Image processing device, control method thereof, and program

Abstract

The present invention provides a technique that can suppress the discrepancy between predicted lifetime values ​​before and after a component lifetime prediction algorithm in an image processing device is replaced. [Solution] The image processing apparatus comprises an acquisition unit that acquires a first wear level predicted using an algorithm before the algorithm predicts the wear level of the components of the image processing apparatus is replaced, and a prediction unit that predicts a second wear level after the algorithm is replaced, the prediction unit predicting the second wear level using the first wear level acquired by the acquisition unit and at least one of the algorithms before and after the replacement.

Description

[Technical Field]

[0001] The present invention relates to an image processing apparatus, a control method therefor, and a program. [Background Art]

[0002] A life determination system has been proposed which updates a life determination algorithm by distributing the life determination algorithm from a server to a machine via a network, and performs determination of consumable parts using the updated life determination algorithm (Patent Document 1). Such a life determination system includes an industrial machine that performs life determination of consumable parts using the life determination algorithm, and a server that manages original data of the life determination algorithm. Then, when the original life determination algorithm is updated, the server transmits the updated life determination algorithm to the industrial machine via the network. The industrial machine receives the updated life determination algorithm and performs life determination of consumable parts using the life determination algorithm. According to such a system, the reliability of life determination for consumable parts of a machine can be improved. [Prior Art Documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Laid-Open No. 2024-135276 [Summary of the Invention] [Problem to be Solved by the Invention]

[0004] It is conceivable to apply the technology described in Patent Document 1 to an image processing device to predict the lifespan of components mounted in the image processing device. Furthermore, it is conceivable to update the prediction algorithm (hereinafter referred to as the component lifespan prediction algorithm, or simply the algorithm) and improve the calculation accuracy based on new training data. In such a case, the algorithm used to predict the state of components mounted in an image processing device is replaced with an algorithm with improved calculation accuracy using software distribution means such as a firmware update for image processing devices used in the market. However, the replaced algorithm may be a new algorithm with significantly improved calculation accuracy, or it may be an algorithm that adds the calculated lifespan value to the previous lifespan value each time it is replaced. In such cases, there may be a large difference between the lifespan value of the component estimated by the component state prediction algorithm before the algorithm replacement and the lifespan value of the component estimated after the algorithm replacement, resulting in a lack of continuity between the lifespan values ​​before and after the replacement, and a discrepancy may occur. Therefore, it may impair the reliability of the lifespan value estimation results for users such as service technicians and operators who refer to the lifespan value when performing tasks such as component replacement.

[0005] The present invention has been made in view of at least one of the above-mentioned problems, and provides a technology that can suppress the discrepancy between predicted lifetime values ​​before and after replacement when the component lifetime prediction algorithm of an image processing device is replaced. [Means for solving the problem]

[0006] According to one aspect of the present invention, An acquisition unit that acquires a first wear level predicted using the algorithm before replacing the algorithm that predicts the wear level of the components of the image processing device, A prediction unit for predicting a second degree of wear after replacing the algorithm, comprising: the prediction unit predicting the second degree of wear using the first degree of wear acquired by the acquisition unit and at least one of the algorithms before and after the replacement, It is an image processing device. [Effects of the Invention]

[0007] According to the present invention, when the component life prediction algorithm of an image processing device is replaced, the discrepancy between the predicted life values ​​before and after the replacement can be suppressed. [Brief explanation of the drawing]

[0008] [Figure 1] Hardware configuration diagram of a component life prediction system according to one embodiment. [Figure 2] Software configuration diagram of a component life prediction system according to one embodiment. [Figure 3] Block diagram of a data collection and transmission module according to one embodiment. [Figure 4] Block diagram of a prediction calculation module according to one embodiment. [Figure 5] Block diagram of a prediction result transmission module according to one embodiment. [Figure 6] Figure showing a display screen according to one embodiment. [Figure 7] Flowchart of the process according to one embodiment [Figure 8] Flowchart of the process according to one embodiment [Figure 9] Flowchart of the process according to one embodiment [Figure 10] Flowchart of the process according to one embodiment [Figure 11] Flowchart of the process according to one embodiment [Figure 12] Flowchart of the process according to one embodiment [Modes for carrying out the invention]

[0009] The embodiments will be described in detail below with reference to the attached drawings. Note that the following embodiments do not limit the invention to the claims. While the embodiments describe multiple features, not all of these features are essential to the invention, and the features may be combined in any way. Furthermore, in the attached drawings, the same or similar components are given the same reference numeral, and redundant descriptions are omitted. Also, the lifespan values ​​of the components in the following embodiments indicate, for example, the degree of wear of the components.

[0010] <Embodiment> (System Configuration) This section describes a component life prediction system according to this embodiment. Here, an application running on an image processing device is used as an example of a component life prediction system. Furthermore, an image forming apparatus is used as an example of a network device that the component life prediction system is intended to diagnose. An MFP (Multifunction Peripheral, i.e., a multifunction device) is used as an example of an image forming apparatus. Note that network devices also include devices other than MFPs, such as printers and fax machines.

[0011] Figure 1 will be used to illustrate the system configuration and hardware configuration of the component life prediction system 10 according to this embodiment. The component life prediction system 10 is comprised of a software distribution server 100, a client computer 120, an algorithm analysis and generation server 140, and an MFP 150, all connected by a network 170. Here, the configuration of the general-purpose computers that make up the software distribution server 100 and the algorithm analysis and generation server 140 is realized, for example, by utilizing hardware resources supplied on demand using virtualization technology. Note that the number of MFP 150s is not limited to one, but may be two or more.

[0012] The software distribution server 100 includes a CPU 101, a RAM 102, a ROM 103, and a network I / F 104. The software distribution server 100 further includes a keyboard I / F 105, a display I / F, an external memory I / F 107, a keyboard 108, a display 109, an external memory 110, and a system bus 111.

[0013] The CPU 101 executes processing based on application programs and the like stored in the ROM 103 or the external memory 110. Furthermore, the CPU 101 generally controls each hardware module connected to the system bus 111. In addition, the CPU 101 opens various registered windows and executes various data processing based on a command instructed by an unshown mouse cursor or the like on the display 109.

[0014] The RAM 102 functions as a main memory, a work area and the like for the CPU 101. The ROM 103 is a read-only memory that functions as a storage area for a basic I / O program and the like. The ROM 103 or the external memory 110 stores an operating system program (hereinafter referred to as OS), which is a control program for the CPU 101, and the like. Furthermore, the ROM 103 or the external memory 110 stores files and various other data used during processing based on the aforementioned application programs and the like.

[0015] The network I / F 104 is configured to include a communication module such as a network card, and connects the software distribution server 100 to the network 170 so that network communication is enabled. The keyboard I / F 105 controls inputs from the keyboard 108 and an unillustrated pointing device. The display I / F 106 controls display on the display 109. The external memory 110 is, for example, an external memory such as a hard disk drive (HDD) or a solid-state drive (SSD), and stores a boot program, various applications, user files, editing files, and the like. The external memory I / F 107 controls access to the external memory 110.

[0016] The software distribution server 100 operates in a state where the CPU 101 executes a basic I / O program and an OS written in the ROM 103 or the external memory 110. The basic I / O program is written in the ROM 103, and the OS is written in the ROM 103 or the external memory 110. Then, when the software distribution server 100 is powered on, the OS is written from the ROM 103 or the external memory 110 to the RAM 102 by the initial program load function in the basic I / O program, and the operation of the OS is started.

[0017] The system bus 111 connects each component of the software distribution server 100. Note that hardware resources such as the CPU 101, the ROM 103, and the external memory 110 that constitute the software distribution server 100 are supplied on demand by, for example, virtualization technology. In this way, the software distribution server 100 is configured as a virtual server on a cloud computing environment.

[0018] The client computer 120 and the algorithm analysis generation server 140 include, for example, the configuration of a general-purpose computer. Since the hardware configuration of these is the same as that of the software distribution server 100 described above, description thereof is omitted.

[0019] The MFP150 comprises a network interface 151, a CPU 152, RAM 153, and ROM 154. The MFP150 also comprises an operation interface 155, an operation unit 156, a printer interface 157, and a printer 158. Furthermore, the MFP150 comprises a scanner interface 159, a scanner 160, an external memory interface 161, an external memory 162, and a system bus 163.

[0020] The network interface 151 includes a communication module, such as a network card, and connects the MFP 150 to the network 170, enabling network communication. The CPU 152 outputs an image signal as output information to the printer 158 via the printer interface 157 connected to the system bus 163, based on a control program. The control program is stored in the ROM 154 or external memory 162. The CPU 152 is configured to communicate with an external computer via the network interface 151. That is, the CPU 152 is configured to notify the software distribution server 100 and the algorithm analysis and generation server 140 of information within the MFP 150. Furthermore, the CPU 152 executes processing based on application programs stored in the ROM 154 or external memory 162.

[0021] RAM153 functions as the main memory and work area of ​​CPU152, and is configured to allow memory capacity expansion by optional RAM connected to an expansion port (not shown). RAM153 is used for output information expansion area, environment data storage area, and NVRAM, etc.

[0022] ROM 154 or external memory 162 stores control programs and application programs for the CPU 152, font data used when generating the above output information, information used on the MFP 150, etc. External memory 162 is a storage medium such as a hard disk drive (HDD), SSD (Solid State Drive), or IC card.

[0023] The operation unit 156 is, for example, an operation panel equipped with switches and LED indicators for operation. The operation unit 156 may also include, for example, a touch panel display. The operation unit I / F 155 is an interface with the operation unit 156 and outputs image data to be displayed to the operation unit 156. It also receives information input by the user via the operation unit 156.

[0024] The printer interface 157 outputs an image signal as output information to the printer 158 (printer engine). The scanner interface 159 receives an image signal as input information from the scanner 160 (scanner engine). The external memory interface 161 (memory controller) controls access to the external memory 162. Furthermore, the number of external memories is not limited to one. The MFP 150 may include at least two external memories 162 and be configured to allow connection of multiple external memories. In addition, the MFP 150 may be configured to include an NVRAM (not shown) and may store printer mode setting information input from the operation unit 156 in the NVRAM. The system bus 163 connects each component that makes up the MFP 150.

[0025] The software blocks of the component life prediction system 10 will be explained using Figure 2. First, the software configuration of the software distribution server 100 will be explained. In the software distribution server 100, the network device diagnostic application and each module exist as files stored in external memory 110. These are program modules that are loaded into RAM 102 and executed at runtime by the OS and modules that utilize them. Furthermore, the network device diagnostic application can be added to the HDD or SSD of the external memory 110, which is supplied on demand using virtualization technology in a cloud computing environment.

[0026] More specifically, the software distribution server 100 includes a network module 200, a web server service module 201, a software distribution application 202, and a database service module 210. Furthermore, the software distribution application 202 includes a UI module 203, a device management module 204, and a distribution management module 207.

[0027] The network module 200 communicates with the client computer 120 and the MFP 150 over the network using any communication protocol. The web server service module 201 provides a service that responds to HTTP requests received from the web browser 221 (described later) on the client computer 120. As an example of the HTTP response, it may return web page data stored in external memory 110. The software distribution application 202 is an application that enables algorithm updates by distributing software to the MFP 150, which is connected to the software distribution server 100 via the network 170.

[0028] The software distribution application 202 is implemented as a program that processes requests to web pages provided by, for example, the web server service module 201. As described above, the software distribution application 202, together with the web server service module 201, realizes a web application that enables algorithm updates by distributing software to the MFP150. The distributed software here is, for example, mainly the firmware program for the MFP150. The database service module 210 stores the firmware incorporating the learning model data obtained through retraining.

[0029] Next, the software configuration of the client computer 120 will be described. Each module that makes up the client computer 120 is a program module that exists as a file stored in ROM 103 or external memory 110. At runtime, it is loaded into RAM 102 and executed by the OS or the module that uses it.

[0030] More specifically, the client computer 120 includes a network module 220, a web browser 221, and a printer driver 222. The network module 220 communicates with the software distribution server 100 and MFP 150 over the network using any communication protocol. The web browser 221 sends HTTP request messages and receives and displays HTTP response messages via the network module 220. Access from the client computer 120 to the software distribution server 100 and MFP 150 is performed through the web browser 221.

[0031] The printer driver 222 creates a print job and sends it to the MFP 150 via the network module 220. The printer driver 222 also receives and displays the print job execution results from the MFP 150 via the network module 220. Here, a job refers to a processing operation such as printing, scanning, and faxing that can be performed by the user on the MFP 150.

[0032] Next, we will explain the overview of the MFP150's software configuration. In the MFP150, various modules exist as files stored in ROM154 or external memory162, and are loaded into RAM153 and executed at runtime.

[0033] More specifically, the MFP150 comprises a network module 240, a print module 241, a scan transmission module 242, a fax module 243, and a data acquisition module 244. The MFP150 also comprises a predictive calculation module 245, a predictive result transmission module 246, a UI module 247, a firmware update module 248, and a database storage module 249.

[0034] The network module 240 communicates with the software distribution server 100 and client computers 120 via a network using any communication protocol. The print module 241 receives print jobs sent from the printer driver 222 on the client computer 120 via the network module 240 and executes the print jobs. The print module 241 also creates a log of the print job execution results and sends it to the data collection module 244.

[0035] The scan transmission module 242 receives a scan command from the user via the UI module 247 and generates and executes scan jobs and scan data transmission jobs. Here, protocols such as email or SMB (Server Message Block) are used for transmitting scan data. The fax module 243 receives fax reception jobs via the network module 240 for fax jobs sent from fax machines or MFPs (not shown). Here, the received fax reception jobs are printed via the print module 241 or transferred to other fax machines or MFPs. In addition, the fax module 243 receives a fax transmission command from the user via the UI module 247 and generates and executes fax transmission jobs.

[0036] In addition to collecting logs of the print job execution results mentioned above, the data collection module 244 has the function of collecting data from sensors that detect the state of each consumable part constituting the MFP150 and processing the data so that it can be used for prediction. The data collection module 244 also transmits the processed data to the prediction calculation module 245. The prediction calculation module 245 uses the data transmitted from the data collection module 244 and the component life prediction algorithm built into the module to perform life value prediction calculations for each consumable part. The prediction result transmission module 246 transmits the prediction calculation results to the algorithm analysis generation server 140 via the network module 240. The UI module 247 displays information such as the component status history screen 600 described later and detects input for the displayed information. The database storage module 249 stores the information displayed on the UI module 247 and the information entered into the UI module 247.

[0037] The algorithm analysis and generation server 140 includes a network module 260, a learning data generation unit 261, a learning database 262, a learning unit 263, and learning model data 264. The learning database 262 stores the lifespan prediction calculation results for each consumable part transmitted from the prediction result transmission module 246 in the MFP 150. That is, if the part lifespan prediction system 10 includes multiple MFPs 150, the learning database 262 will store the calculation results received from multiple MFPs 150. The learning unit 263 performs retraining to improve or generate the part lifespan prediction algorithm from these calculation results. The learning data generation unit 261 generates learning model data 264 using the results of retraining. The learning model data 264 will be incorporated into the MFP 150 as new firmware or software.

[0038] The software distribution server 100 can acquire firmware incorporating the learning model data 264 obtained through such retraining, register it with the database service module 210, and then distribute the firmware to the MFP150. The firmware update module 248 of the MFP150 replaces the component life prediction algorithm by applying the learning model data 264 as the firmware is updated. Note that the timing of replacing the component life prediction algorithm is not limited to firmware updates; for example, it may occur when the MFP150 is first started up or when the firmware is applied during initialization of the MFP150.

[0039] Figure 3 illustrates the detailed module configuration of the MFP150's data acquisition module 244. The data acquisition module 244 comprises a communication unit 300, a sensor information holding unit 301, a sensor information management unit 302, and a time management unit 303.

[0040] The communication unit 300 communicates with the software distribution server 100 or the algorithm analysis and generation server 140 via the network module 240 and the network 170. The sensor information holding unit 301 is an area used for notifying the prediction calculation module 245 of data. The sensor information management unit 302 collects data obtained by measuring the state of each consumable part constituting the MFP 150 with sensors. The sensor information management unit 302 also processes the data so that it can be used for prediction. The sensor information management unit 302 also causes the sensor information holding unit 301 to store the processed data. The time management unit 303 manages the timer function that drives the data collection module 244 to collect data at predetermined time intervals.

[0041] Figure 4 illustrates the detailed module configuration of the predictive calculation module 245 of the MFP150. The predictive calculation module 245 includes a communication unit 400, a calculation method determination unit 401, a calculation method determination result holding unit 402, a predictive calculation unit 403, a calculation result holding unit 404, and a UI display data creation unit 405. Note that the communication unit 400 is the same as the communication unit 300, so its explanation is omitted.

[0042] The calculation method determination unit 401 determines whether the calculation method has been determined in the past when a component life prediction algorithm is replaced due to software distribution or other reasons. The calculation method determination unit 401 also obtains the current life value and compares its magnitude with a predetermined threshold to determine the calculation method for the life value. The calculation method determination unit 401 also instructs the calculation method determination result holding unit 402 to save the result of this determination and the current life value obtained at the time of the determination execution. The calculation method determination result holding unit 402 saves the life value that the calculation method determination unit 401 has instructed to save to a non-volatile storage medium such as an external memory 162 (an example of a "storage unit").

[0043] The prediction calculation unit 403 detects the replacement of the component life prediction algorithm and, after the calculation method determination process by the calculation method determination unit 401, performs life value calculation. At this time, it obtains the calculation method determination result stored by the calculation method determination result holding unit 402 and the current life value obtained when it is determined whether or not the calculation method determination result is saved or what its contents are. The prediction calculation unit 403 then calculates a new life value using the calculation method based on the determination result and has the calculation result stored in the calculation result holding unit 404. The UI display data creation unit 405 uses the calculation result stored in the calculation result holding unit 404 to create the data necessary for the UI module 247 to use for UI display.

[0044] Figure 5 illustrates the detailed module configuration of the prediction result transmission module 246 of the MFP150. The prediction result transmission module 246 includes a communication unit 500 and a prediction calculation result acquisition unit 501. Note that the communication unit 500 is the same as the communication unit 300, so its explanation is omitted. The prediction calculation result acquisition unit 501 acquires the lifetime value calculated by the prediction calculation module 245 and transmits the acquired lifetime value to the algorithm analysis generation server 140.

[0045] Figure 6 illustrates the part status history screen 600. The part status history screen 600 is an example of a screen that includes a graph showing the time-series changes in lifespan values ​​obtained from lifespan prediction. Note that the part status history screen 600 is an example of a screen that displays the service technician's part status display function, which is a function of UI module 247.

[0046] More specifically, the part status history screen 600 is a screen that displays details of the status of a target part, for example. The part status history screen 600 includes date information 601, display period 602, and graph 603. Date information 601 is the date information on when the part's life prediction was last performed. Such date information is displayed as the last update date. Display period 602 is a pull-down menu for changing the display period of the horizontal axis of the time-series graph of the life value shown in graph 603. Display period 602 can select a period of, for example, one month or six months.

[0047] Graph 603 is a time-series graph of the predicted lifespan value. More specifically, the vertical axis represents the lifespan value and the horizontal axis represents the date. Graph 603 shows the points where the lifespan value is plotted for each date on which lifespan prediction was performed. In this embodiment, it is assumed that the component lifespan prediction algorithm was replaced on December 11th. However, Graph 603 shows that there is no deviation in the lifespan value around December 11th.

[0048] <Example of operation 1> Figures 7 to 9 illustrate an example of the operation realized by the MFP150, including the hardware and software configuration described above. First, Figure 7 illustrates an example of processing in the predictive calculation module 245 of the MFP150. This processing is the determination process for the lifespan calculation method. This processing is realized when the CPU 152 of the MFP150 loads a program stored in the ROM 154 into the working area of ​​the RAM 153 and executes it, and various components are controlled through the execution of the program.

[0049] In S701, the communication unit 400 of the predictive calculation module 245 receives a calculation method determination instruction. In S702, the calculation method determination unit 401 (an example of the "third determination unit") determines whether or not the calculation method determination result has been saved in the external memory 162. If the calculation method determination unit 401 determines that the calculation method determination result has been saved, the process proceeds to S705; otherwise, the process proceeds to S703. In S703, the calculation method determination unit 401 obtains the lifetime value. In S704, the calculation method determination unit 401 causes the obtained lifetime value to be saved in the calculation method determination result holding unit 402. In S705, the calculation method determination unit 401 instructs the predictive calculation unit 403 to calculate the lifetime value. The predictive calculation unit 403 then performs the calculation of the lifetime value. The process then terminates.

[0050] Next, using Figure 8, another example of processing in the predictive calculation module 245 of the MFP150 will be explained. This processing is a predictive calculation process for the lifetime value. This processing is realized when the CPU 152 of the MFP150 loads a program stored in ROM 154 into the working area of ​​RAM 153 and executes it, and various components are controlled through the execution of the program.

[0051] In S801, when a replacement of the component life prediction algorithm occurs, the prediction calculation unit 403 of the prediction calculation module 245 detects this replacement of the component life prediction algorithm. In S802, the prediction calculation unit 403 sends a calculation method determination instruction to the calculation method determination unit 401. In S803, the prediction calculation unit 403 detects a life value calculation instruction. In S804, the prediction calculation unit 403 obtains the calculation method determination result and the life value immediately before the replacement from the calculation method determination result holding unit 402. In S805, the prediction calculation unit 403 adds the life value immediately before the replacement to the calculated result of the life value after the replacement to perform a life value calculation.

[0052] This S805 process prevents discrepancies in lifespan values ​​before and after algorithm replacement, even when employing a component lifespan prediction algorithm that adds a newly calculated lifespan value to the lifespan value immediately before replacement. In S806, the prediction calculation unit 403 stores the lifespan calculation result in the calculation result holding unit 404. Then, the process ends.

[0053] Next, using Figure 9, an example of a sequence flow executed in the MFP150 through the cooperation of the predictive calculation module 245, which operates as shown in Figures 7 and 8, and other modules of the MFP150 will be explained. This process is realized when the CPU 152 of the MFP150 loads a program stored in ROM 154 into the working area of ​​RAM 153 and executes it, and each component is controlled through the execution of the program.

[0054] In S900, when a component life prediction algorithm is replaced, the prediction calculation unit 403 (an example of a "detection unit") of the prediction calculation module 245 detects this replacement of the component life prediction algorithm. In S901, the prediction calculation unit 403 transmits a calculation method determination instruction to the calculation method determination unit 401. The communication unit 400 then receives this calculation method determination instruction.

[0055] In S902, the calculation method determination unit 401 queries the calculation method determination result storage unit 402 to determine whether or not a calculation method determination result exists. In S903, the calculation method determination result storage unit 402 determines whether or not a calculation method determination result is stored. The calculation method determination result storage unit 402 then notifies the calculation method determination unit 401 of the existence or non-existence of a calculation method determination result.

[0056] In S904, the calculation method determination unit 401 receives notification from the calculation method determination result holding unit 402 regarding the presence or absence of a calculation method determination result. The calculation method determination unit 401 then uses this notification to determine whether or not the calculation method determination result has been saved. If the calculation method determination unit 401 determines that the calculation method determination result has been saved, the process proceeds to S908; otherwise, the process proceeds to S905. Note that when a component of the MFP150 is replaced, the calculation method determination result holding unit 402 erases the calculation method determination result from the external memory 162. In other words, if the calculation method determination result has not been saved, for example, it is when the MFP150 is started for the first time after a component replacement has been performed.

[0057] In S905, the calculation method determination unit 401 instructs the calculation result holding unit 404 to acquire a lifetime value. In S906, the calculation result holding unit 404 notifies the calculation method determination unit 401 of the lifetime value in response to this instruction. The calculation method determination unit 401 (an example of an "acquisition unit") then acquires this lifetime value (an example of a "first lifetime").

[0058] In S907, the calculation method determination unit 401 instructs the calculation method determination result holding unit 402 to save the lifetime value obtained in S906. Then, the process proceeds to S908. In S908, the calculation method determination unit 401 instructs the prediction calculation unit 403 to calculate the lifetime value. In S909, the prediction calculation unit 403 receives this instruction and requests the calculation method determination result holding unit 402 to obtain the calculation method determination result. In S910, the calculation method determination result holding unit 402 notifies the prediction calculation unit 403 of the lifetime value at the time of calculation method determination that was saved in S907. Then, the prediction calculation unit 403 obtains this lifetime value.

[0059] In S911, the prediction calculation unit 403 (an example of a "prediction unit") uses the lifespan value obtained in S910 as the lifespan value immediately before replacement. The prediction calculation unit 403 then calculates the lifespan value using the lifespan prediction algorithm for the replacement component. The prediction calculation unit 403 then adds the lifespan value calculated using the lifespan prediction algorithm for the replacement component to the lifespan value immediately before replacement to calculate a new lifespan value (an example of a "second lifespan"). In S912, the prediction calculation unit 403 instructs the calculation result storage unit 404 to save the calculation result. In S913, the calculation result storage unit 404 instructs the UI display data creation unit 405 to create UI display data. In S914, the UI display data creation unit 405 (an example of a "generation unit") receives this instruction and creates the UI display data. The UI display data is, for example, a graph of the time series change of the lifespan value shown in Figure 6. The UI display data created in this way is then displayed on the touch panel display of the operation unit 156 by the UI module 247 (an example of an "output unit"). The process then ends.

[0060] <Example of operation 2> Figures 10 to 12 illustrate another example of the operation implemented by the MFP150. First, Figure 10 illustrates another example of the lifespan calculation method determination process in the predictive calculation module 245 of the MFP150. This process is implemented when the CPU 152 of the MFP150 loads the program stored in the ROM 154 into the working area of ​​the RAM 153 and executes it, and various components are controlled through the execution of the program.

[0061] Steps S1001 to S1003 are the same as steps S701 to S703 in Figure 7 relating to Operation Example 1, so their explanation is omitted. In step S1004, the calculation method determination unit 401 (an example of the "first determination unit") determines whether the lifetime value obtained in step S1003 is greater than or equal to a pre-set threshold a (an example of "greater than or equal to the first threshold"). The threshold a can be a value between 0 and 1000. If the calculation method determination unit 401 determines that the lifetime value is greater than or equal to threshold a, the process proceeds to step S1006; otherwise, the process proceeds to step S1005.

[0062] In S1005, the calculation method determination unit 401 (an example of a "second determination unit") further determines whether the lifetime value obtained in S1003 is less than a pre-set threshold b (an example of "less than a second threshold"). The threshold b can take a value between 0 and 1000. It is also a given that threshold b is smaller than threshold a. If the calculation method determination unit 401 determines that the lifetime value is less than threshold b, the process proceeds to S1007; otherwise, the process proceeds to S1008.

[0063] In S1006, the calculation method determination unit 401 sets the calculation method determination result to 2. In S1007, the calculation method determination unit 401 sets the calculation method determination result to 0. In S1008, the calculation method determination unit 401 sets the calculation method determination result to 1. This calculation method determination result is an example of "identification information that can distinguish the determination results of the first determination unit and the second determination unit". In S1009, the calculation method determination unit 401 causes the calculation method determination result holding unit 402 to store the lifetime value obtained in S1003 and the calculation method determination result determined in S1006, S1007, or S1008. S1010 is the same as S705, so the explanation is omitted. Then the process ends.

[0064] Next, using Figure 11, another example of the lifetime value prediction calculation process in the prediction calculation module 245 of the MFP150 will be explained. This process is realized when the CPU 152 of the MFP150 loads a program stored in ROM 154 into the working area of ​​RAM 153 and executes it, and various components are controlled through the execution of the program.

[0065] Steps S1101 to S1104 are the same as steps S801 to S804 in Figure 8 relating to Operation Example 1, so their explanation is omitted. In step S1105, the prediction calculation unit 403 determines whether the calculation method determination result obtained in step S1104 is 2 or not. If the prediction calculation unit 403 determines that the calculation method determination result is 2, the process proceeds to step S1107; otherwise, the process proceeds to step S1106.

[0066] In S1106, the prediction calculation unit 403 further determines whether the calculation method determination result obtained in S1104 is 0 or not. If the prediction calculation unit 403 determines that the calculation method determination result is 0, the process proceeds to S1108; otherwise, the process proceeds to S1109.

[0067] In S1107, the prediction calculation unit 403 calculates the lifespan value by applying the component lifespan prediction algorithm used before the replacement of the component lifespan prediction algorithm was performed. At this time, the assumed state of the component is that it has little life remaining or has reached a level where replacement of the component is necessary. Therefore, this process in S1107 makes it possible to prevent the lifespan value of a component that has been used for a long period of time until replacement is necessary from rapidly increasing after the replacement of the component lifespan prediction algorithm, i.e., preventing a sudden change in the rate of increase of the lifespan value.

[0068] In S1108, the prediction calculation unit 403 applies the replaced component life prediction algorithm to calculate the life value. At this time, the assumed state of the component is that of a nearly new component that has hardly been used. By performing this process in S1108, the life value is predicted using the replaced component life prediction algorithm at an early stage of component use, enabling more accurate component life prediction than in S1107 or S1109.

[0069] In S1109, the lifespan value is calculated by adding the calculation result of the part lifespan prediction algorithm after replacement to the lifespan value immediately before replacement, which was calculated by the part lifespan prediction algorithm before replacement obtained in S1104. At this time, the expected state of the part is assumed to be less than or equal to the state assumed in S1107 and greater than or equal to the state assumed in S1108. For example, consider a case where a part lifespan prediction algorithm is used that adds the lifespan value calculated up to the previous lifespan value to a part that has been used to some extent. In such a case, executing S1109 can prevent a discrepancy in the lifespan value before and after replacement of the part lifespan prediction algorithm. In S1110, the prediction calculation unit 403 saves the lifespan calculation result calculated in S1107, S1108, or S1109 to the calculation result holding unit 404. Then the process ends.

[0070] Next, using Figure 12, another example of a sequence flow executed in the MFP150 through the cooperation of the predictive calculation module 245, which operates as shown in Figures 10 and 11, and other modules of the MFP150, will be explained. This process is realized when the CPU 152 of the MFP150 loads a program stored in ROM 154 into the working area of ​​RAM 153 and executes it, and each component is controlled through the execution of the program.

[0071] Since steps S1200 to S1206 are the same as steps S901 to S906 in Figure 9 relating to Operation Example 1, their explanation is omitted. In S1207, the calculation method determination unit 401 determines the calculation method. That is, the calculation method determination unit 401 determines whether the lifetime value obtained in S1206 is greater than or equal to threshold a. If the calculation method determination unit 401 determines that the lifetime value is greater than or equal to threshold a, it sets the calculation method determination result to 2, and the process proceeds to S1209.

[0072] On the other hand, if the calculation method determination unit 401 determines that the lifespan value is not greater than or equal to threshold a, it determines whether the lifespan value is less than threshold b. If the calculation method determination unit 401 determines that the lifespan value is less than threshold b, it sets the calculation method determination result to 0, and the process proceeds to S1210. Note that the calculation method determination result is 0 if, for example, the MFP150 is started up immediately after a component replacement is performed. On the other hand, if the calculation method determination unit 401 determines that the lifespan value is not less than threshold b, it sets the calculation method determination result to 1, and the process proceeds to S1211.

[0073] In S1209, the calculation method determination unit 401 causes the calculation method determination result holding unit 402 to store 2 as the determination result. Then, the process proceeds to S1212. In S1210, the calculation method determination unit 401 causes the calculation method determination result holding unit 402 to store 0 as the determination result. Then, the process proceeds to S1212. In S1211, the calculation method determination unit 401 causes the calculation method determination result holding unit 402 to store 1 as the determination result. Then, the process proceeds to S1212. In S1212, the calculation method determination unit 401 causes the life value obtained in S1206 to be stored in the calculation method determination result holding unit 402 in association with the calculation method determination result determined in S1207.

[0074] S1213 and S1214 are the same as S908 and S909 in Figure 9 relating to Operation Example 1, so their explanation is omitted. In S1215, the calculation method determination result holding unit 402 notifies the prediction calculation unit 403 of the calculation method determination result saved in any of S1209 to S1211, and the lifetime value at the time of calculation method determination saved in S1212. In S1216, the prediction calculation unit 403 determines the notified calculation method determination result. If the prediction calculation unit 403 determines that the calculation method determination result is 2, the process proceeds to S1217. If the prediction calculation unit 403 determines that the calculation method determination result is 0, the process proceeds to S1218. If the prediction calculation unit 403 determines that the calculation method determination result is 1, the process proceeds to S1219.

[0075] In S1217, the prediction calculation unit 403 calculates the lifespan value by applying the pre-replacement component lifespan prediction algorithm. Alternatively, the prediction calculation unit 403 may calculate the lifespan value by adding the calculation result of the pre-replacement component lifespan prediction algorithm to the lifespan value calculated by the pre-replacement component lifespan prediction algorithm immediately before replacement. Then, the process proceeds to S1220. In S1218, the prediction calculation unit 403 calculates the lifespan value by applying the post-replacement component lifespan prediction algorithm. Then, the process proceeds to S1220. In S1219, the prediction calculation unit 403 calculates the lifespan value by adding the calculation result of the post-replacement component lifespan prediction algorithm to the lifespan value calculated by the pre-replacement component lifespan prediction algorithm. Then, the process proceeds to S1220.

[0076] Since steps S1220 to S1222 are the same as steps S912 to S914 in Figure 9 relating to Operation Example 1, their explanation is omitted. Then, the series of processes is completed.

[0077] (One aspect of action / effect) According to the component life prediction system 10 described above, when the component life prediction algorithm is replaced, the discrepancy between the predicted lifespan values ​​before and after the replacement is suppressed. In other words, after the replacement, an appropriate lifespan value is calculated without causing a sudden recovery in the component's lifespan value. Therefore, it is possible to prevent customers from experiencing reduced print quality or downtime due to component failure by using components beyond their lifespan.

[0078] <Variation> The component status history screen 600, as shown in Figure 6, may be transmitted to the client computer 120 by the network module 240 of the MFP 150 (an example of an "output unit"). The CPU of the client computer 120 may then receive this component status history screen 600 and display it on its display.

[0079] <Other Embodiments> The present invention can also be realized by supplying a program that implements one or more of the functions of the above-described embodiments to a system or device via a network or storage medium, and by having one or more processors in the computer of that system or device read and execute the program. It can also be realized by a circuit (e.g., an ASIC) that implements one or more functions.

[0080] The invention is not limited to the embodiments described above, and various modifications and variations are possible without departing from the spirit and scope of the invention. Accordingly, claims are attached to disclose the scope of the invention.

[0081] The disclosures herein include the following image processing apparatus, control methods thereof, and programs. <Item 1> An acquisition unit that acquires a first wear level predicted using the algorithm before replacing the algorithm that predicts the wear level of the components of the image processing device, A prediction unit for predicting a second degree of wear after replacing the algorithm, comprising: the prediction unit predicting the second degree of wear using the first degree of wear acquired by the acquisition unit and at least one of the algorithms before and after the replacement, Image processing device. <Item 2> A first determination unit controls the execution of a determination of whether the first degree of wear acquired by the acquisition unit is equal to or greater than a first threshold, If the first determination unit determines that the first degree of wear is not equal to or greater than the first threshold, the system further comprises a second determination unit that determines whether or not the first degree of wear is less than the second threshold, The prediction unit, If the first determination unit determines that the first degree of wear is equal to or greater than the first threshold, it predicts the second degree of wear using the algorithm before replacement. If the first determination unit determines that the first degree of wear is not equal to or greater than the first threshold, and the second determination unit determines that the first degree of wear is less than the second threshold, the second degree of wear is predicted using the replaced algorithm. If the first determination unit determines that the first degree of wear is not equal to or greater than the first threshold, and the second determination unit determines that the first degree of wear is not less than the second threshold, the second degree of wear is predicted by adding the degree of wear predicted using the replaced algorithm to the first degree of wear acquired by the acquisition unit. The image processing device described in item 1. <Item 3> A storage unit that stores identification information capable of identifying the determination results of the first determination unit and the second determination unit, The system further comprises a third determination unit that determines whether or not the identification information is stored in the storage unit, If the third determination unit determines that the identification information is stored in the storage unit, the first determination unit does not perform the determination. The storage unit further erases the stored identification information when the component is replaced. The image processing device described in item 2. <Item 4> The prediction unit further includes a detection unit that detects the replacement of the algorithm, The acquisition unit acquires the first wear level in response to the detection unit detecting the replacement. An image processing device as described in any one of items 1 to 3. <Item 5> A generation unit that generates a graph of the second degree of wear predicted by the prediction unit, The system further comprises an output unit that outputs a screen including the graph generated by the generation unit, An image processing device described in any one of items 1 through 4. <Item 6> A method for controlling an image processing device, The acquisition unit performs an acquisition step of acquiring a first wear degree predicted using the algorithm before replacing the algorithm that predicts the wear degree of the components of the image processing device, The prediction unit includes a prediction step for predicting the second degree of wear after replacing the algorithm, the prediction step for predicting the second degree of wear using the first degree of wear obtained in the acquisition step and at least one of the algorithms before and after the replacement, A method for controlling an image processing device. <Item 7> A program for causing a computer to execute each step in a control method for an image processing device, wherein the control method is: The acquisition unit performs an acquisition step of acquiring a first wear degree predicted using the algorithm before replacing the algorithm that predicts the wear degree of the components of the image processing device, The prediction unit includes a prediction step for predicting the second degree of wear after replacing the algorithm, the prediction step for predicting the second degree of wear using the first degree of wear obtained in the acquisition step and at least one of the algorithms before and after the replacement, program. [Explanation of Symbols]

[0082] 10: Component life prediction system, 100: Software distribution server, 110, 162: External memory, 120: Client computer, 140: Algorithm analysis generation server, 150: MFP, 152: CPU, 153: RAM, 154: ROM, 162: External memory, 245: Predictive calculation module, 401: Calculation method determination unit, 402: Calculation method determination result holding unit, 403: Predictive calculation unit, 404: Calculation result holding unit

Claims

1. An acquisition unit that acquires a first wear level predicted using the algorithm before replacing the algorithm that predicts the wear level of the components of the image processing device, A prediction unit for predicting a second degree of wear after replacing the algorithm, comprising: a prediction unit that predicts the second degree of wear using the first degree of wear acquired by the acquisition unit and at least one of the algorithms before and after the replacement, Image processing device.

2. A first determination unit controls the execution of a determination of whether the first degree of wear acquired by the acquisition unit is equal to or greater than a first threshold, If the first determination unit determines that the first degree of wear is not equal to or greater than the first threshold, the system further comprises a second determination unit that determines whether or not the first degree of wear is less than the second threshold, The prediction unit, If the first determination unit determines that the first degree of wear is equal to or greater than the first threshold, it predicts the second degree of wear using the algorithm before replacement. If the first determination unit determines that the first degree of wear is not equal to or greater than the first threshold, and the second determination unit determines that the first degree of wear is less than the second threshold, the second degree of wear is predicted using the replaced algorithm. If the first determination unit determines that the first degree of wear is not equal to or greater than the first threshold, and the second determination unit determines that the first degree of wear is not less than the second threshold, the second degree of wear is predicted by adding the degree of wear predicted using the replaced algorithm to the first degree of wear acquired by the acquisition unit. The image processing apparatus according to claim 1.

3. A storage unit that stores identification information capable of identifying the determination results of the first determination unit and the second determination unit, The system further comprises a third determination unit that determines whether or not the identification information is stored in the storage unit, If the third determination unit determines that the identification information is stored in the storage unit, the first determination unit does not perform the determination. The storage unit further erases the stored identification information when the component is replaced. The image processing apparatus according to claim 2.

4. The prediction unit further includes a detection unit that detects the replacement of the algorithm, The acquisition unit acquires the first wear level in response to the detection unit detecting the replacement. The image processing apparatus according to claim 1.

5. A generation unit that generates a graph of the second degree of wear predicted by the prediction unit, The system further comprises an output unit that outputs a screen including the graph generated by the generation unit, The image processing apparatus according to any one of claims 1 to 4.

6. A method for controlling an image processing device, The acquisition unit performs an acquisition step of acquiring a first wear degree predicted using the algorithm before replacing the algorithm that predicts the wear degree of the components of the image processing device, The prediction unit includes a prediction step for predicting the second degree of wear after replacing the algorithm, the prediction step for predicting the second degree of wear using the first degree of wear acquired in the acquisition step and at least one of the algorithms before and after the replacement, A method for controlling an image processing device.

7. A program for causing a computer to execute each step in a control method for an image processing device, wherein the control method is: The acquisition unit performs an acquisition step of acquiring a first wear degree predicted using the algorithm before replacing the algorithm that predicts the wear degree of the components of the image processing device, The prediction unit includes a prediction step for predicting the second degree of wear after replacing the algorithm, the prediction step for predicting the second degree of wear using the first degree of wear acquired in the acquisition step and at least one of the algorithms before and after the replacement, program.

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