JP2007164724A - System, method and program for supporting delivery of required component - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a system, a method and a program for supporting delivery of required components for exactly and quickly delivering the required components when a customer engineer visits an installation place of equipment to perform a maintenance operation according to failure prediction. <P>SOLUTION: An image forming apparatus 30 performs the failure prediction by a failure prediction system 32, when there is a failure prediction, transmits failure prediction information to an information management device 20. The information management device 20 specifies the required components using equipment component information storage part 26 based on the failure prediction information. Then, information management device 20 transmits component delivery instruction information to a component order acceptance management device 40, the component order acceptance management device 40 specifies the installation place of the image forming apparatus 30 using an equipment installation information storage part 42 to perform processing for delivering the components. In addition, the information management device 20 transmits failure prediction notification information for notifying information regarding the failure prediction and component delivery notification information for notifying information regarding delivery of the components to a customer engineer terminal 50. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a necessary parts delivery support system, a necessary parts delivery support method, and a necessary parts delivery support program for delivering parts required for equipment maintenance work to a place where the equipment is installed.

  Currently, various types of image forming apparatuses such as printers, copiers, and facsimile machines are installed in offices of various customers. In such image forming apparatuses that use paper and print images on paper, It is difficult to eliminate problems such as paper jams. For this reason, even when trouble occurs, various ideas have been made on the image forming apparatus so that the customer can restore the trouble state to the normal state as much as possible.

  However, troubles that can only be recovered by professional maintenance personnel may occur, and maintenance contracts are made between the manufacturers and sales companies of each image forming device and customers, and regular cleaning by maintenance personnel. In addition, there are maintenance systems and contracts that perform maintenance work such as replacement of consumables and consumable parts, and can provide quick response when trouble occurs.

  In the case of a failure that cannot be repaired unless maintenance personnel respond to the image forming device used by the customer, the customer requests repairs from the sales office of each manufacturer or sales company that has a maintenance maintenance contract. . At the maintenance sales base that received the repair request, search for a maintenance person who is in charge of the customer who received the request or a maintenance person who can maintain the model in the vicinity of the customer, and request customer service. It is common.

  Further, in recent years, in order to minimize the operation stop of the image forming apparatus due to maintenance work and to properly grasp the state of the apparatus, the image forming apparatus is provided with a state sensing means and a communication function, and the state is periodically changed through a communication line. A system for automatically diagnosing is proposed (for example, see Patent Document 1). Many techniques that can be used as means for realizing such a system have been disclosed. One of them relates to the detection of a failure of a specific unit or component, and a method for predicting the lifetime of these is also proposed (see, for example, Patent Document 2). In addition, techniques for sequentially diagnosing various failures have been proposed (see, for example, Patent Document 3). There is also a method of detecting an abnormality in a toner image that is a result of the image forming apparatus (see, for example, Patent Document 4). Also disclosed is a technique in which failure pre-diagnosis is performed in each image forming apparatus, and further, the remote management apparatus performs failure diagnosis based on various types of information including user information (see, for example, Patent Document 5). If a diagnostic system is constructed using these technologies, the number of customer visits by maintenance personnel can be reduced, and the time during which the apparatus is stopped due to maintenance work can be reduced.

On the other hand, the present applicant has applied for a method of calculating an index value for predicting the occurrence of an abnormality based on a plurality of types of information acquired during normal operation of the image forming apparatus (see, for example, Patent Document 6). ). By using this method, it is possible to predict failures in a wide range of image forming devices that could not be covered by conventional life prediction technology. Lifetime judgment of many consumable parts by maintenance personnel at the time of emergency failure or periodic preventive maintenance , The maintenance work at an appropriate timing is realized, and the machine stop time is also reduced.
JP2003-241448 (page 5-16) JP 2001-356655 A (pages 9-23) JP 2000-270141 A (page 3-20) JP 2000-89623 A (pages 3-6) JP-A-8-30152 (page 3-16) Japanese Patent Laying-Open No. 2005-17874 (page 6-36)

  However, when dealing with a failure, visits are given priority for emergency response. For this reason, even if the cause of the failure is found by visiting the customer, if the visiting maintenance staff does not have the parts necessary for repair, the parts necessary for recovery from the fault can be returned to the sales office, or can be applied to the sales office. If there are no parts, you will need to arrange and obtain the parts and then visit again. In such a case, the trouble state becomes longer because necessary parts cannot be prepared in advance.

  Also, when an emergency failure occurs immediately before a regular preventive maintenance visit, maintenance parts usually do not have replacement parts and must be visited again when performing repair and maintenance. In such a case, not only the maintenance staff takes time and cost, but also a loss is caused for the customer by stopping the apparatus. Moreover, even when performing failure prediction using the failure prediction technique described in Patent Document 6, it is not possible to quickly respond to failure prediction unless necessary parts are prepared.

  The present invention has been made to solve the above-described problems, and its purpose is to accurately and quickly locate necessary parts when a maintenance staff visits the installation location of equipment according to failure prediction and performs maintenance work. A necessary parts delivery support system, a necessary parts delivery support method, and a necessary parts delivery support program are provided.

  In order to solve the above-mentioned problems, the invention according to claim 1 is characterized in that the device part information storage means that records the failure contents of the device in association with the components used for the failure, and information on the installation location of the device. And a device installation information storage means recorded in association with each other, and performs processing for delivering necessary parts based on the failure prediction of the device to be managed, and also sends notification information to the maintenance staff terminal based on the failure prediction A necessary component delivery support system for transmitting, wherein a computer provided in the necessary component delivery support system performs failure prediction means for performing failure prediction of a device to be managed, and based on the failure prediction result, the device component information A component identification unit that identifies a necessary component using a storage unit; and a component identification unit that identifies the installation location of the device using the device installation information storage unit and delivers the component Functioning as a delivery information processing unit for transmitting information, a failure prediction notification information for notifying information on the failure prediction, and a component delivery notification information for notifying information on the delivery of the component to a maintenance staff terminal Is the gist.

  According to a second aspect of the present invention, in the necessary component delivery support system according to the first aspect, the necessary component delivery support system includes an information management device connectable to the device, and the device serves as the failure prediction unit. And the device transmits information related to a result of failure prediction by the failure prediction means to the information management device, and the information management device executes processing using the information related to the result of failure prediction. The gist.

The gist of the invention according to claim 3 is the necessary parts delivery support system according to claim 1 or 2, wherein the device is an image forming apparatus.
According to a fourth aspect of the present invention, there is provided a device part information storage unit that records the failure content of a device and a component used for handling the failure in association with each other, and a device installation information storage that records information relating to a device installation location in association with the device. And a process for delivering the necessary parts based on the failure prediction of the device to be managed using the necessary parts delivery support system provided with the means, and the notification information is sent based on the failure prediction. A necessary part delivery support method for transmitting to a computer, wherein the computer provided in the necessary part delivery support system performs a failure prediction of a managed device, and the device part information storage based on the failure prediction result A step of specifying a necessary part using a means, and a step of performing a process for specifying the installation location of the equipment and delivering the part using the equipment installation information storage means When, the gist to perform the step of transmitting a component delivery notice information for notifying the information about the delivery of the parts and failure prediction notification information representing information on the failure prediction maintenance personnel terminal.

  The invention according to claim 5 is a device to be managed by using a device part information storage unit that records the failure content of the device and a component to be used for dealing with the failure, and a computer that can be connected to the device to be managed. A necessary parts delivery support program for performing a process for delivering a necessary part based on a failure prediction and transmitting notification information to a maintenance staff terminal based on the failure prediction. A failure prediction result receiving unit that receives information on a failure prediction result of the device from a target device, and a component specification that specifies a necessary component using the device component information storage unit based on the failure prediction result Means, delivery instruction means for instructing delivery of the identified part to the installation location of the device, failure prediction notification information for notifying information on the failure prediction, and the unit Delivering the component delivery notice information for notifying the information about the subject matter to be made to function as the notification information transmission means for transmitting to the maintenance person terminal.

(Function)
According to the first and fourth aspects of the present invention, the computer provided in the necessary component delivery support system performs failure prediction of the device to be managed, and uses the device component information storage means based on the failure prediction result. Identify the necessary parts. Then, the device installation information storage means is used to specify the installation location of the device and perform the process for delivering the component, and also notify the failure prediction notification information for notifying information related to the failure prediction and the information relating to the delivery of the component. The parts delivery notification information to be transmitted is transmitted to the maintenance staff terminal. Thereby, based on the result of the failure prediction for the device to be managed, necessary parts can be delivered to the installation location of the device, and information on failure prediction and component delivery can be notified to the maintenance staff. Therefore, the necessary parts can be delivered accurately and quickly to the installation location of the equipment, and the maintenance staff does not have to prepare the necessary parts by himself / herself, and thus can quickly go to the installation location of the equipment.

  According to a second aspect of the present invention, the necessary component delivery support system includes an information management device connectable to the device. And while the said apparatus functions as the said failure prediction means, the said apparatus transmits the information regarding the result of the failure prediction by the said failure prediction means to the said information management apparatus, The said information management apparatus is related with the result of the said failure prediction The process is executed using the information. As a result, each device to be managed performs failure prediction, and the information management apparatus can perform processing using the result of failure prediction.

According to the third aspect of the present invention, the device to be managed can be an image forming apparatus.
According to the invention described in claim 5, the computer connectable to the management target device receives information on the failure prediction result of the device from the management target device, and based on the failure prediction result, Necessary parts are specified using the equipment part information storage means. Then, the delivery of the identified part to the installation location of the device is instructed, and the failure prediction notification information for notifying the information about the failure prediction and the part delivery notification information for notifying the information about the part delivery are transmitted to the maintenance staff terminal. To do. This makes it possible to deliver the necessary parts to the installation location of the equipment based on the result of the failure prediction for the managed device, and to notify the maintenance staff of information related to the failure prediction and the parts delivery. Therefore, the necessary parts can be delivered accurately and quickly to the installation location of the equipment, and the maintenance staff does not have to prepare the necessary parts by himself / herself, and thus can quickly go to the installation location of the equipment.

ADVANTAGE OF THE INVENTION According to this invention, when a maintenance worker visits the installation place of an apparatus according to failure prediction and performs a maintenance work, required parts can be delivered accurately and rapidly.

  Hereinafter, an embodiment embodying the present invention will be described with reference to FIGS. In the present embodiment, when a maintenance staff visits the installation location of equipment according to failure prediction and performs maintenance work, a necessary parts delivery support system, a necessary parts delivery support method, and a necessary parts delivery support method for delivering necessary parts accurately and promptly, and This will be described as a necessary parts delivery support program. In the present embodiment, it is assumed that parts necessary for maintenance work include consumables.

As shown in FIG. 1, the information management apparatus 20 can be connected to the image forming apparatus 30, the parts order management apparatus 40, and the maintenance staff terminal 50 via communication lines 61, 62, and 63, respectively.
The information management device 20 includes a control unit 21. The control unit 21 includes control means (CPU), storage means (RAM, ROM, hard disk, etc.), data transmission / reception means, etc. (not shown). Based on the failure prediction result of the image forming apparatus 30, the control unit 21 delivers necessary parts to the installation location of the device, and processes described later to notify the maintenance staff of information related to the failure prediction and parts delivery. Execute. The control unit 21 includes a failure prediction information reception unit 22, a component identification unit 23, a component delivery instruction information transmission unit 24, and a terminal notification information transmission unit 25.

  The failure prediction information receiving unit 22 receives failure prediction information transmitted from the image forming apparatus 30 through the communication line 61 when an abnormal prior event occurs in the image forming apparatus 30 connected via the communication line 61. The failure prediction information includes a failure prediction date (a date when a predicted failure is performed after n days), a model identifier / manufacturing number of the image forming apparatus 30 that has transmitted the failure prediction information, a predicted failure type, and a corresponding type. Information on (preparation for parts replacement / adjustment) is included. Thus, in this embodiment, the failure prediction information receiving unit 22 functions as a failure prediction result receiving unit described in the claims. The failure prediction information receiving unit 22 transfers the received failure prediction information to the component specifying unit 23.

  The component specifying unit 23 searches and extracts the component number and the component name recorded in the device component information storage unit 26 based on the model identifier, the predicted failure type, and the corresponding type included in the failure prediction information. . Thus, in this embodiment, the component specific | specification part 23 functions as a component specific | specification means as described in a claim. Then, the component identification unit 23 transfers the extracted component number, information about the component name, and failure prediction information to the component delivery instruction information transmission unit 24 and the terminal notification information transmission unit 25, respectively.

  The component delivery instruction information transmission unit 24 transmits component delivery instruction information including data related to a failure prediction date, a model identifier, a manufacturing number, a component number, and a component name to the component order management device 40. Thus, in this embodiment, the parts delivery instruction information transmission unit 24 functions as a delivery instruction means described in the claims.

  The terminal notification information transmission unit 25 includes terminal notification information including failure prediction notification information based on the failure prediction information and component delivery notification information including data regarding a failure prediction date, a model identifier, a manufacturing number, a part number, and a part name. It transmits to the maintenance staff terminal 50. Thus, in this embodiment, the terminal notification information transmission unit 25 functions as a notification information transmission unit described in the claims.

  The information management apparatus 20 further includes a device component information storage unit 26 as device component information storage means. In the device part information storage unit 26, device part information related to a part number and a part name for a part necessary for handling a failure is recorded for each model identifier and type of failure. This device component information is recorded in advance for each model identifier and type of failure. In the present embodiment, the device component information includes data relating to a model identifier, a type of failure, a component number for a necessary component, and a component name.

  The component order management device 40 includes a control unit 41 and a device installation information storage unit 42 as a device installation information storage unit. The component order management device 40 receives the component delivery instruction information transmitted from the information management device 20, identifies the installation location of the image forming device 30, and performs processing for delivering the component to the identified installation location. Do. As described above, in this embodiment, the component delivery instruction information transmission unit 24 and the component order management device 40 function as delivery processing means described in the claims.

  The control unit 41 receives the parts delivery instruction information transmitted from the information management apparatus 20, searches the equipment installation information storage unit 42 based on the model identifier / manufacturing number included in the parts delivery instruction information, and Identify the installation location. And the control part 41 performs the process for delivering components to this installation place.

  In the device installation information storage unit 42, device installation information related to the installation location of the device (image forming apparatus 30) is recorded for each model identifier and serial number. In this embodiment, the address and name of the customer where the device is installed are recorded as the information regarding the installation location of the device. In this embodiment, the address and name of the customer where the device of this device installation information is installed are recorded by registration input when the device is installed at the customer site, and changed when the device installation location is changed. Updated by input. In the present embodiment, the device installation information includes data related to a model identifier, a serial number, a customer address, and a name. As information regarding the installation location of the device, the device (image forming apparatus 30) includes a GPS position specifying means, and the part order management device 40 acquires the position information of the image forming apparatus 30 by this position specifying means. May be. For example, when the image forming apparatus 30 is moved, the position information may be acquired and recorded in the device installation information storage unit 42 as information regarding the installation location of the device.

  The maintenance staff terminal 50 is a computer terminal used by the maintenance staff, stores information received from the information management apparatus 20, and presents the visited location, the state of the target image forming apparatus, and the like. As shown in FIG. 3, the maintenance staff terminal 50 includes a reception unit 51, a reception information recording unit 52, a visit request notification unit 53, and a display unit 54. The receiving unit 51 receives terminal notification information including failure prediction notification information and component delivery notification information transmitted from the information management device 20. The reception information recording unit 52 records this reception information. The visit request reporting unit 53 reports a visit request based on the failure prediction notification information received by the receiving unit 51. Based on these pieces of information, the display unit 54 displays information related to failure prediction and information related to parts delivery. The maintenance staff performs maintenance work based on the information displayed on the display unit 54.

  The image forming apparatus 30 includes an image forming unit 31, a failure prediction system 32, and a transmission unit 33. The image forming unit 31 includes various units (such as a printer unit, a sheet feeding unit, a scanner unit, and a document conveying unit) for performing image formation. In the present embodiment, the failure prediction system 32 functions as failure prediction means described in the claims.

As illustrated in FIG. 2, the failure prediction system 32 includes an information acquisition unit 71, an index value calculation unit 72, a state determination unit 73, a control unit 81, a parameter group formation unit 82, and a storage unit 83.
The information acquisition unit 71 acquires a plurality of types of information related to the image forming operation of the image forming apparatus 30. The information acquisition unit 71 is provided with a processing unit 75 for each input item 74 in the image forming unit 31. The index value calculation unit 72 calculates a single index value based on a plurality of types of information acquired by the information acquisition unit 71. The state determination unit 73 determines a subsequent change in the state of the image forming apparatus based on the time change data of the index value calculated by the index value calculation unit 72. The data of the time change of the index value calculated by the index value calculation unit 72 and the data of the determination result determined by the state determination unit 73 are used by the control unit 81 that controls each device in the image forming unit 31 or displayed. Or the like, or output to an external device. In this embodiment,
The state determination unit 73 outputs the determination result data to the transmission unit 33, and the transmission unit 33 transmits the diagnosis result data to the information management apparatus 20 through the communication line 61. This diagnosis result data is transmitted by, for example, a method of periodically transmitting (for example, once a day), a method of transmitting only when the index value has a specific value or more, or a method of combining these. To do.

  The information acquisition unit 71 acquires various types of information to be described later, and includes various sensors that detect various types of sensing information, a control unit 81, and a communication interface for data transmission / reception with an image data processing unit (not shown). Has been. The information acquisition unit 71 transmits a data acquisition request to the various sensors, the control unit 81, and the image data processing unit. The information acquisition unit 71 receives data of various sensing information from various sensors, receives data of control parameter information for mode designation from the control unit 81, and receives data of input image information from the image data processing unit. Can be received.

  The control unit 81 includes a CPU, a RAM, a ROM, an I / O interface unit, and the like. The index value calculation unit 72 and the state determination unit 73 may be provided separately from the control unit 81 as a device configured by a dedicated LSI or the like, and also share hardware resources such as a CPU constituting the control unit 81. May be configured.

The parameter group forming unit 82 calculates a plurality of parameters (parameter group) for calculating the index value and stores them in the storage unit 83.
The storage unit 83 uses a storage medium 84 that is detachable from the main body of the image forming apparatus 30. For this reason, replacement and content change can be easily performed as necessary. As such a storage medium, a conventionally known memory module such as a memory card, a memory board, a memory cartridge, a ROM cartridge, an IC card, or the like can be used. Alternatively, a magnetic memory such as a flexible disk may be used. These drivers are provided in the image forming apparatus 30 main body, and data is read in the state determination mode, and data is mainly written in the parameter group formation mode. By replacing these storage media 84, it is possible to easily change the determination condition (index value calculation formula) in the state determination mode.

  The failure prediction system 32 calculates an index value from various input information using a predetermined parameter. Hereinafter, the mode for performing the operation for calculating the index value is referred to as “state determination mode”, and the mode for determining the parameter for calculating the index value is referred to as “parameter group formation mode”.

  The information acquisition unit 71 takes in information on m items (a specific example will be described later) from the image forming unit 31. In the parameter group formation mode, the acquired information is processed and then output to the parameter group formation unit 82. On the other hand, in the state determination mode, the acquired information is processed and then output to the index value calculation unit 72.

  Next, information acquired by the information acquisition unit 71 will be described. Information acquired by the information acquisition unit 71 includes sensing information (a), control parameter information (b), input image information (c), and the like.

  The sensing information is information including data obtained by various sensors provided in or around the image forming apparatus. The sensing information includes the dimensions of each part of the apparatus, the speed of the moving body in the apparatus, time (timing), weight, current value, potential, vibration, sound, magnetic force, light quantity, temperature, humidity, and the like.

The control parameter information is generally information stored as a result of device control. The control parameter information includes user operation history, power consumption, toner consumption, various image forming condition setting history, warning history, and the like.

  The input image information is obtained from information input to the image forming apparatus 30 as image data. The input image information includes the cumulative number of colored pixels, character portion ratio, halftone portion ratio, color character ratio, toner consumption distribution in the main scanning direction, RGB signal (total toner amount in pixel units), document size, and document with borders. , Character type (size, font), etc.

  The mode of the failure prediction system 32 is switched by an instruction from the control unit 81. The control unit 81 designates the mode according to the number of output images or the cumulative driving time of the image forming system. These numerical values (threshold values) may be set in advance, or may be determined by an externally transmitted signal (for example, information input through an operator's key input or communication line).

The mode switching may be determined according to the following criteria, for example, depending on whether or not the image forming system has a failure.
・ If an obvious failure occurs, the previous data is discarded, and a new parameter group formation mode is started to make it stable.
-If an obvious failure occurs, the parameter formation group mode is continued without adopting only the data at that time.
-If an obvious failure occurs, the parameter formation group mode is continued without adopting data for a specific period going back from that point. Alternatively, the parameter group formation mode is executed without adopting a specific period after that point. Here, the specific period can be arbitrarily set.

  In the parameter group formation mode, the parameter group formation unit 82 calculates a plurality of parameters (parameter groups) for calculating the index value according to a predetermined procedure, and stores them in the storage unit 83.

  In the state determination mode, the index value calculation unit 72 introduces information obtained from the information acquisition unit 71 and a parameter group to be read from the storage unit 83 into a preset calculation formula, and the index value at that time point Is calculated. The result is sent to the state determination unit 73 for final determination. Specific processing contents regarding this determination will be described later.

The basic operation in each mode will be described below.
<Basic operation of parameter group formation mode>
Here, the parameter group is formed based on the state of normal operation until the target date to be predicted. In other words, “normal state” defines what combination pattern of acquired data is used. Deviating from it is regarded as an abnormal, ie (potential) fault condition.

  For example, when prediction is performed after n days, a normal state is assumed when no problem has occurred for n consecutive days. The parameter group is determined by the following steps from the acquired information. The processing procedure for determining the index value calculation method (forming the diagnostic parameter group) will be described below with reference to FIG.

  First, data for n days (k types) for the “normal state” defined above is acquired (step S1-1). If a state that is not normal (a failure occurs in any of consecutive n days) is included, the data at that time is not used. This is performed until n days of data are accumulated.

Table 1 shows the data structure. K pieces of data are obtained under the first condition (the first day). Let them be y ₁₁ , y ₁₂ ,..., Y _1k . Similarly, the data obtained under the following conditions (second day) is y ₂₁
, Y ₂₂ ,..., Y _2k , etc., and n sets of data are acquired.

次に、情報の種類（ｊ）ごとに生データ（例えばｙ_ij）を平均値（ｙ_j）と標準偏差（
σ_j）で規格化する（ステップＳ１−２）。表２は、表１に示すデータを数１に示す式を
用いて規格化した結果を示している。

Next, for each type of information (j), the raw data (for example, y _ij ) is _converted into an average value (y _j ) and a standard deviation (y
(σ _j ) is normalized (step S1-2). Table 2 shows the result of normalizing the data shown in Table 1 using the equation shown in Equation 1.

このステップＳ１−１、ステップＳ１−２の処理を、すべてのｉ，ｊについて終了するまで（ステップＳ１−３においてＹＥＳになるまで）繰り返す。そして、すべてのｉ，ｊについて終了した場合（ステップＳ１−３においてＹＥＳの場合）、各規格化情報の相関係数ｒ_pqを算出する（ステップＳ１−４）。すなわち、数２で示す式を用いてｋ種類のうち２組のデータ間の相関係数ｒ_pq（＝ｒ_qp）をすべて求め、それらを数３で示すように行列Ｒで表わす。なお、数２で示す式中の「Σ」は、添字ｉに関する総和を表している。

The processes in steps S1-1 and S1-2 are repeated until all i and j are completed (YES in step S1-3). When the processing is completed for all i and j (YES in step S1-3), the correlation coefficient r _pq of each normalized information is calculated (step S1-4). That is, using the equation shown in Equation 2, all correlation coefficients r _pq (= r _qp ) between two sets of data among the k types are obtained, and these are represented by the matrix R as shown in Equation 3. In addition, “Σ” in the expression shown in Equation 2 represents the sum total regarding the subscript i.

次に、ｋ個の項目の中から、判定しようとする故障内容（例えば紙詰まり、濃度低下、雑音発生など）に応じてｍ個を行列要素として選択する（ステップＳ１−５）。選択のしかたは、予め決められていて、診断する故障の種類と必要な情報の項目の対応が項目指定部（図示せず）の中に格納されている。故障内容を絞らない場合はｍ＝ｋとなる。

Next, from the k items, m are selected as matrix elements according to the content of the failure to be determined (for example, paper jam, density reduction, noise generation, etc.) (step S1-5). The selection method is determined in advance, and the correspondence between the type of failure to be diagnosed and the items of necessary information is stored in an item designation section (not shown). If the details of the failure are not narrowed down, m = k.

Then, the cofactor matrix or inverse matrix is obtained, and the result is represented by the parameter matrix A (a _ij ) as shown in Equation 4 (step S1-6).

以上により、上記単一の指標値の算出するときに用いる算出式における算出パラメータの値（パラメータ行列Ａ）が定まる。ここで扱うデータ群はいずれも正常な状態を表すものであるので、取りこんだ様々な情報間に一定の相関があると考える。正常な状態から離れて故障などの異常が起こりそうになると、これらの相関に乱れが生じて、上記定義した多次元空間における原点（安定状態の平均）からの「距離」が大きくなる。この「距離」が指標値である。このパラメータ群（パラメータ行列Ａ）を記憶部８３（記憶媒体８４）に格納する（ステップＳ１−７）。

As described above, the value of the calculation parameter (parameter matrix A) in the calculation formula used when calculating the single index value is determined. Since the data group handled here represents a normal state, it is considered that there is a certain correlation between the various pieces of information captured. When an abnormality such as a failure is likely to occur away from the normal state, these correlations are disturbed, and the “distance” from the origin (average of the steady state) in the multidimensional space defined above increases. This “distance” is an index value. The parameter group (parameter matrix A) is stored in the storage unit 83 (storage medium 84) (step S1-7).

<Basic operation of state judgment mode>
Hereinafter, a processing procedure in the state determination mode will be described with reference to FIGS. 5 and 6.
As shown in FIG. 5, first, the information acquisition unit 71 acquires the same k types of data acquired in the normal state (step S2-1). Next, the index value calculation unit 72 reads out the parameter group stored in the storage unit 83 (storage medium 84) (step S2-2). Then, an index value is calculated from the acquired plurality of information (step S2-3). Based on the calculated index value, determination is made as described later, and the determination result is output (step S2-4).

<Calculation of index value in state determination mode>
The procedure for calculating the index value will be described with reference to FIG.
As shown in FIG. 6, k types of data x ₁ , x ₂ ,..., X _k in an arbitrary state are acquired (step S3-1). The data types correspond to y ₁₁ , y _{12 ,.} Next, number 5
The data of the acquired information is normalized using the equation shown in (Step S3-2). Here, the normalized data X _1, X _2, · · ·, and X _k.

これをすべての種類について（全jについて）終了するまで（ステップＳ３−３におい
てＹＥＳとなるまで）、jを順次変化させながら繰り返す。

This is repeated while changing j sequentially until it is finished for all types (for all j) (YES in step S3-3).

Next, using the elements of the inverse matrix A is already calculated, the calculation expression shown in Equation 6 to calculate the index value MD ² (step S3-4).

この指標値ＭＤ²の平方根である指標値ＭＤは「マハラノビスの距離」と呼ばれている
。また、数６で示す式中の「Σ」は、添字ｐおよびｑに関する総和を表している。

The index value MD ² of the index value MD is the square root is called the "Mahalanobis distance". In addition, “Σ” in the expression shown in Equation 6 represents the sum total regarding the subscripts p and q.

  In the state deviating from the normal state, the pattern of the input data is different from the pattern of the input data in the normal state, and the degree of deviating from the normal state is reflected in the magnitude of the index value MD. In this example, “normal” means that there is no failure continuously until n days later. Therefore, when the index value MD increases, it indicates that failure is likely to occur within n days.

  Each parameter used in Equations 5 and 6 does not necessarily have to be obtained by a device to be diagnosed in the future as in the processing of the parameter group formation mode shown in FIG. It can also be determined in advance based on the result of an experiment using another type of device or the result obtained by numerical simulation. Further, these parameters may be updated periodically or at a specific time as required, or according to a user instruction.

  Note that the prediction period can be arbitrarily set to improve the efficiency of maintenance work. When the period is set by direct input such as a key or touch panel, or input from a device connected via a communication line, it is reflected in the program that executes the parameter group formation mode, and the normal state is redefined and A parameter group for calculating the index value is formed.

<Specific example of prediction>
Hereinafter, a specific example of prediction will be described. Here, an example will be described in which (1) paper jam, (2) photoconductor deterioration, and (3) image density fluctuation are predicted. Note that specific examples to which the present invention is applied are not limited thereto. For example, the present invention can also be applied to predicting the life (replacement time) of the paper feed roller, transfer belt, and fixing roller.

  In the present embodiment, the following information is used as input information in the failure prediction system 32. Note that the input information for failure prediction is not limited to the following, and for example, the information disclosed in Patent Document 6 can be used as input information for failure prediction.

(1) Temperature As a temperature sensor, a thermocouple that measures using the principle that thermoelectric power is generated by connecting the tip of two different types of metal wires and the temperature difference between the tip and the other end, A resistance temperature detector that uses the property that the electrical resistance of metal increases in proportion to temperature, a thermistor that uses the characteristics of a metal oxide sintered element whose resistance changes greatly with changes in temperature, and a dissimilar metal A bimetal that measures the temperature from a change in shape due to the difference in coefficient of thermal expansion, a full-type thermometer that measures the thermal expansion of the temperature-sensitive part by changing the pressure, and the thermal radiation radiated from the measurement object A radiation thermometer is used.

(2) Humidity Regarding humidity, a humidity sensor that can be made compact is useful in the present invention. Utilizing the fact that the moisture sensing element changes its properties as it absorbs and dehumidifies, and uses water-absorbing substances such as lithium chloride, ceramics, and polymers, and changes in the amount of water vapor, such as electrical resistance and capacitance. What measures as an electrical change is preferable.

(3) Vibration The vibration sensor converts various vibration amounts into electrical quantities such as voltage and current. Piezoelectric sensors using piezoelectric elements such as piezo elements (electric charges are generated by force), strain gauge type Servo type, laser Doppler type speed vibrometer, etc. can be used.

(4) Density (for 4 colors)
The toner density is detected for each color. A conventionally known method can be used as the toner density sensor. For example, it is detected by a sensing system that measures a change in the magnetic permeability of the developer in the developing device as disclosed in JP-A-6-289717.

(5) Charging potential (for 4 colors)
The surface potential of the photoreceptor after charging is measured. As the potential sensor, for example, a conventionally known one as disclosed in JP-A-6-51007 can be used.

(6) Potential after exposure (for 4 colors)
The surface potential of the photoconductor after irradiation with an LD (semiconductor laser) for image exposure is detected in the same manner as in the case of (5) charging potential.

(7) Colored area ratio (4 colors)
From the input image information, the coloring area ratio is obtained for each color from the ratio of the cumulative value of pixels to be colored and the cumulative value of all pixels, and this is used.

(8) Amount of developed toner (for four colors)
The toner adhesion amount developed on the photoreceptor is read by a reflection density sensor. The reflection density sensor irradiates an object with LED light and detects the reflected light with an optical sensor. The relationship between the toner adhesion amount and the reflectance data is preferably grasped in advance for each toner color.

(9) Inclination of paper tip position Optical sensors are installed on the front side and the back side in the paper surface direction at any position along the path from the registration roller to the intermediate transfer belt, and the leading edge position of the conveyed paper is detected. The time to pass is measured with reference to the time when the registration roller drive signal is transmitted, and tilt data with respect to the feed direction is obtained.

(10) Discharge timing The passage timing of the leading edge of the paper after passing the discharge roller is detected by an optical sensor. Also in this case, measurement is performed with reference to the time when the registration roller drive signal is transmitted.

(11) Photoconductor total current (for four colors)
Get all the current flowing from the photoreceptor to ground. Detection is performed by installing a current measuring means between the substrate of the photosensitive member and the ground terminal.

(12) Photoconductor driving power (for four colors)
The driving power (current × voltage) consumed by the driving source (motor) of the photoreceptor is measured by an ammeter / voltmeter.

In the present embodiment, the above 12 types and 33 items of data are employed as input information.
In failure prediction for each type of failure, information on different items is used depending on the type of failure. Table 3 shows the correspondence between failure types and input information with respect to (1) paper jam, (2) photoconductor deterioration, and (3) image density fluctuation as the types of failure. In failure prediction for each failure type, correspondence between failure types and input information as shown in Table 3 is determined in advance, and information corresponding to each failure prediction / diagnosis is used.

ここでは、実際に画像形成装置を稼動させ、５日間故障のなかった場合を「正常な状態」として、該当するデータ５０組を取得する。すなわち、５日間故障のなかった場合を「正常な状態」として、「正常な状態」のデータを５０日分集める。例えば、以下の（例１）、（例２）のように行う。

Here, when the image forming apparatus is actually operated and no failure has occurred for 5 days, the “normal state” is assumed and 50 sets of corresponding data are acquired. That is, the case of no failure for 5 days is regarded as “normal state”, and “normal state” data is collected for 50 days. For example, the following (Example 1) and (Example 2) are performed.

  (Example 1) Collect data when no failure occurred for 55 consecutive days (data for 50 days as “normal state”). In this case, the “normal state” starts from the 6th day, and data for 50 days from the 6th day is collected as the “normal state”.

  (Example 2) Data when failure did not occur for 20 consecutive days (data for 15 days as “normal state”) and data when failure did not occur for 40 consecutive days (35 days as “normal state”) Data) is collected for a total of 50 days of “normal state”.

  In this way, by collecting 50 days of “normal state” data for 33 items, the total number of data becomes 33 × 50. Based on this, normalization of data for each item and generation of a matrix made up of correlation coefficients are performed in accordance with the mathematical formulas shown in Equations 1 to 3.

Hereinafter, an equation for calculating an index value for each type of failure is defined.
(1) In the case of a paper jam, an inverse matrix (or cofactor matrix) of a 13 × 13 matrix having a correlation coefficient between information of the selected seven types of 13 items (circles in Table 3) as an element Form. That is, the parameter matrix of Equation 4 is formed. Thereby, the parameters of the mathematical formulas shown in Equation 5 and Equation 6 for calculating the index value MD are determined, and the index value MD can be defined. Equation 7 is a mathematical expression corresponding to Equation 6 above for the index value MD ₁ in this case.

（２）感光体劣化の場合も同様に、選択された７種類２２項目（表３の○印）の情報間
の相関係数からなる２２行２２列の行列の逆行列（または余因子行列）を形成する。すなわち、上記数４のパラメータ行列を形成する。これを用いて指標値ＭＤを定義することができる。数８は、この場合の指標値ＭＤ₂についての上記数６に対応する数式である。

(2) Similarly, in the case of photoreceptor deterioration, an inverse matrix (or cofactor matrix) of a 22-by-22 matrix composed of correlation coefficients between information of seven selected 22 items (circles in Table 3). Form. That is, the parameter matrix of Equation 4 is formed. The index value MD can be defined using this. Equation 8 is an equation corresponding to the above equation 6 for the index value MD ₂ in this case.

（３）画像濃度変動の場合も同様に、選択された７種類２２項目（表３の○印）の情報間の相関係数からなる２２行２２列の逆行列（または余因子行列）を形成する。すなわち、上記数４のパラメータ行列を形成する。これを用いて指標値ＭＤを定義することができる。数９は、この場合の指標値ＭＤ₃についての上記数６に対応する数式である。

(3) Similarly, in the case of image density fluctuation, an inverse matrix (or cofactor matrix) of 22 rows and 22 columns formed of correlation coefficients between information on the selected seven types and 22 items (circles in Table 3) is formed. To do. That is, the parameter matrix of Equation 4 is formed. The index value MD can be defined using this. Equation 9 is an equation corresponding to the above equation 6 for the index value MD ₃ in this case.

診断時には、表３に示す全項目の情報を取得し、数７、数８、数９の数式に従って（ＭＤ₁、ＭＤ₂、ＭＤ₃）をそれぞれ求める。

At the time of diagnosis, information on all items shown in Table 3 is acquired, and (MD ₁ , MD ₂ , MD ₃ ) are obtained according to the mathematical expressions of Equations 7, 8, and 9, respectively.

According to these mathematical formulas (Equation 7, Equation 8, Equation 9), when the device is operating normally for 5 days, the correlation between the items does not change and the data falls within the expected range. The index value MD (MD ₁ , MD ₂ , MD ₃ ) is a value close to 1.0. On the other hand, if a failure-free state appears within 5 days, the correlation between the information is lost, and data that does not fall within the expected range is obtained. Therefore, the index values MD (MD ₁ , MD ₂ , MD ₃ ) shows a large value. By utilizing this fact, it is possible to predict whether maintenance work is necessary for five days ahead based on information that can be input at that time.

  A threshold is set for each of the index values MD corresponding to each type of failure, and if the value exceeds the threshold value, a warning is issued and an instruction is sent to the maintenance staff to take action. To do. In the present embodiment, as will be described later with reference to Table 4, parts are shipped according to the index value MD, and maintenance work is instructed to maintenance personnel. Each threshold is appropriately determined from data such as the past failure rate. If the image forming apparatus is updated as needed while operating the image forming apparatus, the accuracy of diagnosis can be improved.

Furthermore, in addition to the index values MD (MD ₁ , MD ₂ , MD ₃ ) defined by Equations 7, 8, and 9, an index value MD (MD ₀ ) employing all items is defined. This is shown in Equation 10.

ＭＤ₀の値は、最初の段階の５０組のデータに基づく各情報の相関関係のずれを示すも
のであり、画像形成装置の全般的な状態を表す指標となる。このため、上記（１）紙詰まり、（２）感光体劣化、（３）画像濃度変動の故障に関するもの以外についての診断もすることができる。

The value of MD ₀ indicates a correlation shift of each information based on 50 sets of data in the first stage, and is an index indicating the general state of the image forming apparatus. For this reason, it is possible to make diagnoses other than those relating to (1) paper jam, (2) photoconductor deterioration, and (3) image density fluctuation failure.

  The entire apparatus is diagnosed according to the criteria shown in Table 4. In Table 4, the judgment threshold value for each index value is 10, but it is usually better to set different values based on actual data.

表４に示すように、ＭＤ₀、ＭＤ₁、ＭＤ₂、ＭＤ₃ともすべて判断閾値未満の場合は、判定は正常となり、対応の必要はない。ＭＤ₀が判断閾値未満であって、ＭＤ₁が判断閾値以上の場合、故障（１）の紙詰まりが発生する可能性があると判定される。この場合、故障（１）の紙詰まりの対策として部品交換や調整を行う必要がある。故障（２）、（３）についても、同様に判定が行われ、それぞれについて必要な対応を行う必要がある。

As shown in Table 4, when all of MD ₀ , MD ₁ , MD ₂ , and MD ₃ are less than the determination threshold, the determination is normal and no action is required. If MD ₀ is less than the determination threshold and MD ₁ is greater than or equal to the determination threshold, it is determined that there is a possibility that a paper jam of failure (1) may occur. In this case, it is necessary to replace or adjust parts as a countermeasure against the paper jam of the failure (1). For the failures (2) and (3), the determination is made in the same manner, and it is necessary to take necessary measures for each.

If MD ₀ is greater than or equal to the determination threshold and MD ₁ , MD ₂ , and MD ₃ are all less than the determination threshold, it is determined that there is a possibility of a general failure. It is necessary to take measures.

When MD ₀ is equal to or greater than the determination threshold and MD ₁ is equal to or greater than the determination threshold, it is determined that the paper jam of the failure (1) may occur and a general failure may occur. In this case, it is necessary to replace and adjust parts as a countermeasure against the paper jam of the failure (1), and to investigate the cause and take countermeasures as a general failure countermeasure. For the failures (2) and (3), the determination is made in the same manner, and it is necessary to take necessary measures for each. In Table 4, “Correspondence” is a content prepared by a service person. Depending on the type of failure, it is possible to set a mode for automatic repair or to temporarily limit a specific operation of the apparatus.

In reality, it is considered that MD ₀ is less than the threshold and other MD values rarely exceed the threshold. However, the theoretical possibility cannot be completely denied, so it is necessary to clarify the correspondence. is there.

  Further, for example, the data exchanged in the market is accumulated for the paper feed roller, transfer belt, and fixing roller, and the relationship shown in FIG. 7 is created and stored in the storage unit 83 (storage medium 84). When predicting the remaining life based on this, the previous replacement time is set as the origin (t = 0), and for example, the time (t = t1) at which 10% of the total is expected to fail is within n days. A determination is made as to whether or not to arrive, and if it reaches, failure prediction information for the corresponding part is transmitted to the information management apparatus 20.

(Basic operation of state determination of image forming apparatus 30)
In the present embodiment, the index value calculation parameter for predicting the failure of the image forming apparatus 30 is determined in advance. A basic operation of the state determination of the image forming apparatus 30 in the present embodiment will be described with reference to FIG.

As shown in FIG. 8, when the system (image forming system) of the image forming apparatus 30 is activated (
In step S4-1), the state determination process is performed as follows.
First, the failure prediction system 32 detects whether or not the storage medium 84 is attached to the main body of the image forming apparatus 30 (step S4-2).

  If the storage medium 84 is not attached (NO in step S4-2), the failure prediction system 32 displays a warning on the display unit of the image forming apparatus 30 (step S4-3). This is repeated until it is attached, and it does not proceed to the following steps until it is attached. However, image formation is performed.

  When it is detected that the storage medium 84 is attached (YES in step S4-2), the failure prediction system 32 executes a state determination mode (step S4-4). If it is determined that there is a failure prediction, the failure prediction system 32 executes processing according to the failure prediction. In the present embodiment, the state determination unit 73 transfers determination result data to the transmission unit 33, and the transmission unit 33 transmits failure prediction information to the information management device 20.

  In addition, as a process according to failure prediction, the failure prediction system 32 may automatically respond. Automatic responses include output of results (for example, display, audio output, recording to a recording medium), transmission of results, storage, device stop, device operation restrictions and control changes (for example, color mode change, Changing the recording speed, changing the number of lines for halftone reproduction, changing the halftone processing method, changing the paper type, changing the registration adjustment parameters, image formation parameters (in the case of an electrophotographic method, charging potential, exposure amount, development bias) ), Transfer bias, etc.)), automatic repair, etc. On the other hand, when parts (including consumables) need to be replenished / replaced, it is necessary to prepare the necessary parts (including consumables). In this case, in this embodiment, the following processing is performed automatically. The delivery instruction is sent to the installation location of the image forming apparatus 30. As a result, it is not necessary for maintenance personnel to bring parts to be used for troubleshooting.

(Information management device processing)
The failure prediction information receiving unit 22 receives failure prediction information transmitted from the transmission unit 33 of the image forming apparatus 30 through the communication line 61 when an abnormal prior event occurs in the image forming apparatus 30 connected by the communication line 61. Receive (step S5-1). The failure prediction information includes a failure prediction date (a day when a predicted failure is performed after n days), a model identifier that has transmitted the failure prediction information, a serial number, the above-mentioned (1) paper jam, (2) photoconductor deterioration, (3) Information on a predicted failure type such as image density fluctuation, a corresponding type (preparation for parts replacement / adjustment), and the like is included. The failure prediction information receiving unit 22 transfers the received failure prediction information to the component specifying unit 23.

  The component identifying unit 23 searches and extracts the component number and the component name recorded in the device component information storage unit 26 based on the model identifier, the predicted failure type, and the corresponding type (step S5-2). ). The component identification unit 23 transfers the extracted component number, information about the component name, and failure prediction information to the component delivery instruction information transmission unit 24 and the terminal notification information transmission unit 25, respectively.

  The component delivery instruction information transmission unit 24 transmits component delivery instruction information including data related to a failure prediction date, a model identifier, a manufacturing number, a component number, and a component name to the component order management device 40 (step S5-3).

  The control unit 41 of the component order management apparatus 40 searches the device installation information storage unit 42 for information related to the installation position of the device based on the model identifier and the manufacturing number of the received component delivery instruction information. Then, the part order management device 40 instructs delivery of the part specified by the part delivery instruction information to the installation position based on the information related to the found installation position. Based on this, the part specified by the part delivery instruction information is delivered to the place where the device is installed.

  On the other hand, the terminal notification information transmitting unit 25 includes terminal prediction information including failure prediction notification information based on the failure prediction information, and part delivery notification information including data related to a failure prediction date, a model identifier, a manufacturing number, a part number, and a part name. Information is transmitted to the maintenance staff terminal 50 (step S5-4). Based on this, maintenance personnel perform the following processing.

(Maintenance work plan by maintenance personnel)
When the maintenance notification terminal 50 receives the terminal notification information by the reception unit 51, the maintenance staff terminal 50 records the reception information in the reception information recording unit 52 and transfers the failure prediction notification information included in the terminal notification information to the visit request notification unit 53. Based on the failure prediction notification information, a visit request including the model identifier, serial number, and failure prediction content is displayed on the display unit 54. Based on this, the maintenance staff plans maintenance work, and visits the customer where the image forming apparatus 30 is installed to perform the maintenance work. Processing for planning maintenance work in the maintenance staff terminal 50 will be described with reference to FIG.

  When the terminal notification information is received by the maintenance staff terminal 50, the maintenance staff performs maintenance work reflecting countermeasures against failure prediction after n days according to the processing procedure shown in FIG. 10 based on the visit request displayed on the maintenance staff terminal 50. To plan.

  First, based on the failure prediction notification information, the maintenance worker inputs the failure prediction result (failure prediction after n days) to the maintenance worker terminal 50 (step S6-1). Then, the maintenance staff confirms the necessity of maintenance work (step S6-2). Specifically, the necessity of maintenance work is confirmed based on information on the type of failure, the determination result, and the necessary response included in the failure prediction notification information. If maintenance work is not required (NO in step S6-2), the maintenance staff inputs a work end instruction and ends the maintenance work plan process.

  If maintenance work is necessary (YES in step S6-2), the contents are listed (step S6-3). Specifically, when there is a failure prediction for a specific type of failure, the countermeasures for that failure are listed. In addition, when the occurrence of a failure is predicted for a specific failure and the possibility of occurrence of a general failure is predicted, the general failure measures are listed together with the measures for the specific failure. Then, the maintenance staff prepares the work based on this content and makes a detailed work plan.

  At this time, since the maintenance staff can confirm the delivery date of the necessary parts based on the parts delivery instruction notification information in the terminal notification information, the maintenance staff can grasp the time when the necessary parts have arrived. For this reason, a visit plan is made so that work is performed after the necessary parts arrive. Therefore, the maintenance staff can perform appropriate maintenance work without bringing necessary parts. Further, if the customer is visited at the timing when the necessary parts arrive and work can be performed immediately based on the delivery instruction notification information, it is not necessary to store the parts that have arrived at the customer destination for a long period of time.

As described above, according to the present embodiment, the following effects can be obtained.
In the above embodiment, the image forming apparatus 30 performs failure prediction of the image forming apparatus 30 using the failure prediction system 32, and transmits failure prediction information to the information management apparatus 20 when there is failure prediction. And the information management apparatus 20 specifies a required component using the apparatus component information storage part 26 based on this failure prediction information. Then, the information management device 20 transmits component delivery instruction information to the component order management device 40 in order to deliver the identified component to the installation location of the image forming device 30, and the component order management device 40 includes a device installation information storage unit. The installation location of the image forming apparatus 30 is specified using 42, and processing for delivering parts is performed. Further, the information management apparatus 20 transmits failure prediction notification information for notifying information regarding failure prediction and component delivery notification information for notifying information regarding component delivery to the maintenance staff terminal 50. Thereby, based on the result of failure prediction for the image forming apparatus 30 to be managed, necessary parts can be delivered to the installation location of the device, and information regarding failure prediction and parts delivery can be notified to the maintenance staff. Therefore, the necessary parts can be delivered accurately and quickly to the installation location of the equipment, and the maintenance staff does not have to prepare the necessary parts by himself / herself, and thus can quickly go to the installation location of the equipment.

  In the above-described embodiment, each image forming apparatus 30 includes the failure prediction system 32, and performs failure prediction of the image forming apparatus 30, and transmits failure prediction information to the information management apparatus 20 when there is failure prediction. As a result, each image forming apparatus 30 to be managed makes a failure prediction, and the information management apparatus 20 can perform a process for supporting the necessary parts delivery using the result of the failure prediction.

In addition, you may change the said embodiment into the following aspects.
In the above embodiment, the device order information storage unit 42 is provided in the component order management device 40. When it is necessary to deliver a part, the information management apparatus 20 transmits part delivery instruction information to the part order management apparatus 40, and the part order management apparatus 40 determines the installation location of the image forming apparatus 30 to which the part is delivered. Identified. Instead of this, the information management device 20 may specify the installation location of the image forming apparatus 30 that is the delivery destination of the parts. For example, the device installation information storage unit 42 may be provided in the information management device 20, and the information management device 20 may search for data in the device installation information storage unit 42.

  In the above embodiment, the device installation information storage unit 42 records the customer's address and name as the information about the installation location of the image forming apparatus 30 and the location information acquired by the GPS location specifying means, and stores the model identifier / manufacturing The installation location of the image forming apparatus 30 is specified by searching for information regarding the installation location based on the number. The information regarding the installation location recorded in the device installation information storage means may not be such information that directly specifies the installation location. For example, information for specifying the image forming apparatus 30 is recorded as information regarding the installation location, and each image forming apparatus 30 includes a position specifying unit using GPS. When the failure is predicted, the installation position of the image forming apparatus 30 where the failure is predicted may be specified by the position specifying unit provided in the image forming apparatus 30.

  In the above embodiment, each image forming apparatus 30 performs failure prediction, and transmits information related to the result of failure prediction to the information management device 20. Alternatively, an information management apparatus that can be connected to the image forming apparatus may perform failure prediction for each image forming apparatus. For example, the information management apparatus may acquire various types of information acquired by the information acquisition unit 71 of the above-described embodiment from each image forming apparatus and perform failure prediction of each image forming apparatus.

  In the above embodiment, the image forming apparatus is targeted. However, the device to be managed is the device to be subjected to maintenance work by the visit of the maintenance staff, and it may be necessary to prepare parts. The present invention may be applied to any device as long as it is present.

1 is a schematic diagram of a system according to an embodiment of the present invention. 1 is a functional block diagram of an image forming apparatus. The functional block diagram of a maintenance worker terminal. Explanatory drawing of the process sequence of diagnostic parameter group formation. Explanatory drawing of the process sequence of failure prediction determination. Explanatory drawing of the process sequence of calculation of an index value. Explanatory drawing for demonstrating the replacement timing of components. Explanatory drawing of the process sequence at the time of system operation | movement of an image forming apparatus. Explanatory drawing of the process sequence of the required components delivery assistance process of an information management apparatus. Explanatory drawing of the process sequence of the maintenance work plan draft of the maintenance worker using a maintenance worker terminal.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 20 ... Information management apparatus, 26 ... Equipment part information storage part as equipment part information storage means, 30 ... Image forming apparatus, 32 ... Failure prediction system, 40 ... Parts order receiving management apparatus, 42 ... Equipment as equipment installation information storage means Installation information storage unit, 50 ... maintenance personnel terminal.

Claims (5)

A device to be managed, comprising: a device part information storage unit that records the failure content of the device and a component used for handling the failure in association with each other; and a device installation information storage unit that records information about the installation location of the device in association with the device. A necessary parts delivery support system that performs processing for delivering the necessary parts based on the failure prediction of and transmits notification information to the maintenance staff terminal based on the failure prediction,
A computer provided in the necessary parts delivery support system,
Failure prediction means for predicting failure of managed devices;
Based on the result of the failure prediction, a component identifying unit that identifies a necessary component using the device component information storage unit;
A delivery processing means for performing a process for delivering the component by specifying an installation location of the equipment using the equipment installation information storage means;
Necessary component delivery support, which functions as a notification information transmission means for transmitting failure prediction notification information for notifying information on the failure prediction and component delivery notification information for notifying information on delivery of the components to a maintenance staff terminal system. The necessary parts delivery support system includes an information management device connectable to the device,
The device functions as the failure prediction means, and the device transmits information on the result of failure prediction by the failure prediction means to the information management device,
The necessary information delivery support system according to claim 1, wherein the information management device executes processing using information related to the result of the failure prediction.   3. The necessary component delivery support system according to claim 1, wherein the device is an image forming apparatus. Necessary parts delivery support provided with equipment part information storage means for recording the equipment failure contents and parts used for dealing with the equipment in association with each other, and equipment installation information storage means for recording information about the installation location of the equipment in association with the equipment A necessary parts delivery support method that performs processing for delivering necessary parts based on a failure prediction of a managed device using a system and transmits notification information to a maintenance staff terminal based on the failure prediction. There,
A computer provided in the necessary parts delivery support system,
A stage for predicting failure of managed equipment;
Identifying the necessary parts using the equipment part information storage means based on the failure prediction results;
Performing a process for specifying the installation location of the device using the device installation information storage means and delivering the component;
A necessary parts delivery support method, comprising: transmitting failure prediction notification information for notifying information on the failure prediction and parts delivery notification information for notifying information on delivery of the parts to a maintenance staff terminal. Parts required based on the failure prediction of the managed device using the device part information storage means that records the device failure contents and the parts used for the failure in association with each other and the computer that can be connected to the managed device A necessary parts delivery support program for sending notification information to the maintenance staff terminal based on the failure prediction,
The computer,
A failure prediction result receiving means for receiving information on a failure prediction result of the device from a device to be managed;
Based on the result of the failure prediction, a component identifying unit that identifies a necessary component using the device component information storage unit;
Delivery instruction means for instructing delivery of the identified part to an installation location of the device;
Necessary component delivery support characterized by causing failure prediction notification information for notifying information on failure prediction and component delivery notification information for notifying information on delivery of the components to function as notification information transmitting means for transmitting to a maintenance staff terminal program.

Images