method of the user U3 is a mixture of black and white print (10%) and color print (90%), and the weight Wcmy for CMY toner is Wcmy = 12.0 × 90/100 = 10.8. Therefore, the predicted toner values corresponding to the user U3 are K toner: 12.0 × X, C toner: 10.8 × X, M toner: 10.8 × X, and Y toner: 10.8 × X.

  The specific example of the prediction value calculation by the prediction unit 123 has been described by taking the toner prediction value as an example. The prediction value calculated in this way indicates how long the service can be used on the time axis. It is the service available time. Hereinafter, an example of a method for calculating the service provisionable time will be described in detail by taking as an example a case where the predicted value calculated by the predicted value 123 is a predicted toner value.

FIG. 11 is a plot of the toner remaining amount history (actually measured values) in a certain device on the network NT on the time axis. FIG. 12 shows a toner consumption prediction curve L1 calculated based on the above-described toner prediction value. As in the example of the service history information illustrated in FIG. 5, the prediction curve L <b> 1 is calculated based on the predicted toner value for each user who uses a device when three users are using one device. The In the case of the example shown in FIG. 12, the prediction curve L1 of K toner consumption is calculated based on the toner prediction values related to the K toners of the three users U1 to U3 for the time after May 2, 2010. . As the user's device usage increases, an appropriate weight is calculated, and the accuracy of the prediction curve L1 is improved. Here, if the number of users using the device a, the average of the weights of all the users using the apparatus and W _A, prediction curve L1 is expressed by the following equation.
W _A × X × a = Δr

Here, W _A × X represents a toner usage average daily per user, [Delta] r represents the slope of the prediction curve L1 (% / day). Note that X represents the average amount of toner used once as described above, but the value of X can be calculated based on the history value included in the service history information and can be adjusted. It is. The curve that decreases linearly with the slope Δr is the prediction curve L1.

  FIG. 13 is a graph showing the peak output time for each of the three users U1 to U3. FIG. 14 is obtained by reflecting the peak output time of FIG. 13 on the prediction curve L1 shown in FIG. The prediction curve L2 is shown. Since the prediction curve L1 considers only the amount of toner used per day, there may be cases where sufficient prediction accuracy cannot be ensured. However, the prediction curve L2 shown in FIG. Therefore, the toner consumption increases during a time period when the output from the user is large, and conversely, the toner consumption tends to decrease during a time period when the output from the user is small. Compared with the prediction curve L1, the prediction accuracy is increased. Can be increased. The prediction curve L2 shown in FIG. 14 indicates that the toner consumption is lower than the prediction curve L1 in the time zone between 7:00 and 8:00 on May 2, 2010. In FIG. 14, only the prediction curve L2 related to the amount of Y toner used by the user U3 is shown, but finally, the amount of toner used by the three users U1 to U3 is added together for each toner of KCMY. Thus, a prediction curve L2 for each device is derived.

  FIG. 15 is a plot of the prediction curve L1 and the prediction curve L2 on a longer time axis than that of FIG. Along with the prediction curve L1 and the prediction curve L2, a time when the remaining amount of toner is 0% is a toner prediction end time, and a time until the toner end prediction time is a service available time. Here, since the prediction curve L2 is predicted on a daily basis, the toner prediction end time obtained from the prediction curve L2 is more accurate than the toner prediction end time obtained from the prediction curve L1.

  Next, an example will be described in which a predicted value of the amount of staple used as one of the consumables (hereinafter referred to as “staple predicted value”) is calculated as a predicted value.

  Assuming that the average staple usage amount at one time is X ′ (the staple amount used in one printing operation defined in advance), the staple predicted value is included in the average staple usage amount X ′ and the service history information. It can be obtained by using a weight corresponding to a history value of staple usage (per day).

  FIG. 16 is a flowchart illustrating an example of processing for calculating a predicted staple value.

  The prediction unit 123 first uses the staple value for each user included in the service history information and the information shown in FIG. 17 (information indicating the correspondence between the history value related to the staple usage amount and the weight value). A weight value Ws for the quantity is calculated (step S401). Next, the prediction unit 123 multiplies the average staple usage amount X ′ by the weight value Ws (step S402), and sets the result as the staple predicted value (step S403).

  FIG. 18 is a diagram illustrating weight values for the staple usage amount for each of the users U1 to U3 calculated using the service history information illustrated in FIG. 18A corresponds to the user U1, FIG. 18B corresponds to the user U2, and FIG. 18C corresponds to the user U3.

  Since the history value for the staple usage amount of the user U1 is 0, the weight value Ws for the staple usage amount corresponding to the user U1 is 0 as shown in FIG. Therefore, the predicted staple value corresponding to the user U1 is 0.

  Since the history value for the staple usage amount of the user U2 is 4, the weight value Ws for the staple usage amount corresponding to the user U2 is 1.0 as shown in FIG. Therefore, the predicted staple value corresponding to the user U2 is 1.0 × X ′.

  Since the history value for the staple usage amount of the user U3 is 12, the weight value Ws for the staple usage amount corresponding to the user U3 is 3.0 as shown in FIG. Therefore, the predicted staple value corresponding to the user U3 is 3.0 × X ′.

  Note that the prediction unit 123 can also obtain a predicted paper value that is a value obtained by predicting the amount of paper used as one of the consumables by the same method as described above. Further, the prediction unit 123 can also calculate the service available time based on the staple predicted value and the paper predicted value by the same method as the method of calculating the service available time based on the toner predicted value.

  Finally, a specific example of a UI screen displayed on the user terminal by display control by the UI presenting unit 111 will be described.

  FIG. 19 is a diagram illustrating an example of a UI screen for a user to input a job execution request. In this UI screen, various input means for specifying the contents of the job are provided. The user selects “Distributed Optimal Printing System” from the UI screen shown in FIG. 19 displayed on the user terminal, and selects each of “Color / Finish”, “Printing Range”, and “Print Copies” items. After inputting the above, a job execution request can be input by pressing the “print” button.

  FIG. 20 is a diagram illustrating an example of a UI screen displayed on the user terminal when the requested job is executed normally. On this UI screen, information indicating that the requested job (printing in the example of FIG. 20) has been completed and the position of the device that executed the requested job are displayed. The user can confirm the completion of the requested job and the position of the device that executed the requested job by referring to the UI screen shown in FIG. 20 displayed on the user terminal.

  FIG. 21 is a diagram illustrating an example of a UI screen displayed on the user terminal when the requested job cannot be executed. On this UI screen, information indicating that the requested job cannot be executed and information for designating a device to which a consumable item (K toner in the example of FIG. 20) should be replenished are displayed. By referring to the UI screen shown in FIG. 21 displayed on the user terminal, the user confirms that the requested job cannot be executed and which device should be supplied with consumables to execute the requested job. can do.

  FIG. 22 is a diagram illustrating an example of a UI screen displayed on the user terminal when there is no service providing device corresponding to the requested job. By referring to the UI screen as shown in FIG. 22 displayed on the user terminal, the user can confirm that the service providing device corresponding to the requested job does not exist on the network NT.

  As described above in detail with specific examples, in the image forming system according to the present embodiment, the job execution control apparatus 100 connected to the network NT together with the plurality of image forming apparatuses A to E includes: For each of the plurality of image forming apparatuses A to E on the network NT, an information table 122 that stores service history information that represents a history of consumption of consumables for each user who uses each image forming apparatus, and an information table 122 are stored. A prediction unit 123 that calculates a predicted value that is a predicted value of the amount of consumables used in the plurality of image forming apparatuses A to E, and history information and prediction unit 123 held by the information table 122 based on the history information An image forming apparatus that executes a requested job requested by the user among the plurality of image forming apparatuses A to E based on the calculated predicted value. A service management unit 121 for selecting, and a.

  Accordingly, the job execution control apparatus 100 accurately predicts the state of consumables of the image forming apparatuses A to E on the network NT, and appropriately selects an image forming apparatus that executes the requested job requested by the user. Can do. As a result, a service desired by the user can be efficiently realized as the entire image forming system, and a highly convenient system can be realized.

  The job execution control apparatus 100 according to the present embodiment includes, as an example, a control device such as a CPU, a storage device such as a ROM and a RAM, an external storage device such as an HDD and a CD drive device, and a display device. A display device and an input device such as a keyboard and a mouse are provided, and a hardware configuration using a normal computer is employed.

  The job execution control program executed by the job execution control apparatus according to the present embodiment is, for example, a file in an installable format or an executable format, such as a CD-ROM, a flexible disk (FD), a CD-R, a DVD ( The program is recorded on a computer-readable recording medium such as Digital Versatile Disc).

  Further, the job execution control program executed by the job execution control apparatus according to the present embodiment is stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Also good. Further, the job execution control program executed by the job execution control apparatus according to the present embodiment may be configured to be provided or distributed via a network such as the Internet.

  Further, the job execution control program according to the present embodiment may be provided by being incorporated in advance in a ROM of a computer used as the job execution control apparatus 100.

  The job execution control program executed by the job execution control apparatus 100 according to the present embodiment has a module configuration including the above-described units (service management unit 121, information table 122, prediction unit 123, service control unit 124). As actual hardware, a CPU (processor) reads out and executes a job execution control program from the recording medium, so that the above-described units are loaded on the main storage device, and a service management unit 121, an information table 122, a prediction unit 123, the service control unit 124 is generated on the main storage device.

  The embodiment described above shows a preferred application example of the present invention, and the technical scope of the present invention is not limited to the technical matter disclosed as the above embodiment as it is. The technical scope of the present invention includes modifications, alternative means, and the like that are easily derived by adding technical common sense to the technical matters disclosed as the above embodiments.

DESCRIPTION OF SYMBOLS 100 Job execution control apparatus 121 Service management part 122 Information table 123 Prediction part 124 Service control part AE Image forming apparatus NT Network

JP 2005-100229 A JP 2003-186649 A JP 2009-140012 A

Claims (13)

A job execution control device connected to a network together with a plurality of devices and controlling execution of a job requested by a user,
For each of the plurality of devices, holding means for holding history information that represents a history of consumable usage for each user who uses each device;
Calculation means for calculating a predicted value that is a value predicted from the consumption information of the consumables in the plurality of devices based on the history information;
Selecting means for selecting a device that executes the job from the plurality of devices based on the history information and the predicted value ;
The calculation means obtains, as the predicted value, a value obtained by multiplying an average value of consumable consumption when executing one job by a weight corresponding to a history of consumable consumption included in the history information. calculated to the job execution control device according to claim Rukoto. The selection unit detects a device that can execute all of the jobs among the plurality of devices, and detects when a plurality of devices that can execute all of the jobs are detected. among the plurality of devices, the job execution control device according to claim 1, characterized in that supply levels estimated from the predicted value of the largest instrument, selecting a device to perform the job. The selection unit detects a plurality of devices that can execute a part of the job from the plurality of devices when a device that can execute all of the jobs cannot be detected, and detects the devices. 3. The job execution control according to claim 2 , wherein among the plurality of devices, a combination of devices having a large amount of remaining consumables estimated from the predicted value is selected as a combination of devices that execute the job. apparatus. The selection unit detects a device that can execute all of the jobs among the plurality of devices, and detects when a plurality of devices that can execute all of the jobs are detected. among the plurality of devices, said longest instrument time to consumables predicted completion time calculated from the predicted value, the job execution control according to claim 1, characterized by selecting as the device that performs the job apparatus. The selection unit detects a plurality of devices that can execute a part of the job from the plurality of devices when a device that can execute all of the jobs cannot be detected, and detects the devices. among the plurality of apparatus to which, according to claim 4, characterized in that the time until the calculated from the predicted value consumables predicted end time of the combination of long device, selects as the combination of devices to perform the job Job execution control device. The history information includes a peak time, which is information for identifying a time zone in which consumables are frequently used for each user,
The selection unit detects a device that can execute all of the jobs among the plurality of devices, and detects when a plurality of devices that can execute all of the jobs are detected. among the plurality of devices, the job execution control device according to claim 1, wherein the peak time is a device that is farthest from the current time, and selecting as the device that performs the job. The selection unit detects a plurality of devices that can execute a part of the job from the plurality of devices when a device that can execute all of the jobs cannot be detected, and detects the devices. The job execution control apparatus according to claim 6 , wherein among the plurality of devices, a combination of devices having the peak time apart from the current time is selected as a combination of devices that execute the job.   A message output means for outputting a message prompting the user to replenish a consumable with a device having the least amount of consumables among the plurality of devices when the selection means cannot select a device for executing the job; The job execution control apparatus according to claim 1, further comprising: The plurality of devices are image forming apparatuses,
2. The job execution according to claim 1, wherein the history information includes information on a total number of output sheets per day for each user, information indicating whether the output format is black and white or color, and information on a used paper size. Control device. The job execution control apparatus according to claim 9 , wherein the history information further includes staple usage information. An image forming system in which a plurality of image forming apparatuses and a job execution control apparatus that controls execution of a job requested by a user are connected to a network.
The job execution control device is
For each of the plurality of image forming apparatuses, a holding unit that holds history information indicating a history of consumption of consumables for each user who uses each image forming apparatus;
A calculation unit that calculates a predicted value that is a value predicted from the consumption amount of the consumables in the plurality of image forming apparatuses based on the history information;
Selecting means for selecting an image forming apparatus that executes the job among the plurality of image forming apparatuses based on the history information and the predicted value ;
The calculation means obtains, as the predicted value, a value obtained by multiplying an average value of consumable consumption when executing one job by a weight corresponding to a history of consumable consumption included in the history information. calculated to the image forming system according to claim Rukoto. A job execution control method for controlling execution of a job requested by a user,
Obtaining history information representing a history of consumption of consumables for each user who uses each device from each of a plurality of devices connected to the network;
Based on the history information, calculating a predicted value that is a predicted value of the amount of consumables used in the plurality of devices;
Based on the history information and the predicted value, it looks including the steps of: selecting a device to perform the job of the plurality of devices,
In the step of calculating the predicted value, a value obtained by multiplying an average value of consumable consumption when executing one job by a weight according to a history of consumable consumption included in the history information, A job execution control method, wherein the job execution control method calculates the predicted value . To a computer connected to a network with multiple devices,
For each of the plurality of devices, a function of holding history information representing a history of the amount of consumables used for each user who uses each device;
Based on the history information, a function of calculating a predicted value that is a value predicted from the consumption amount of the consumables in the plurality of devices;
Based on the history information and the predicted value, realizing a function of selecting a device that executes a job requested by a user from among the plurality of devices ,
The function for calculating the predicted value is a value obtained by multiplying an average value of consumable consumption when executing one job by a weight according to a history of consumable consumption included in the history information, job execution control program characterized that you calculated as the predicted value.

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