JP2012008974A - Diagnosis device and method for industrial machine and program and recording medium for computer - Google Patents

Abstract

PROBLEM TO BE SOLVED: To easily and appropriately perform the diagnosis of productivity or quality under the consideration of the inspection result of an industrial machine concerning a diagnosis device and a diagnosis method of the industrial machine.SOLUTION: This diagnosis device of the industrial machine is configured such that an input part inputs a machine symptom in machine stop, and that a processing part estimates an occurrence factor event of machine stop from the input machine symptom by referring to the association data of the machine symptom with the occurrence factor event as the occurrence factor of the machine symptom, and estimates, by referring to the association data of a machine inspection result with the occurrence factor event assumed from the machine inspection result, the occurrence factor event from a machine failure item obtained in inspection, and specifies the occurrence factor event as the factor of machine stop from a difference between the occurrence factor event estimated from the machine symptom and the occurrence factor event estimated from the machine failure item.

Description

  The present invention relates to an industrial machine diagnostic apparatus and method, a computer program, and a recording medium suitable for maintenance and management of industrial machines.

  In factories that produce or process various products, in order to efficiently produce or process products of superior quality with industrial machines, maintenance such as replacement of consumable parts of the machine is performed appropriately, or larger than the parts. It is necessary to appropriately exchange machine elements (component machines constituting industrial machines). In addition, it is desirable to replace expensive parts or basically expensive constituent machines at an appropriate timing in consideration of the investment effect.

  In order to judge the replacement of parts and component machines from the aspect of investment effect, the original production capacity of the machine (theoretical maximum production volume, ideal production volume) and the actual production state of the machine (actual production volume) It is necessary to grasp that. In other words, since the performance of components and component machines gradually deteriorates due to deterioration over time during use, the quality of products to be produced or processed and the production efficiency are lowered. Therefore, if the impact of cost due to deterioration of parts and component machines is grasped from the ideal production volume and actual production volume, and if parts or component machines can be replaced or repaired at an appropriate timing, high productivity can be achieved. Can be secured.

  The timing of grasping the ideal production quantity and actual production quantity of such machines and the replacement of parts and component machines based on this can be judged by the factory side, but it is decided by the machine manufacturer who is familiar with the machine equipment. However, it is more efficient to propose to the factory side. For this reason, a sales servant on the machine manufacturer's side obtains data about the machine from the factory side, grasps the actual production volume, calculates the ideal production volume, and based on these, the parts at an appropriate timing Proposals are made for the factory (customer) to replace the machine and the machine.

  For example, FIG. 11 shows various types implemented by the machine manufacturer who delivered the corrugator 2 or the box making machine 3 to an industrial machine such as the corrugator 2 or box making machine 3 installed in the cardboard factory 1 that manufactures the cardboard product. It is a figure explaining the form of this service. As shown in FIG. 11, the service person M1 collects operation data regarding the corrugator 2 and the box making machine 3 installed from the corrugated board factory (customer) 1 side, and based on this, the actual production amount and the ideal production amount are collected. Calculate production volume.

  The service person M1 analyzes the productivity based on the ideal production amount and the actual production amount, obtains products (corrugated cardboard sheets and cardboard boxes), analyzes the quality status, and analyzes the productivity / quality analysis. Create a report, create a recommended construction proposal that recommends replacement of parts and component machines at an appropriate timing based on the report, and propose it to the factory (customer). As a result, machine manufacturers can expect orders for work such as equipment replacement.

  On the other hand, for maintenance, a maintenance manager M2 on the machine maker's side goes to the corrugated board factory 1 to perform maintenance inspection and maintenance of the corrugator 2 and the box making machine 3, etc. separately from the service person. This maintenance inspection and maintenance may be performed periodically, or may be performed at the request of the factory due to some trouble in the machine. At this time, the maintenance manager M2 creates a machine inspection report and submits it to the factory side (customer) and uses it for subsequent maintenance management.

  As a technique related to maintenance inspection, there is a maintenance inspection system for a construction machine described in Patent Document 1. In this technology, when model information and user information of a construction machine in which a failure has occurred are set and input by a user terminal computer, the machine information acquisition means of the server recognizes it via the Internet, and the server recognizes the construction machine based on the model information. A program for executing the corresponding maintenance inspection flow is output to the user terminal computer via the Internet. Thereby, it is possible to easily inspect according to the inspection procedure information without requiring specialized knowledge, and if the problem is relatively minor, the user can deal with it, and the maintenance inspection cost of the machine can be reduced.

JP 2003-178148 A

By the way, the actual production amount necessary for the work of the serviceman M1 can be automatically obtained if the operation history of the machine is recorded. However, the ideal production amount is obtained by the serviceman M1 collecting his own data. Therefore, it takes a very long time to calculate, and there is no quick response, and it becomes a burden on the service person M1.
The productivity and quality analyzed by the serviceman M1 depend on the state of the machine. On the other hand, the machine inspection result obtained by the maintenance manager M2 includes information indicating the state of the machine. It is. However, since the productivity analysis and quality analysis created by the serviceman M1 and the machine inspection result obtained by the maintenance manager M2 are not particularly linked, the report created by the serviceman M1 from each analysis is It does not reflect the result of machine inspection, and the impact on the customer is weak in this respect.

From the results of productivity and quality analysis, if there are any problems, we will consider a recommended proposal (replacement of component machines, modification, parts replacement, adjustment), but this is also left to the skill of serviceman M1, Inexperienced serviceman M1 may not be able to present an accurate proposal.
In addition, since the cost and price required for each proposal cannot be calculated promptly at the customer site, the investment amount and the investment effect cannot be presented to the customer-side person in charge M3 by an estimate or the like. Reports will be made with unclear priorities.

For this reason, negotiations regarding recommended proposals will not proceed smoothly, and the costs and prices required for recommended proposals will be presented to the customer again at a later date. It will decline and you will lose the opportunity to accept orders.
Further, in this case, the factory side may be in an unfavorable state from the viewpoint of production efficiency due to delays in measures.

  The present invention was devised in view of such problems, and an industrial machine diagnostic apparatus that can easily and appropriately diagnose productivity and quality while considering the inspection results of industrial machines. And a diagnostic method for an industrial machine that can disclose a proposal necessary from the diagnosis result, a cost required for the proposal, and the like linked to the diagnosis result. It is another object of the present invention to provide a computer program and a recording medium.

  In order to achieve the above object, an industrial machine diagnostic apparatus according to the present invention includes an information input unit, a data processing unit connected to the information input unit, and a data storage unit connected to the data processing unit. An industrial machine diagnostic apparatus comprising: a machine symptom at the time of a machine stop and an occurrence cause event of the machine symptom with respect to the industrial machine (or an industrial machine of the same type as the industrial machine) in the data storage unit. Corresponding first data corresponding to the machine failure matter obtained by machine inspection with respect to the industrial machine (or the same kind of industrial machine as the industrial machine) and the occurrence cause event assumed from the machine failure matter Second data is stored, and the data processing unit is stored in the data storage unit and information on the machine symptom related to the machine stop input to the information input unit Based on the first data, first estimation means for estimating the occurrence cause event related to the machine stop, the machine malfunction matter input to the information input unit, and the data storage unit stored in the data storage unit Based on the second data, the second estimation means for estimating the occurrence cause event assumed from the machine trouble matter, the occurrence cause event estimated by the first estimation means, and the second estimation means Machine stop cause specifying means for specifying the occurrence cause event that caused the machine stop based on the difference from the estimated occurrence cause event.

The apparatus further comprises inspection result extraction means for extracting a machine defect item from the result of the machine inspection input to the information input unit, and the machine defect item used for estimation by the second estimation unit is extracted by the inspection result extraction unit. It is preferred that
The data storage unit further stores third data associating the occurrence cause event with a countermeasure against the occurrence cause event with respect to the industrial machine (or an industrial machine of the same type as the industrial machine), and the data processing The unit selects a countermeasure for the identified occurrence cause event based on the occurrence cause event identified by the machine stop cause identification means and the third data stored in the data storage unit Preferably further means are provided.

  And a display unit connected to the data processing unit, wherein the display unit displays the machine symptom related to the machine stop related to the estimation by the first estimation unit and the occurrence cause event in correspondence with each other. Display, a second display for displaying the machine malfunction matter and the occurrence cause event related to the estimation by the second estimation means, and the occurrence cause event specified by the machine stop cause specifying means according to the display. A third display for displaying the correspondence between the machine symptom and the machine malfunction item, and a fourth display for displaying the countermeasure selected by the countermeasure selection means corresponding to the machine symptom, the occurrence cause event, and the machine malfunction item. It is preferable that at least one of display is performed.

  The data processing unit includes a production amount calculating means for calculating an actual production amount and an ideal production amount of the industrial machine from machine operation data and machine specification data of the industrial machine input to the information input unit, From the machine stop time information from the production amount, the information on the machine symptom related to the machine stop input to the information input unit, and the actual production amount and the ideal production amount calculated by the production amount calculation means A production loss amount calculating means for calculating a production loss amount of the industrial machine for each machine symptom, and the display unit displays the production loss amount calculated by the production loss amount calculation means as the machine symptom or It is preferable that a fifth display corresponding to the machine trouble matter is displayed.

  The data storage unit further stores fourth data in which the measure selected by the measure selection means and the actual price required for the measure are associated with each other, and the fifth display by the display unit includes A plurality of the countermeasures are displayed in a list, and the data processing unit displays countermeasure selection information selected and input by the information input unit from among the countermeasures listed as the fifth display, and the data storage unit. Price calculation means is further provided for calculating an actual price corresponding to the selected and inputted countermeasure based on the stored fourth data, and the display section includes the selected and inputted countermeasure, and the price. It is preferable to perform a sixth display for correspondingly displaying the actual price corresponding to the selected and inputted measure calculated by the calculating means.

In the data processing unit, an investment for calculating an investment effect from the production loss amount calculated by the production loss amount calculation unit and the actual price corresponding to the selected and inputted measure calculated by the price calculation unit It is preferable that an effect calculation unit is further provided, and that the display unit displays a seventh display in which the investment effect calculated by the investment effect calculation unit is displayed in correspondence with the machine symptom or the second event.
In the seventh display, the investment effect is preferably displayed with a priority.

It is preferable that the data processing unit further includes a report creation unit that automatically creates a diagnostic report regarding a preset item from the processing results.
In the data processing unit, it is preferable that the processing of each unit is executed when the industrial machine is stopped.
The data storage unit includes fifth data in which a quality item of a product produced by the industrial machine and a reference value related to the quality item are associated with each other, a quality error of the product, and a machine malfunction matter that causes the product Sixth data associated with each quality item is further stored, and the data processing unit stores the quality measurement result of the product input to the information input unit and the data storage unit. Based on the fifth data, determination means for determining whether the quality of the product satisfies a quality standard for each quality item, and the quality of the product does not satisfy the quality standard by the determination means If it is determined that there is a quality error, a machine malfunction that causes the quality error based on the quality item that is regarded as the quality error and the sixth data stored in the data storage unit. Third estimation means for estimating machine inspection results extracting means for extracting machine defect items from the machine inspection results input to the information input unit, machine defect items estimated by the third estimation means, and the inspection It is preferable that the apparatus further includes a machine defect identification unit that identifies the machine defect item that causes the quality error based on the difference from the machine defect item extracted by the result extraction unit. The quality standard is a standard value related to quality items.

  Another industrial machine diagnostic apparatus according to the present invention includes an information input unit, a data processing unit connected to the information input unit, and a data storage unit connected to the data processing unit. The data storage unit includes fifth data in which a quality item of a product produced by the industrial machine is associated with a reference value related to the quality item, a quality error of the product, and a machine that causes the product Sixth data in which defect items are associated with each quality item is stored, and the data processing unit stores the quality measurement result of the product input to the information input unit and the data storage unit Determination means for determining whether the quality of the product satisfies the quality standard for each quality item based on the fifth data, and the quality of the product satisfies the quality standard by the determination means Shi If it is determined that there is a quality error, a machine defect matter that causes the quality error based on the quality item that is the quality error and the sixth data stored in the data storage unit Third estimation means for estimating machine inspection results extracting means for extracting machine defect items from the machine inspection results input to the information input unit, machine defect items estimated by the third estimation means, and the inspection Machine defect identifying means for identifying the machine defect item causing the quality error based on the difference from the machine defect item extracted by the result extracting means is provided.

  The data storage unit further stores seventh data in which the machine malfunction item and the countermeasure against the machine malfunction item are associated with each other, and the data processing unit stores the machine identified by the machine malfunction item identification unit. It is preferable that a quality countermeasure selecting unit is further provided for selecting a countermeasure for the identified machine defect item based on the defect item and the seventh data stored in the data storage unit.

  The display unit further includes a display unit connected to the data processing unit, and the display unit determines that the quality of the product does not satisfy the quality standard and is a quality error by the determination unit. An eighth display for displaying the quality item determined to be an error, and a ninth display for displaying the machine malfunction matter estimated by the third estimation means in correspondence with the quality item related to the quality error. The tenth display for displaying the machine defect matter extracted by the inspection result extraction means, and the corresponding display of the quality item of the quality error and the machine failure matter identified by the machine failure matter identification means. 11 displays the countermeasure selected by the quality countermeasure selecting means, the quality item of the quality error, and the specified machine malfunction item. 12 the display of that, it is preferable that at least any is performed.

  The data storage unit further stores eighth data in which the measure selected by the quality measure selecting means and the actual price required for the measure are associated with each other, and is displayed on the twelfth display by the display unit. A plurality of the countermeasures are displayed in a list, and the data processing unit selects countermeasure input information selected and input by the information input unit from the countermeasures listed as the twelfth display, and the data storage unit Price calculation means for calculating an actual price corresponding to the selected and inputted measure based on the eighth data stored in the display, and the display unit includes the selected and inputted measure, and It is preferable that a thirteenth display for correspondingly displaying the actual price calculated by the price calculation means and the selected and inputted countermeasure is performed.

It is preferable that the data processing unit further includes a report creation unit that automatically creates a diagnostic report on a preset item from each processing result on the quality.
Each of the data stored in the data storage unit is preferably updated based on new acquired data.
It is preferably configured using a mobile personal computer.

  The industrial machine diagnosis method according to the present invention includes, in advance, first data in which a machine symptom at the time of a machine stop that has occurred in the past with respect to the industrial machine is associated with an occurrence cause event that has caused the machine symptom. First machine data corresponding to the machine failure matter obtained from the machine inspection with respect to the industrial machine and the occurrence cause event assumed from the machine failure matter is prepared, and information on the machine symptom related to the machine stop is prepared And based on the first data, the first step of estimating the occurrence cause event related to the machine stop, the machine malfunction matter related to the machine inspection result, and the second data, the machine A second step of estimating the cause-of-occurrence event assumed from a defect, the cause-of-occurrence event estimated from information on the machine symptom, and the machine failure From difference between the cause events assumed from engagement matters, it is characterized by a third step of identifying the cause event that caused the machine stop.

  In advance, fifth data in which quality items of products produced by the industrial machine are associated with reference values related to the quality items, quality errors of the product that have occurred in the past, and machine malfunction items that cause the product Sixth data corresponding to each quality item is further prepared, and based on the quality measurement result of the product and the fifth data, whether the quality of the product satisfies the quality standard A fourth step of determining for each quality item; and if the quality of the product does not satisfy the quality standard and is determined to be a quality error by the fourth step, the quality item determined as the quality error; , Based on the sixth data, a fifth step of estimating a machine fault matter causing the quality error, a sixth step of extracting a machine fault matter from the machine inspection result, A seventh step of identifying the machine fault matter causing the quality error from the difference between the machine fault matter estimated in the fifth step and the machine fault matter extracted in the sixth step; It is also preferable to have it.

  Another industrial machine diagnosis method according to the present invention includes, in advance, fifth data in which a quality item of a product produced by the industrial machine is associated with a reference value related to the quality item, and the product generated in the past. 6th data in which the quality error and the machine malfunction matter causing the quality error are associated for each quality item, and based on the quality measurement result of the product and the 5th data, A fourth step for determining whether the quality satisfies the quality standard for each quality item, and the fourth step determines that the quality of the product does not satisfy the quality standard and is a quality error. And a fifth step of estimating a machine malfunction item causing the quality error based on the quality item determined as the quality error and the sixth data, and a machine defect from the machine inspection result. The machine failure matter that caused the quality error from the difference between the machine failure matter estimated in the sixth step, the fifth step, and the machine failure matter extracted in the sixth step. And a seventh step of specifying

The industrial machine diagnosis program according to the present invention is characterized in that each step of the above-described industrial machine diagnosis method is programmed so as to be controllable by a computer.
The recording medium of the present invention is characterized in that the above-mentioned industrial machine diagnostic program is recorded in a computer-readable format.

  According to the present invention, when there is a machine stop, the pre-stored data is used to estimate the cause-cause event that caused the machine symptom at that time, and from the machine trouble matter obtained by machine inspection. Estimate the possible cause events and identify the cause event that caused the machine stop from the difference between these estimated cause events, so that the cause event that caused the machine stop is more accurate. Therefore, it is possible to easily and appropriately diagnose the productivity of industrial machines.

In addition, an appropriate proposal can be made by selecting a countermeasure for the specified occurrence cause event using data stored in advance.
In addition, the display section shows the general correspondence between the machine symptom and the cause-cause event, the general correspondence between the machine fault and the cause-cause event, the identified cause-cause event and the machine symptom related to this, Easily visually check various information related to machine stoppage by displaying the correspondence with machine failure items, the selected countermeasures and the corresponding machine symptom, occurrence event, and the corresponding relationship between the machine failure items. can do.

In addition, if a selection operation is selected from the countermeasures displayed in a list on the display unit, the actual price corresponding to the selected countermeasure is calculated and displayed based on the stored data. It is possible to consider the implementation of countermeasures.
Further, if the investment effect is calculated and displayed from the production loss amount due to the machine stop and the actual price corresponding to the selected and inputted measure, the implementation of the measure can be considered while considering the investment effect.

At this time, if the investment effects are displayed with priorities, they can be used as a reference for considering the implementation of countermeasures, and the implementation of countermeasures can be examined more actively.
By automatically creating a diagnostic report on preset items from each processing result, implementation of countermeasures can be considered based on the diagnostic report.
If each of the above processes is executed when the industrial machine is stopped, the processes can be performed efficiently and clearly.

  According to another aspect of the present invention, when product quality is measured, data stored in advance is used to determine whether the product quality satisfies quality standards for each quality item. If the quality error is not satisfied, the pre-stored data is used to estimate the machine fault that causes the quality error, and the machine fault extracted from the machine inspection result is estimated. Because the machine defect item that caused the quality error is identified from the difference from the machine defect item, the machine defect item that caused the quality error can be estimated more accurately, and the product produced by the industrial machine Diagnosis relating to the quality of the product can be performed easily and appropriately.

Furthermore, an appropriate countermeasure can be guided by selecting a countermeasure for the specified machine malfunction item using data stored in advance.
In addition, by appropriately displaying the quality items that have been regarded as quality errors, machine failure items, machine failure items extracted from inspection results, identified machine failure items, and selected countermeasures on the display section Various information related to the machine stop can be easily recognized.

Furthermore, by calculating the actual price corresponding to the countermeasure selected and inputted from the countermeasures displayed in the list and displaying these correspondingly, the implementation of the countermeasure can be examined while considering the actual price.
In this case as well, by automatically creating a diagnostic report on a preset item from each processing result, implementation of countermeasures can be considered based on the diagnostic report.

If each data stored in the data storage unit is updated based on newly acquired data, more appropriate estimation, determination, identification, and selection can be performed.
Furthermore, if this apparatus is configured using a mobile personal computer, for example, a person in charge from the manufacturer side of the production machine goes to the factory side where the production machine is installed, and performs the above processes, thereby improving productivity. And the machine improvement items related to quality can be explained in an easy-to-understand manner to the person in charge at the factory.

It is a block diagram explaining the apparatus structure concerning 1st Embodiment of this invention. It is a schematic diagram explaining the diagnostic process concerning 1st Embodiment of this invention. It is a flowchart explaining the diagnostic process concerning 1st Embodiment of this invention. It is a figure explaining the example of data used for the diagnostic process concerning 1st Embodiment of this invention. It is a figure explaining the example of a display about the diagnostic processing concerning a 1st embodiment of the present invention. It is a block diagram explaining the apparatus structure concerning 2nd Embodiment of this invention. It is a schematic diagram explaining the diagnostic process concerning 2nd Embodiment of this invention. It is a flowchart explaining the diagnostic process concerning 2nd Embodiment of this invention. It is a figure explaining the example of data used for the diagnostic process concerning 2nd Embodiment of this invention. It is a figure explaining the example of a display about the diagnostic processing concerning 2nd Embodiment of this invention. It is a schematic diagram explaining the diagnostic process concerning background art.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
1 to 5 illustrate the first embodiment of the present invention, and FIGS. 6 to 10 illustrate the second embodiment of the present invention.

[First Embodiment]
First, a first embodiment of the present invention will be described with reference to FIGS. The present embodiment relates to diagnosis (analysis) of productivity of industrial machines.
In the present embodiment, as shown in FIG. 2, a diagnosis for an industrial machine such as a corrugator 2 or a box making machine 3 installed in a corrugated cardboard factory 1 for producing a corrugated cardboard product will be described. It is not limited to.

<Overview>
First, the situation where the apparatus and method according to the embodiment are applied will be described. As shown in FIG. 2, a corrugated board factory 1 that manufactures corrugated board products is equipped with industrial machines such as a corrugator 2 and a box making machine 3. Yes. For such machinery, the person in charge on the factory side routinely maintains and manages it, but on the other hand, the machine manufacturer who delivered the corrugator 2, box making machine 3, etc. The service is implemented.

That is, the service person M1 collects operation data related to the installed corrugator 2 and box making machine 3 from the corrugated cardboard factory (customer) 1 side, and grasps and analyzes the state of the machinery based on this.
On the other hand, for maintenance, a maintenance manager M2 on the machine maker's side goes to the corrugated board factory 1 to perform maintenance inspection and maintenance of the corrugator 2 and the box making machine 3, etc. separately from the service person. This maintenance inspection and maintenance may be performed periodically, or may be performed at the request of the factory due to some trouble in the machine. The maintenance manager M2 can collect the status of each part of the machinery through maintenance inspection and maintenance.

  In this embodiment, when the machine stops due to some trouble during operation, the cause of the machine stop is approached from the data obtained from the operation status, and the cause of the machine stop is also approached from the maintenance management information. Thus, the cause of the machine stoppage is to be estimated with high accuracy from both sides. Furthermore, measures for eliminating machine stoppages and costs for such measures can be provided promptly. In addition, a diagnostic report on the state of the machine obtained by collecting from various aspects can be automatically created so as to achieve more effective operation of the machine.

<Overall configuration>
As shown in FIG. 1, the industrial machine diagnostic apparatus according to the present embodiment includes a data input unit (information input unit such as a keyboard or a mouse) 11 and a data processing unit (CPU) to which the data input unit 11 is connected. , An information processing unit comprising a memory, etc.) 12, a data storage unit (large capacity memory) 13 connected to the data processing unit 12, and a processing result display unit (display unit, monitor display) connected to the data processing unit 12 14 and the computer 10.
The data storage unit 13 stores the following data groups as a database, and the data processing unit 12 is assigned the following processing function elements by software.

<Data storage unit>
First, data stored in the data storage unit 13 will be described.
The data storage unit 13 stores and stores data relating to the same kind of industrial machines as the industrial machines 2 and 3 installed in the factory 1 as first to third databases 13a to 13c.
Among these, in the first database 13a, when machines such as the corrugator 2 and the box making machine 3 are stopped, specific machine symptoms at the time of stop (machine stop) (this is referred to as “machine symptoms”). Also, the first data is stored that associates the cause of the machine symptom with the event that causes the machine symptom (this is referred to as the “occurrence cause event”).

  As the machine stop factor (machine symptom), in the case of the corrugator 2 or the box making machine 3, symptoms such as “paper jam”, “out of paper”, “paper splicing error” and the like are raised. In addition, the events that cause the symptoms such as “paper jam”, “paper out”, and “paper splicing error” (occurrence cause events) include “cutting failure”, “paper meandering”, “order” “Change (paper exchange) mistake”. There is a certain correlation between these machine stop factors (machine symptom) and the event that caused it (occurrence event). By collecting past data on the same type of industrial machine, This correspondence can be made into a database. Thereby, the first data can be created.

In the second database 13b, there is second data in which machine trouble items obtained by checking machines such as the corrugator 2 and the box making machine 3 and the occurrence cause events assumed from the machine trouble matters are associated with each other. It is remembered.
“Machine troubles” are items such as “knife wear”, “knife receiving wear”, “warming roll stop”, “corrugated roll wear”, “meander control device failure” in the case of corrugator 2 or box making machine 3. Is raised. These “machine malfunction items” induce occurrence-causing events such as “cutting failure”, “paper meandering”, and “order change (paper replacement) error” according to the contents of the malfunction items. And, there is a certain correlation between these "machine malfunction items" and the events induced by them (occurrence events), and this correspondence can be obtained by collecting past data on the same type of industrial machinery. Can be made into a database. Thereby, the second data can be created.

In the third database 13c, the countermeasures for the occurrence cause events such as “cutting failure”, “paper meandering”, and “order change (paper replacement) error” are associated with the specific matters of the occurrence cause events. Three data are stored.
In other words, with respect to the cause-causing events such as “cutting failure”, “paper meandering”, and “order change (paper replacement) error” described above, measures to avoid this for each specific matter of the cause-causing event ( ) Exists. For example, the countermeasures include “knife polishing”, “knife replacement”, “cutting device overhaul”, “cutting device replacement”, “knife receiver replacement”, for example, “cutting failure”. There are measures such as. Further, regarding the cause of occurrence such as “paper meandering”, there are measures such as “control device overhaul” and “control device replacement”.
Measures against specific matters of such occurrence-causing events can be made into a database as a correspondence relationship by collecting past data on industrial machines of the same type. Thereby, the third data can be created.
Further, the data storage unit 13 is provided with a fourth database 13d that stores fourth data in which the above-described countermeasure is associated with the actual price required for this countermeasure.

  For example, for the measures such as “knife replacement”, “replacement of cutting device”, “replacement of knife receiver”, “replacement of control device”, the cost (price) required for each can be obtained from the actual results. It is possible to create a database of correspondence between countermeasures and the price required for them. Thereby, 4th data can be created.

<Data processing section>
The data processing unit 12 includes a functional element (first estimation means) 12a for estimating an occurrence cause event corresponding to a machine symptom associated with a machine stop and a machine inspection item input to the data input unit 11 from a machine inspection result. The estimated results of the functional elements (inspection result extraction means) 12m to be extracted, the functional elements (second estimation means) 12b for estimating the occurrence cause event assumed from the extracted machine malfunction items, and the estimation results of both the estimation means 12a and 12b And a functional element (machine stop cause specifying means) 12c for specifying the cause-of-occurrence event that caused the machine stop.

In the first estimation means 12a, when the information on the machine symptom related to the machine stop is input to the information input unit 11, the machine symptom of the first data stored in the first database 13a of the data storage unit 13, the occurrence cause event, Is used to estimate the cause-cause event that caused the machine symptom information related to the input machine stoppage.
The inspection result extraction means 12m extracts the machine defect matter from the information on the machine inspection result input to the information input unit 11, if it is checked.

  In the second estimation means 12b, the machine trouble matter extracted by the inspection result extraction means 12m, the machine trouble matter of the second data stored in the second database 13b of the data storage unit 13, and the occurrence cause event assumed from now on The cause-of-occurrence event that is assumed from the machine troubles is estimated using the corresponding relationship.

  The machine stop cause identifying means 12c is based on the difference between the occurrence cause event estimated by the first estimation means 12a and the occurrence cause event estimated by the second estimation means 12b, and the cause that caused the machine stop. Identify the event. That is, if the occurrence cause event estimated by both the estimation means 12a and 12b is the same, the same occurrence cause event is specified as the occurrence cause event that caused the machine to stop. In many cases, there are a plurality of occurrence-causing events estimated by the estimating means 12a, 12b, and therefore, a common one among the plurality of occurrence-causing events is specified.

If there is no common occurrence cause event, a specific (single or plural) occurrence cause event can be selected through the input unit 11.
The data processing unit 12 further uses the third data stored in the third database 13c of the data storage unit 13 when the occurrence cause event is specified by the machine stop cause specifying unit 12c or by the input through the input unit 11. A functional element (measure selection means) 12d is provided for selecting a measure for the specified cause-cause event by using a correspondence relationship between a certain cause-cause event and a measure against it.

Further, when the machine operation data and the machine specification data are input to the information input unit 11, the data processing unit 12 further determines the actual production amount and the ideal production amount of the machine from the machine operation data and the machine specification data. Is provided with a functional element (production amount calculating means) 12e.
Note that the machine operation data is history information such as the operation speed and operation time of the machine, and the machine specification data includes the product type manufactured by the machine, and from these machine operation data and machine specification data, The actual production volume can be calculated for each type of product produced. The machine specification data includes the standard operation speed for each product type manufactured by the machine and the time schedule related to operation. From these, the ideal production volume, that is, the production volume when the machine is used most time-effectively. The (estimated maximum possible production amount) can be calculated.

  Further, the data processing unit 12 further receives the actual production amount and the ideal production amount calculated by the production amount calculation unit 12e when the machine symptom information and the machine stop time information concerning the machine stop are input to the information input unit 11. And a functional element (production loss amount calculation means) 12f for calculating a machine production loss amount for each machine symptom from the inputted machine symptom information and machine stop time information.

For example, as shown in FIG. 4A, the production loss amount can be calculated together with the loss price corresponding to the machine stop factor (machine symptom).
Furthermore, when the information selection unit 11 inputs countermeasure selection information from the recommended countermeasures displayed as a list on the display unit 14, the data processing unit 12 stores the fourth data stored in the fourth database 13 d of the data storage unit 13. A functional element (price calculation means) 12g for calculating the actual price corresponding to the selected and inputted countermeasure based on the correspondence relationship between the countermeasure and the price required as data is provided. As shown in FIG. 4 (b), it can be shown as a price (estimated price) estimated corresponding to each measure.

The data processing unit 12 also calculates the investment effect from the production loss amount calculated by the production loss amount calculation unit 12f and the actual price corresponding to the selected measure calculated by the price calculation unit 12g. (Investment effect calculation means) 12h.
With this investment effect, for example, as shown in FIG. 4C, the production loss amount per unit time (here 1 year) is divided by the countermeasure cost (investment) per unit time (here 1 year). Can be a value. That is, the cost ratio of how much investment can reduce the production loss per unit time can be given as an index of the investment effect.
Further, the data processing unit 12 includes a functional element (report report creating unit) 12i that automatically creates a diagnostic report regarding a preset item from each processing result. This diagnostic report will be described later.

<Display section>
The display unit 14 displays information related to estimation by the first estimation means 12a (first display), information display related to estimation by the second estimation means 12b (second display), and information display related to the identified occurrence cause event ( (Third display), information display regarding the selected countermeasure (fourth display), information display regarding the production loss amount (fifth display), information display regarding the actual price (sixth display), information display regarding the investment effect (Seventh display) is appropriately displayed.

The information display (first display) related to the estimation by the first estimating means 12a is to display the machine symptom related to the machine stop and the occurrence cause event in correspondence with each other as shown in FIG. 5A, for example.
For example, as shown in FIG. 5B, the information display (second display) relating to the estimation by the estimating means 12b is the machine symptom and the machine malfunction matter related to the occurrence cause event specified by the machine stop cause specifying means 12c. And corresponding display.

For example, as shown in FIG. 5C, the information display (third display) relating to the specified cause-of-occurrence event is the machine symptom and the machine malfunction associated with the cause-of-occurrence event specified by the machine stop cause specifying means 12c. Items are displayed in correspondence with each other.
For example, as shown in FIG. 5D, the countermeasure information display (fourth display) displays the countermeasure selected by the countermeasure selecting means 12d in correspondence with the machine symptom, the cause-causing event, and the machine malfunction item. Is.

The information display (fifth display) regarding the production loss amount corresponds to the machine symptom or the second event, for example, the production loss amount calculated by the production loss amount calculation means 12f as shown in FIG. To display.
For example, as shown in FIG. 5 (e), the information display regarding the actual price (sixth display) displays the correspondingly selected measure and the actual price required for the measure calculated by the price calculating means 12g. It is. If the ratio of countermeasures implemented in the past is calculated and this ratio is also displayed in correspondence, it can be used as a judgment material for selecting the countermeasure.

  For example, the information display (seventh display) regarding the investment effect is the same as the information display (seventh display) regarding the investment effect calculated by the investment effect calculating means 12h as shown in FIG. A priority is given to the investment effect together with the symptom or the second event, and the corresponding display is performed.

<Action (Operation)>
Since the industrial machine diagnostic apparatus according to the present embodiment is configured as described above, the machine is diagnosed by a computer that operates according to software (computer program), for example, as shown in FIG. Can do.

That is, when the machine operation data and the machine specification data are input to the information input unit 11 (step a2), the production amount calculation means 12e calculates the actual production amount of the machine and the machine operation data and the machine specification data from the machine operation data and the machine specification data. The ideal production amount is calculated (step b2).
After the determination in step b4, the machine operation data fluctuates while the machine is operating. Therefore, it is difficult to perform an analysis process for diagnosis at this stage, and the analysis process is not performed (step b6). The following analysis process is performed when the machine is stopped.

First, when machine stop time information is input to the information input unit 11 in association with information on a factor (machine symptom) related to machine stop (step a4), the production loss amount calculation means 12f is caused by the production amount calculation means 12e. From the calculated actual production amount and ideal production amount, and the input machine symptom information and machine stop time information, the machine production loss amount is calculated for each machine symptom.
And the 1st estimation means 12a analyzes a stop factor. That is, using the correspondence relationship between the machine symptom of the first data stored in the first database 13a of the data storage unit 13 and the occurrence cause event, this information is obtained from the information of the machine symptom (stop factor) related to the input machine stop. The occurrence cause event that is the cause is estimated (step b10). A list of presumed causes (occurrence events) of the machine stop is generated from the estimation result (step b12) and displayed on the display unit 14 as shown in FIG. 5A (step c2).

On the other hand, when a machine inspection result is input to the information input unit 11, the inspection result extraction unit 12m extracts a machine defect item from the input machine inspection result and generates a list of machine defect items (step b13). This is displayed on the display unit 14 as shown in FIG. 5B (step c3).
On the other hand, when a machine malfunction item based on the machine inspection result is extracted by the inspection result extraction unit 12m (step b13), the second estimation unit 12b stores the second data stored in the second database 13b of the data storage unit 13. A possible cause event is estimated from the extracted machine defect item by using the correspondence relationship between the machine defect item and the expected cause event (step b14). From this estimation result, a list of expected machine stoppage events (cause occurrence events) due to machine failure is generated (step b16) and displayed on the display unit 14 as shown in FIG. 5C (step c4).

  Then, the machine stop cause identifying means 12c causes the machine stop presumed cause (occurrence cause event) estimated by the first estimating means 12a, and the machine stop cause event (occurrence cause event) estimated by the second estimation means 12b. Are identified (step b18), and the cause-causing event that caused the machine to stop is identified (step b20). That is, if the occurrence cause event estimated by both the estimation means 12a and 12b is the same, the same occurrence cause event is specified as the occurrence cause event that caused the machine to stop. In many cases, there are a plurality of occurrence-causing events estimated by the estimating means 12a, 12b, and therefore, a common one among the plurality of occurrence-causing events is specified.

If there is a matching occurrence cause event, a list of matching occurrence cause events (specified occurrence cause events) is generated (step b22) and displayed on the display unit 14 as shown in FIG. Step c6).
On the other hand, if there is no coincident occurrence cause event, that fact is displayed on the display unit 14, and selection information of a specific (single or plural) occurrence cause event (machine stop cause) is input through the input unit 11. Wait for At this time, a list of occurrence cause events (machine stop causes) is displayed on the display unit 14 and selected from the list. When selection information of an occurrence cause event (machine stop cause) is input (step a8), this is specified as an occurrence cause event causing the machine stop.

  When an occurrence cause event (cause of machine stop) is specified by the machine stop cause specifying unit 12c or input through the input unit 11, the measure selecting unit 12d stores the third event stored in the third database 13c of the data storage unit 13. A countermeasure against the identified occurrence cause event or the like is selected by comparing with the correspondence relationship between the occurrence cause event and the countermeasure against the three data (step b24). Then, a list in which the selected countermeasure is associated with the identified occurrence cause event (cause) and the corresponding machine malfunction item is generated (step b26), and as shown in FIG. 14 (step c8).

  Thus, when the list is displayed on the display unit 14 (step c8), countermeasure selection information is input from the displayed recommended countermeasures by the information input unit 11 (step a10). The price calculation unit 12g calculates the actual price corresponding to the input countermeasure based on the correspondence (fourth data) between the countermeasure stored in the fourth database 13d of the data storage unit 13 and the price required for the countermeasure (fourth data) ( Step b28). Then, a countermeasure list in which the recommended countermeasures are associated with the actual prices is generated (step b30) and displayed on the display unit 14 as shown in FIG. 5 (f) (step c10).

  Further, the investment effect calculation means 12h calculates the investment effect which is the ratio of the production loss amount and the investment amount from the production loss amount and the actual price corresponding to the selected measure (step b32), and calculates the investment effect. As information on the investment effect calculated by the means 12h, a list [refer to FIG. 4C] in which the investment effect is prioritized together with the machine symptom or the second event is generated (step b34), and is displayed on the display unit 14. Display (step c10).

Further, the report creation means 12i automatically creates a diagnosis report regarding a preset item from each processing result (step b36).
In addition, as a diagnostic report, it is assumed that each collected information is organized by a preset method, and is compiled into a list or graph.

<Effect>
Therefore, according to this device, the cause event that caused the machine symptom at the time of machine stop (machine stop factor) is estimated, and on the other hand, from the machine trouble matter obtained by machine inspection, the machine trouble matter The cause-of-cause event that caused the machine stoppage is estimated from the difference between these estimated cause-of-occurrence events, and the cause-cause event that caused the machine stoppage is identified. Can be estimated more accurately, and the diagnosis of the productivity of the industrial machine can be performed easily and appropriately.

In addition, an appropriate countermeasure can be guided by selecting a countermeasure for the identified occurrence cause event using data stored in advance.
Further, the display unit 14 displays a general correspondence between the machine symptom and the occurrence cause event, a general correspondence between the machine malfunction item and the occurrence cause event, and the identified occurrence cause event and the machine symptom related thereto. By displaying the correspondence relationship between the machine failure item and the selected countermeasure and the machine symptom, event causing the failure, and the machine failure matter, various information related to machine stoppage can be easily displayed. It can be visually recognized.

In addition, if a selection operation is performed from among the measures displayed in the list on the display unit 14 through the input unit 11, the actual price corresponding to the selected measure is calculated and displayed based on the stored data. It is possible to consider the implementation of measures while considering the aspect.
Further, since the investment effect is calculated and displayed from the production loss amount due to the machine stop and the actual price corresponding to the selected and inputted countermeasure, it is possible to examine the implementation of the countermeasure while considering the investment effect. In this display, priority is given to the investment effect, so it can be used as a reference for considering the implementation of countermeasures, and the implementation of countermeasures can be examined more actively.
Furthermore, by automatically creating a diagnostic report on a preset item from each processing result, implementation of countermeasures can be considered based on the diagnostic report.

[Second Embodiment]
Next, a second embodiment of the present invention will be described with reference to FIGS. The present embodiment relates to diagnosis (analysis) of product quality by an industrial machine.
In this embodiment, as shown in FIG. 7, the diagnosis for an industrial machine such as a corrugator 2 or a box making machine 3 installed in a corrugated cardboard factory 1 for producing a corrugated cardboard product will be described. It is not limited to.

<Overview>
First, the situation in which the apparatus and method according to the embodiment are applied will be described. As shown in FIG. 7, a corrugated board factory 1 for producing corrugated board products is equipped with industrial machines such as a corrugator 2 and a box making machine 3. Yes. For such machinery, the person in charge on the factory side routinely maintains and manages it, but on the other hand, the machine manufacturer who delivered the corrugator 2, box making machine 3, etc. The service is implemented.

That is, the service person M1 collects quality data of products related to the corrugator 2 and the box making machine 3 installed from the corrugated cardboard factory (customer) 1 side, and based on this collects and analyzes the state of the machinery. .
On the other hand, for maintenance, a maintenance manager M2 on the machine maker's side goes to the corrugated board factory 1 to perform maintenance inspection and maintenance of the corrugator 2 and the box making machine 3, etc. separately from the service person. This maintenance inspection and maintenance may be performed periodically, or may be performed at the request of the factory due to some trouble in the machine. The maintenance manager M2 can collect the status of each part of the machinery through maintenance inspection and maintenance.

  In the present embodiment, the serviceman M1 measures the quality of the product, and if there is a quality defect (hereinafter also referred to as a quality error), the machine malfunction causing the quality error is estimated and the machine malfunction is also detected from the maintenance management information. It is intended to collect machine information and to estimate with high accuracy the machine fault that caused the quality error from both sides. In addition, measures to eliminate quality errors and costs for such measures can be provided promptly. It is also intended to enable more efficient operation of the machine by automatically creating a diagnostic report on the state and quality of the machine obtained by collecting from various aspects.

<Overall configuration>
As shown in FIG. 6, the industrial machine diagnostic apparatus according to the present embodiment includes an information input unit (for example, a keyboard and a mouse) 11 and a data processing unit (CPU, memory, etc.) to which the information input unit 11 is connected. Information processing unit) 12, a data storage unit (large capacity memory) 13 connected to the data processing unit 12, and a processing result display unit (display unit, monitor display) 14 connected to the data processing unit 12. The computer 10 is configured.
The data storage unit 13 stores the following data groups as a database, and the data processing unit 12 is assigned the following processing function elements by software.

<Data storage unit>
First, data stored in the data storage unit 13 will be described.
In the data storage unit 13, fifth data that associates the quality items of the products produced by the industrial machines 2 and 3 installed in the factory 1 with the reference values related to the quality items is stored in the fifth database 13 e. The sixth data in which the quality error is associated with the machine malfunction item causing the error is stored in the sixth database 13f.

  In the data storage unit 13, the seventh data corresponding to the machine trouble item and the countermeasure against the machine trouble matter is stored in the seventh database 13 g and the countermeasure selected by the quality countermeasure selecting means 12 p described later and the countermeasure. The eighth data corresponding to the actual price (estimated price) required for each is stored in the eighth database 13h.

The quality items related to product quality errors include, for example, “sheet thickness uniformity”, “sheet cut surface condition”, “sheet warp condition”, etc., and each quality item has a preset reference value. If it exceeds the upper limit, for example, as shown in FIG. 9B, symptoms such as “non-uniform sheet thickness”, “bad sheet cut surface”, and “large sheet warp” are determined as quality errors related to these.
As described above, the machine trouble items include “pressure roll wear”, “knife wear”, “knife receiving wear”, “humidification roll stop” and the like as shown in FIG. 9B, for example.

As countermeasures against machine troubles, there are countermeasures such as “pressure roll replacement”, “knife polishing”, “knife replacement”, “knife receiving replacement”, “humidification roll replacement” and the like.
As the eighth data, for example, there is data as shown in FIG. 9A, and when linked with a quality error and a machine malfunction item, the data becomes as shown in FIG. 9A, for example.

<Data processing section>
The data processing unit 12 determines, for each quality item, whether the quality of the product satisfies the quality standard, a function element (determination unit) 12j, and if the determination unit 12j determines that the quality error is a cause of the quality error A functional element (third estimation means) 12k for estimating a machine malfunction matter, a functional element (inspection result extraction means) 12m for extracting a machine malfunction matter from a machine inspection result, and a machine malfunction matter causing a quality error And a functional element (machine fault identification means) 12n to be identified.

Based on the quality measurement result of the product input to the information input unit 11 and the fifth data stored in the data storage unit 13, the determination unit 12j determines whether the product quality satisfies the quality standard. Judge every time.
The third estimating means 12k, when the judging means 12j judges that the quality of the product does not satisfy the quality standard and is a quality error, the quality item regarded as the quality error and the data stored in the data storage unit 13. Based on the sixth data, a machine defect matter that causes a quality error is estimated.

The inspection result extraction unit 12m extracts machine defect items from the machine inspection result input to the information input unit 11. If there is a problem with the machine, extract it from the machine check result information.
The machine failure identification means 12n determines the previous machine failure matter that caused the quality error from the difference between the machine failure matter estimated by the third estimation means 12k and the machine failure matter extracted by the inspection result extraction means 12m. Identify. In other words, if the machine failure matter estimated by the third estimation means 12k and the machine failure matter extracted by the inspection result extraction means 12m are the same, this same failure matter is a machine failure matter causing a quality error. Is specified. In many cases, there are a plurality of machine trouble items estimated by the third estimating means 12k and a machine trouble matter extracted by the inspection result extracting means 12m. Therefore, a common matter among the plurality of machine trouble matters is specified. Will be.

The data processing unit 12 further has a function of selecting a countermeasure for the identified machine malfunction item based on the machine malfunction item identified by the machine malfunction identification unit 12n and the seventh data stored in the data storage unit 13. Selection input based on the element (quality countermeasure selection means) 12p, countermeasure selection information selected and input by the information input unit 11 from the countermeasures displayed in the list, and the eighth data stored in the data storage unit 13 And a functional element (price calculation means) 12q for calculating the actual price corresponding to the taken countermeasures.
Furthermore, the data processing unit 12 further includes a functional element (report creation means) 12r that automatically creates a quality diagnosis report relating to a preset item from each processing result relating to quality. This diagnostic report will be described later.

<Display section>
The display unit 14 displays information related to quality errors (eighth display) by the judging means 12j, information display related to estimation (third display) by the third estimating means 12k, and information display related to extraction by the inspection result extracting means 12m ( (Tenth display), information display regarding specific items by the machine defect specifying means 12n (eleventh display), information display regarding selection by the quality countermeasure selecting means 12p (twelfth display), information display regarding prices by the price calculating means 12q (13th display) is appropriately displayed.

The information display regarding the quality error (eighth display) by the judging means 12j is such that if the judgment means 12j judges that the quality of the product does not satisfy the quality standard and is a quality error, the quality item that has been regarded as the quality error is displayed. For example, it is displayed as shown in FIG.
The information display (the ninth display) relating to the estimation by the third estimating means 12k corresponds to a quality item in which the machine fault matter estimated by the third estimating means 12k is regarded as a quality error, for example, FIG. ) Is displayed.

The information display (tenth display) related to the extraction by the inspection result extraction unit 12m displays machine trouble items extracted by the inspection result extraction unit as shown in FIG. 10C, for example.
The information display (the eleventh display) regarding the specified items by the machine defect specifying unit 12n is shown in FIG. 10 (d), for example, the quality items of the quality error and the machine defect items specified by the machine defect specifying unit 12n. It is displayed correspondingly. Also in this case, if the ratio of countermeasures implemented in the past is calculated and this ratio is also displayed in correspondence, it can be used as a judgment material for selecting the countermeasure.

The information display (the twelfth display) regarding the selection by the quality countermeasure selection means 12p is the information selected by the quality countermeasure selection means 12p, the quality item of the quality error, and the specified machine malfunction item, for example, FIG. As shown in FIG.
The information display (13th display) regarding the price by the price calculation means 12q is displayed as shown in FIG. 10F, for example, corresponding to the measure selected and inputted by the actual price calculated by the price calculation means 12q. Is.

<Action (Operation)>
Since the industrial machine diagnosis apparatus according to the present embodiment is configured as described above, for example, as shown in FIG. 8, it is possible to perform machine diagnosis.
That is, when the data of the product quality measurement result is input to the information input unit 11 (step a12), the determination unit 12j collates the fifth data that associates the product quality item with the reference value related to the quality item. In step b42, it is determined for each quality item whether the quality of the product satisfies the quality standard (step b44).
If it is determined in step b44 that the product quality satisfies the quality standard, the analysis process is not performed (step b46). If the product quality does not satisfy the quality standard, the following analysis process is performed. .

First, a list of items whose product quality does not satisfy the quality standard is generated for displaying the matching result (step b48), and this is displayed on the display unit 14 as shown in FIG. Display (step c12).
Next, the third estimator 12k analyzes the cause of the quality error, that is, the sixth data in the data storage unit 13 in which the quality item that is regarded as the quality error and the machine trouble matter that causes the quality error are associated with each other. By collating, a machine defect matter that causes a quality error is estimated (step b50).

In order to display the analysis result of the quality error cause, a list of quality error estimated causes (machine defect items) is generated (step b52), and this is displayed on the display unit 14 as shown in FIG. (Step c14).
When a machine inspection result is input to the information input unit 11, the inspection result extraction unit 12m extracts a machine defect item from the input machine inspection result, generates a list of machine defect items (step b54), and Is displayed on the display unit 14 as shown in FIG. 10C (step c16).

Then, the machine fault identification means 12n collates the machine fault matter (estimated cause) estimated by the third estimation means 12k with the machine fault matter extracted by the inspection result extraction means 12m (step b56), It is determined whether there is a match with the machine fault (step b58).
If there is a match with each machine failure item, a list of matching machine failure items is generated (step b60), and this is displayed on the display unit 14 as shown in FIG. Step c18).

On the other hand, if there is no match between the machine trouble items, the fact is displayed on the display unit 14. In this case, the information input unit 11 inputs the machine trouble item causing the quality error. (Step a16). At this time, a list of causes of quality errors (cause of machine stoppage) is displayed on the display unit 14 and selected from the list.
In this way, when the machine malfunction item causing the quality error is identified, the quality countermeasure selecting unit 12p analyzes the cause / defect, that is, the seventh data (machine malfunction problem) stored in the data storage unit 13. The data corresponding to the countermeasure for the machine) is compared with the specified machine malfunction item, and the countermeasure for the machine malfunction item is selected (step b62). In order to display this collation result, a list of countermeasures for the cause / fault is generated (step b64), and this is displayed on the display unit 14 as shown in FIG. 10 (e) (step c20).

  With reference to this display (step c20), when measure selection information is input from the displayed recommended measures by the information input unit 11 (step a18), the price calculation means 12q is stored in the data storage unit 13. The eighth data (data corresponding to the countermeasure and the actual price (estimated price) required for this countermeasure) is collated with the countermeasure inputted and inputted (step b66), and the actual price corresponding to the countermeasure is obtained. calculate. In order to display this countermeasure and price, a list of recommended countermeasures and estimated prices is generated (step b68), and this is displayed on the display unit 14 as shown in FIG. 10 (f) (step c22). .

Further, the report creating means 12r automatically creates a quality diagnosis report relating to a preset item from each processing result relating to quality (step b70).
In addition, as a diagnostic report, it is assumed that each collected information is organized by a preset method, and is compiled into a list or graph.

<Effect>
Therefore, according to this device, when a quality error is found from the quality measurement result of the product, the machine trouble matter that causes the quality error is estimated, and on the other hand, the machine trouble matter is extracted from the machine inspection result. In addition, since the machine fault that caused the quality error is identified from the difference between the estimated machine fault and the extracted machine fault, the machine fault that caused the quality error should be estimated more accurately. Therefore, it is possible to easily and appropriately diagnose the quality of the product produced by the machine.

Furthermore, an appropriate countermeasure can be guided by selecting a countermeasure for the specified machine malfunction item using data stored in advance.
In addition, on the display unit 14, the quality items that are regarded as quality errors, the machine malfunction items, the machine malfunction items extracted from the inspection results, the identified machine malfunction items, and the selected countermeasures are appropriately displayed. Thus, various information related to the machine stop can be easily recognized.

Furthermore, by calculating the actual price corresponding to the countermeasure selected and inputted from the countermeasures displayed in the list and displaying these correspondingly, the implementation of the countermeasure can be examined while considering the actual price.
Then, by automatically creating a diagnostic report regarding a preset item from each processing result, implementation of countermeasures can be considered based on the diagnostic report.

Also in this case, if each data stored in the data storage unit 13 is updated based on new acquired data, more appropriate estimation, determination, identification, and selection can be performed.
Furthermore, if this apparatus is configured using a mobile personal computer, for example, a person in charge from the manufacturer side of the production machine goes to the factory side where the production machine is installed, and performs the above processes, thereby improving productivity. And the machine improvement items related to quality can be explained in an easy-to-understand manner to the person in charge at the factory.

<Others>
Although the embodiments of the present invention have been described above, the apparatus, method, and computer program of the present invention are not limited to the above-described embodiments, and the above-described embodiments are within the scope of the present invention. It is also possible to carry out by changing a part of the above, or to implement only a part of the above-described embodiment or in various combinations.

For example, it can be set as the apparatus structure which combined 1st Embodiment and 2nd Embodiment, Rather this can pick up the machine improvement matter from both sides of productivity and quality, and is rational, The effect is also great.
In this case, the diagnostic report is more effective because it is approached from both aspects of productivity and quality. In this case, the report items include a list of measures for productivity (related to events such as machine stoppage and machine speed reduction), quality (measurement results of each quality item), machine maintenance, and malfunction (machine stoppage, product quality error). A comprehensive diagnostic report can be created by listing each item (current countermeasures, recommended countermeasures in the future), a check result list of each part of the machine, etc.

  Of course, the present invention can be applied to various industrial machines.

1 Factory 2, 3 Industrial Machine 10 Diagnostic Equipment (Computer)
11 Information input part (input part)
12 data processing unit 12a first estimation unit 12b second estimation unit 12c machine stop cause identification unit 12d measure selection unit 12e production amount calculation unit 12f production loss calculation unit 12g price calculation unit 12h investment effect calculation unit 12i report creation unit 12j Judgment means 12k Third estimation means 12m Inspection result extraction means 12n Machine failure identification means 12p Quality countermeasure selection means 12q Price calculation means 12r Report creation means 13 Data storage section 13a to 13g Database 14 Processing result display section (display section)

Claims (23)

An industrial machine diagnostic apparatus comprising an information input unit, a data processing unit connected to the information input unit, and a data storage unit connected to the data processing unit,
In the data storage unit, the first data in which the machine symptom when the machine is stopped with respect to the industrial machine and the generation cause event of the machine symptom are associated with each other, the machine trouble matter obtained by machine inspection with respect to the industrial machine, Second data corresponding to the occurrence cause event assumed from the machine trouble matter is stored,
The data processing unit
Based on the information on the machine symptom related to the machine stop input to the information input unit and the first data stored in the data storage unit, the generation cause event related to the machine stop is estimated. 1 estimation means;
Second estimation means for estimating the occurrence cause event assumed from the machine malfunction matter based on the machine malfunction matter input to the information input unit and the second data stored in the data storage unit When,
A machine stop that identifies the occurrence cause event that caused the machine stop from the difference between the occurrence cause event estimated by the first estimation means and the occurrence cause event estimated by the second estimation means A diagnostic device for an industrial machine, comprising a cause identifying means. Further comprising inspection result extraction means for extracting machine trouble items from the result of the machine inspection input to the information input unit,
2. The industrial machine diagnostic apparatus according to claim 1, wherein the machine malfunction matter used for estimation by the second estimation unit is extracted by the inspection result extraction unit. The data storage unit further stores third data associating the occurrence cause event with the countermeasure against the occurrence cause event with respect to the industrial machine,
The data processing unit selects a countermeasure for the identified occurrence cause event based on the occurrence cause event identified by the machine stop cause identification means and the third data stored in the data storage unit The industrial machine diagnostic apparatus according to claim 1 or 2, further comprising countermeasure selection means. A display unit connected to the data processing unit;
The display unit includes a first display for displaying the machine symptom related to the machine stop related to the estimation by the first estimation unit and the occurrence cause event, and the machine defect matter regarding the estimation by the second estimation unit. And a second display for displaying the occurrence cause event identified by the machine stop cause identifying means in correspondence with the machine symptom and the machine defect matter relating thereto. And at least one of the machine symptom related to the countermeasure selected by the countermeasure selecting means, the occurrence cause event, and the fourth display for correspondingly displaying the machine malfunction matter is performed. The industrial machine diagnostic apparatus according to claim 3. In the data processing unit,
From the machine operation data and machine specification data of the industrial machine input to the information input unit, a production amount calculating means for calculating an actual production amount and an ideal production amount of the industrial machine,
The machine symptom information and machine stop time information related to the machine stop input to the information input unit, and the actual production amount and the ideal production amount calculated by the production amount calculation unit, for each machine symptom. A production loss amount calculating means for calculating a production loss amount of the industrial machine,
5. The display according to claim 4, wherein a fifth display for displaying the production loss amount calculated by the production loss amount calculation unit in correspondence with the machine symptom or the machine malfunction matter is performed on the display unit. Industrial machine diagnostic equipment. The data storage unit further stores fourth data associating the measure selected by the measure selecting means with the actual price required for the measure,
In the fifth display by the display unit, a plurality of measures are displayed in a list,
In the data processing unit, countermeasure selection information selected and input by the information input unit from among the countermeasures listed as the fifth display, and the fourth data stored in the data storage unit And a price calculation means for calculating a performance price corresponding to the selected and inputted measure.
In the display unit, a sixth display for displaying the selected and inputted countermeasure and the actual price corresponding to the selected and inputted countermeasure calculated by the price calculating unit is performed. The industrial machine diagnostic device according to claim 5. In the data processing unit, an investment for calculating an investment effect from the production loss amount calculated by the production loss amount calculation unit and the actual price corresponding to the selected and inputted measure calculated by the price calculation unit Further comprising an effect calculation means,
7. The industry according to claim 6, wherein the display unit displays a seventh display in which the investment effect calculated by the investment effect calculating means is displayed in correspondence with the machine symptom or the second event. Machine diagnostic equipment. The industrial machine diagnosis device according to claim 7, wherein the seventh display displays the investment effect with a priority. The said data processing part is further provided with the report preparation means which produces automatically the diagnostic report regarding the matter preset from the said each processing result, The any one of Claims 1-8 characterized by the above-mentioned. Diagnostic equipment for industrial machinery as described in 1. 10. The industrial machine diagnosis apparatus according to claim 1, wherein the data processing unit executes the processing of each unit when the industrial machine is stopped. 11. The data storage unit includes fifth data in which a quality item of a product produced by the industrial machine and a reference value related to the quality item are associated with each other, a quality error of the product, and a machine malfunction matter that causes the product Sixth data corresponding to each quality item is further stored,
In the data processing unit,
Based on the quality measurement result of the product input to the information input unit and the fifth data stored in the data storage unit, it is determined for each quality item whether the quality of the product satisfies a quality standard. A determination means for determining
When the determination means determines that the quality of the product does not satisfy the quality standard and is a quality error, the quality item determined as the quality error and the sixth item stored in the data storage unit. Third estimation means for estimating a machine defect matter that causes the quality error based on the data;
Inspection result extracting means for extracting machine defect items from the machine inspection result input to the information input unit;
Machine failure identification means for identifying the machine failure matter causing the quality error from the difference between the machine failure matter estimated by the third estimation means and the machine failure matter extracted by the inspection result extraction means The industrial machine diagnostic apparatus according to claim 1, further comprising: An industrial machine diagnostic apparatus comprising an information input unit, a data processing unit connected to the information input unit, and a data storage unit connected to the data processing unit,
The data storage unit includes fifth data in which a quality item of a product produced by the industrial machine and a reference value related to the quality item are associated with each other, a quality error of the product, and a machine malfunction matter that causes the product Sixth data corresponding to each quality item is stored,
In the data processing unit,
Based on the quality measurement result of the product input to the information input unit and the fifth data stored in the data storage unit, the quality item indicates whether the quality of the product satisfies the quality standard A judgment means for judging each;
When the determination means determines that the quality of the product does not satisfy the quality standard and is a quality error, the quality item determined as the quality error and the sixth item stored in the data storage unit. Third estimation means for estimating a machine defect matter that causes the quality error based on the data;
Inspection result extracting means for extracting machine defect items from the machine inspection result input to the information input unit;
Machine failure identification means for identifying the machine failure matter causing the quality error from the difference between the machine failure matter estimated by the third estimation means and the machine failure matter extracted by the inspection result extraction means And an industrial machine diagnostic device. The data storage unit further stores seventh data in which the machine trouble items are associated with countermeasures against the machine trouble items,
The data processing unit takes measures against the identified machine malfunction matter based on the machine malfunction matter identified by the machine malfunction identification means and the seventh data stored in the data storage unit. 13. The industrial machine diagnostic apparatus according to claim 11 or 12, further comprising a quality measure selecting means for selecting. A display unit connected to the data processing unit;
The display unit includes an eighth display for displaying the quality item determined as the quality error when the determination unit determines that the quality of the product does not satisfy the quality standard and is a quality error. A ninth display for displaying the machine malfunction matter estimated by the third estimation means in correspondence with the quality item related to the quality error, and a machine malfunction matter extracted by the inspection result extraction means A measure selected by the quality measure selecting means is an eleventh display for indicating the correspondence between the quality item of the quality error and the machine failure item specified by the machine failure specifying means. And a twelfth display for correspondingly displaying the quality item of the quality error and the identified machine malfunction item are performed. DOO characterized, diagnostic apparatus for industrial machine according to claim 13, wherein. The data storage unit further stores eighth data that associates the measure selected by the quality measure selecting means with the actual price required for the measure,
In the twelfth display by the display unit, a plurality of measures are displayed in a list,
The data processing unit includes countermeasure selection information selected and input by the information input unit from among the countermeasures listed as the twelfth display, and the eighth data stored in the data storage unit. And a price calculation means for calculating a performance price corresponding to the selected and inputted measure.
The display unit is characterized in that a thirteenth display for displaying the selected countermeasure, the actual price calculated by the price calculation means and the selected countermeasure is displayed. Item 14. The industrial machine diagnostic device according to Item 14. The said data processing part is further equipped with the report preparation means which automatically produces the diagnostic report regarding the preset matter from each processing result regarding the said quality, The any one of Claims 11-15 characterized by the above-mentioned. 2. The industrial machine diagnostic apparatus according to item 1. The industrial machine diagnostic apparatus according to any one of claims 1 to 16, wherein each of the data stored in the data storage unit is updated based on new acquired data. The industrial machine diagnostic apparatus according to any one of claims 1 to 17, wherein the apparatus is configured using a mobile personal computer. An industrial machine diagnostic method,
First, the first data in which the machine symptom causing the machine stop that occurred in the past with respect to the industrial machine and the occurrence cause event that caused the machine symptom are associated with each other, and the machine inspection with respect to the industrial machine Preparing second data in which the obtained machine malfunction matter and the occurrence cause event assumed from the machine malfunction matter are associated with each other;
A first step of estimating the occurrence cause event related to the machine stop based on the information of the machine symptom related to the machine stop and the first data;
A second step of estimating the occurrence cause event assumed from the machine malfunction matter based on the machine malfunction matter according to the machine inspection result and the second data;
A third step of identifying the occurrence cause event that caused the machine stop from the difference between the occurrence cause event estimated from the information on the machine symptom and the occurrence cause event assumed from the machine malfunction matter; A method for diagnosing an industrial machine, comprising: In advance, fifth data in which quality items of products produced by the industrial machine are associated with reference values related to the quality items, quality errors of the product that have occurred in the past, and machine malfunction items that cause the product Sixth data corresponding to each quality item is further prepared,
A fourth step of determining, for each quality item, whether the quality of the product satisfies the quality standard based on the quality measurement result of the product and the fifth data;
If it is determined in the fourth step that the quality of the product does not satisfy the quality standard and is a quality error, based on the quality item determined as the quality error and the sixth data, A fifth step of estimating machine faults causing quality errors;
A sixth step of extracting machine faults from the machine inspection results;
A seventh step of identifying the machine fault matter causing the quality error from the difference between the machine fault matter estimated in the fifth step and the machine fault matter extracted in the sixth step; The industrial machine diagnosis method according to claim 19, further comprising: An industrial machine diagnostic method,
In advance, fifth data in which quality items of products produced by the industrial machine are associated with reference values related to the quality items, quality errors of the product that have occurred in the past, and machine malfunction items that cause the product 6th data corresponding to each quality item is prepared,
A fourth step of determining, for each quality item, whether the quality of the product satisfies the quality standard based on the quality measurement result of the product and the fifth data;
If it is determined in the fourth step that the quality of the product does not satisfy the quality standard and is a quality error, based on the quality item determined as the quality error and the sixth data, A fifth step of estimating machine faults causing quality errors;
A sixth step of extracting machine faults from the machine inspection results;
And a seventh step of identifying the machine fault matter causing the quality error from the difference between the machine fault matter estimated in the fifth step and the machine fault matter extracted in the sixth step. A method for diagnosing industrial machinery.   An industrial machine diagnostic program, wherein each step of the industrial machine diagnostic method according to any one of claims 19 to 21 is programmed to be controllable by a computer.   23. A recording medium in which the industrial machine diagnosis program according to claim 22 is recorded in a computer-readable format.

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