Production management system, production management method, and program

Abstract

To provide a technology that makes a prioritized improvement for a production line further clearly recognizable.SOLUTION: A production managing system (1) that relates to a production line (10) where production processes and inspection processes are executed includes: an actual achievement value calculating unit (110a) that calculates a production actual achievement value which is the actual achievement value of a barometer relating to the productivity of a product or the quality thereof in the production line (10); and an ability value calculating unit (110a) that calculates a production ability value which is the ability value of a barometer relating to the productivity of the product or the quality thereof in the production line on the basis of the actual achievement value. In such a production managing system (1), the production ability value is the barometer relating to the productivity of the product or the quality thereof calculated by subtracting, from data on the barometer relating to the productivity of the product or the quality thereof in the production line (10), the data on the barometer corresponding to the statistical outlier in the distribution of the production actual achievement values and / or the data on the barometer affected by a predetermined condition change in the production line.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a production management system, a production management method, and a program for managing production on a product production line. [Background technology]

[0002] In product production lines, product inspection equipment is placed at intermediate and final processes to detect defects and sort out defective products. For example, a production line for component-mounted boards typically includes a device (printing device) that prints solder paste on printed wiring boards, a device (mounting device) that mounts components on the board with the solder paste printed on it, and a device (reflow device) that heats the board after component mounting to solder the components to the board. Then, inspection equipment placed after each production device inspects whether the work at each device is being performed correctly as planned.

[0003] In addition, the above production line operates a production management system that collects information from each manufacturing device and inspection device and comprehensively manages defect rates, production volume, etc., contributing to improving the productivity of the entire production line.

[0004] In the above-described production management systems, a function for aggregating data related to the production of products over a certain period and outputting it as a report is sometimes required (see, for example, Patent Documents 1 and 2). Conventionally, this reporting function has provided aggregate reports by line, manufacturing equipment, product, or KPI. However, many of these reports simply compare ideal values ​​calculated theoretically based on a business plan with actual values ​​that include the results of various problems. Because the actual performance of the production line is unclear, it is not possible to quickly grasp the location and scale of problems that should be resolved as a priority. Furthermore, the validity of target values ​​and losses due to discrepancies between actual performance and performance are unclear, making it difficult to implement efficient measures to improve the productivity of the production line. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2003-187069 [Patent Document 2] Japanese Patent Application Laid-Open No. 2003-122420 Summary of the Invention [Problem to be solved by the invention]

[0006] The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a technique that enables priority improvements in a production line to be more clearly recognized. [Means for solving the problem]

[0007] In order to achieve the above object, the present disclosure employs the following configuration: A production management system for a production line having one or more manufacturing devices and inspection devices, in which a manufacturing process and an inspection process of a product are carried out by the manufacturing devices and the inspection devices, a performance value calculation unit that calculates a production performance value that is a performance value of an index related to the productivity or quality of the product on the production line; an actual production value calculation unit that calculates an actual production value, which is an actual value of an index related to the productivity or quality of the product on the production line, based on the actual performance value; Equipped with The production capability value is an index relating to the productivity or quality of the product on the production line. The index is characterized by being an index relating to the productivity or quality of the product, calculated by excluding from the data the data of the index that corresponds to a statistical outlier in the distribution of the actual production values ​​and / or the data of the index that has been affected by a predetermined change in conditions on the production line.

[0008] According to this, a production result value is a result value of an index related to the productivity or quality of the product on the production line; It is possible to obtain a production capability value, which is an index related to the productivity or quality of a product, calculated from data on an index related to the productivity or quality of a product on a production line by excluding data on an index that corresponds to a statistical outlier in the distribution of actual production values ​​and / or data on an index that has been affected by a specified change in conditions on the production line.

[0009] As a result, by comparing actual production values ​​with actual production capabilities, it is possible to more easily identify productivity or quality indicators of a production line that have room for improvement, and by improving those indicators, productivity or quality can be improved. In this disclosure, a specified change in a production line condition may include a change equivalent to the so-called 4M changes. In addition, in this disclosure, by excluding data that has become a statistical outlier in the actual production value for some reason or data related to a sudden change in conditions in the process, it is possible to obtain a more accurate actual value of the target production line. Furthermore, by eliminating or improving specified change in conditions in the production line that affected the data of indicators excluded in the calculation of the actual value, the actual value can be brought closer to the actual value.

[0010] In the present disclosure, the predetermined condition change includes a planned condition change that is planned in advance for the production line and an accidental condition change that occurs accidentally on the production line, the actual production value calculation unit calculates the actual production value by excluding, from data on an index related to the productivity or quality of the product on the production line, data on the index that corresponds to a statistical outlier in the distribution of the actual production values ​​and that has been affected by a planned change in conditions on the production line; The capability value calculation unit may calculate the production capability value by excluding, from the data of the index related to the productivity or quality of the product used in calculating the production performance value, data of the index that corresponds to a statistical outlier in the distribution of the production performance values ​​and that is affected by an accidental change in conditions on the production line. The production performance value can be calculated by excluding the effects of planned changes in conditions that are scheduled in advance, and the production capability value can be calculated by excluding the effects of accidental changes in conditions. This makes it possible to calculate the production performance value and the production capability value in a form that facilitates factor analysis.

[0011] In the present disclosure, the indicators relating to the productivity or quality of the products on the production line may include at least one of the production volume of the products per given time, the manufacturing takt time of the products, and the error rate of the products. By using such direct indicators, it becomes possible to more clearly grasp the priority measures for increasing the production volume.

[0012] In addition, the present disclosure may further include a result reporting unit that creates a result report that allows a comparison between the actual production value and the production capacity value for a predetermined period of time, thereby making it possible to more clearly indicate prioritized measures for increasing production volume to managers and other decision-makers regarding the production line.

[0013] In addition, the present disclosure further includes a result reporting unit that creates a result report that allows comparison between the actual production value and the production capacity value for a predetermined period, The result reporting unit may report the details of the accidental condition change related to the data of the index that was excluded when the production capability value calculation unit calculated the production capability value. This makes it possible to clarify the cause of the difference between the actual production value and the production capability value, and to clearly understand measures to bring the production performance value closer to the production target value.

[0014] The present disclosure also provides a production management method for a production line having one or more manufacturing devices and inspection devices, in which a product manufacturing process and an inspection process are performed by the manufacturing devices and the inspection devices, comprising: a performance value calculation step of calculating a performance value of an index relating to the productivity or quality of the product on the production line; a production capability value calculation step of calculating a production capability value, which is a capability value of an index related to the productivity or quality of the product in the production line, based on the actual performance value; and The production management method may be characterized in that the production capability value is an index related to the productivity or quality of the product, calculated by excluding, from data on an index related to the productivity or quality of the product on the production line, data on the index that corresponds to a statistical outlier in the distribution of the actual production values ​​and / or data on the index that has been affected by a predetermined change in conditions on the production line.

[0015] The present disclosure also provides a method for manufacturing a production line, the method comprising: In the actual value calculation step, the actual production value is calculated by excluding data of the index related to the productivity or quality of the product on the production line, the data of the index corresponding to a statistical outlier in the distribution of the actual production values ​​and affected by a planned change in conditions on the production line; The production management method may be characterized in that in the step of calculating the actual production value, the production ability value is calculated by further excluding, from data on an index related to productivity or quality of the product used in calculating the actual production value, data on the index that corresponds to a statistical outlier in the distribution of the actual production values ​​and that is affected by an accidental change in conditions on the production line.

[0016] The present disclosure may also be the above-mentioned production management method, wherein the indicators relating to the productivity or quality of the products on the production line include at least one of a production volume of the products per predetermined time, a manufacturing takt time of the products, and an error rate of the products.

[0017] The present disclosure may also be the above-mentioned production management method, further comprising a result reporting step of creating a result report that allows the actual production value and the actual production capacity value to be compared. The present disclosure may also be the above-mentioned production management method, further comprising a result reporting step of creating a result report that allows the actual production value and the actual production capacity value to be compared, The production management method may be characterized in that the result reporting step includes reporting the content of the accidental condition change related to the data of the index excluded when calculating the production capability value in the capability value calculation step. This makes it possible to clarify the areas where measures should be taken to bring the actual value closer to the capability value.

[0018] The present disclosure also provides a production line having one or more manufacturing devices and inspection devices, in which a manufacturing process and an inspection process of a product are performed by the manufacturing device and the inspection device, and in which the production line is configured to: a performance value calculation step of calculating a production performance value which is a performance value of an index related to productivity or quality of the product on the production line; a production capability value calculation step of calculating a production capability value, which is a capability value of an index related to the productivity or quality of the product in the production line, based on the actual performance value; Execute The program may be characterized in that the production capability value is an index related to the productivity or quality of the product, calculated by excluding, from data on an index related to the productivity or quality of the product on the production line, data on the index that corresponds to a statistical outlier in the distribution of the actual production values ​​and / or data on the index that has been affected by a predetermined change in conditions on the production line.

[0019] The present disclosure also provides a method for manufacturing a production line, the method comprising: In the actual value calculation step, the actual production value is calculated by excluding data of the index related to the productivity or quality of the product on the production line, the data of the index corresponding to a statistical outlier in the distribution of the actual production values ​​and affected by a planned change in conditions on the production line; The above-mentioned program may be characterized in that in the actual capacity value calculation step, the production capacity value is calculated by further excluding, from data on an index related to productivity or quality of the product used in calculating the actual production value, data on the index that corresponds to a statistical outlier in the distribution of the actual production values ​​and that has been affected by an accidental change in conditions on the production line.

[0020] The present invention can be achieved by combining the above-described configurations and processes as long as no technical contradiction occurs. [Effects of the Invention]

[0021] According to the present invention, priority improvements on the production line can be more clearly identified. [Brief explanation of the drawings]

[0022] [Figure 1] 1 is a schematic configuration diagram of a production management system according to an embodiment of the present invention; [Figure 2] 10 is a diagram for explaining the difference between the best value and the actual value of the production volume in the production line according to the embodiment of the present invention. FIG. [Figure 3] 1 is a functional block diagram of a production management device according to an embodiment of the present invention; [Figure 4] 1 is a flowchart of a process in a production management system according to an embodiment of the present invention. [Figure 5] FIG. 4 is a diagram illustrating an example of a method for calculating an optimum value according to the first embodiment of the present invention. [Figure 6]FIG. 10 is a diagram illustrating a second example of a method for calculating an optimum value according to the first embodiment of the present invention. [Figure 7] FIG. 10 is a diagram showing an example of a graph included in a report according to the first embodiment of the present invention. [Figure 8] FIG. 10 is a diagram showing an example of a message to be included in a report according to the first embodiment of the present invention. [Figure 9] FIG. 10 is a diagram showing a second example of a graph included in a report according to the first embodiment of the present invention. [Figure 10] FIG. 10 is a diagram showing an example of the contents of a report provided by email according to the first embodiment of the present invention. [Figure 11] FIG. 10 is a diagram showing an example of the contents of a report downloaded by a web browser according to the first embodiment of the present invention. [Figure 12] FIG. 10 is a diagram showing an example of the contents of a report provided on a web browser according to the first embodiment of the present invention. [Figure 13] 10 is a flowchart illustrating an optimum value calculation according to a second embodiment of the present invention. [Figure 14] 10 is a flowchart for calculating a performance value and an optimum value according to a third embodiment of the present invention. [Figure 15] FIG. 10 is a diagram showing an example of data relating to the manufacture of a substrate according to Example 5 of the present invention. [Figure 16] FIG. 10 is a diagram showing another example of data relating to the manufacture of a substrate according to Example 5 of the present invention. [Figure 17] FIG. 11 is a diagram showing an example of presentation of an improvement target according to the fifth embodiment of the present invention. [Figure 18] FIG. 13 is a diagram showing another example of presentation of an improvement target according to the fifth embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0023] <Application example> 1, a production line 10 to which the present invention is applied includes a solder printing device 10a, a post-solder printing inspection device 10b, a mounter 10c, a post-mount inspection device 10d, a reflow furnace 10e, and a post-reflow inspection device 10f. Each device in the production line 10 is connected to a production management device 1a via a network such as a LAN. The production management device 1a is configured by a general-purpose computer system.

[0024] FIG. 2 shows the best value and actual value of production volume on production line 10. The arrows in the upper row indicate the case where production is carried out smoothly, and the arrows in the lower row indicate the actual case. This best value corresponds to the production capability value in this disclosure. On the other hand, the actual case in the lower row includes pre-planned 4M fluctuations such as waiting times in each manufacturing device or inspection device, accidental 4M fluctuations due to unforeseen causes such as equipment trouble, and other fluctuations in process conditions whose causes cannot be identified. The production volume in this case is the actual value. The actual value corresponds to the actual production value in this disclosure.

[0025] In order to improve the production efficiency of the production line 10, it is ultimately necessary to eliminate all of the above factors, but the first priority is to make the production line 10 perform to its full potential. In this application example, the actual state of the decrease in production volume, which should be eliminated as a priority, is clarified and a function for reporting this is provided.

[0026] FIG. 3 shows a block diagram of a production management device 1a according to this application example. The production management device 1a includes a data acquisition unit 11a that receives data from each device on the production line 10, and a control unit 11b that calculates and reports the best and actual values ​​for the production line 10. The production management device 1a also includes a memory unit 11c that stores data acquired by the data acquisition unit 11a, the best and actual values ​​calculated by the control unit 11b, and the contents of reports, and an output unit 11d that can output various data and report contents. The control unit 11b further includes functional modules, such as an actual value calculation unit 110a, a best value calculation unit 110b, and a result reporting unit 110c. The best value calculation unit 110b corresponds to the performance value calculation unit in this disclosure.

[0027] When the best value calculation unit 110b calculates the best value from the actual production volume values, for example, as shown in Fig. 5, outliers are removed from the frequency distribution of the takt time as the actual value calculated by the actual value calculation unit 110a by the Smirnoff-Grubbs test. Then, the test is performed on all data until there are no outliers, and the frequency distribution when there are no outliers is taken as the frequency distribution of the best value.

[0028] The production management device 1a outputs a report including the calculated production volume and takt time performance values ​​and actual results. FIG. 7 shows an example of a graph that may be included when creating a report. The report may include a histogram of the production cycle time (takt time) before excluding outliers as the performance values, as shown in FIG. 7(a). Alternatively, the report may include a histogram of the production cycle time (takt time) after excluding outliers as shown in FIG. 7(b).

[0029] The report may further include a message as shown in Figure 8. The top row shows the best and actual cycle time (takt time) values, the ratio between the two values, and the percentage of outliers. In addition, the difference between the best value and the ideal value is also described. Furthermore, as shown in the lower part of FIG. 8, the production number may be described. More specifically, the best value and the actual value of the production number are displayed, and the difference between the best value and the actual value, and the difference between the ideal value and the best value may also be described.

[0030] Hereinafter, embodiments of the present invention will be described with reference to the drawings. However, unless otherwise specified, the components described in each of the following examples are not intended to limit the scope of the present invention.

[0031] Example 1 A production management system 1 according to the present invention includes, for example, a production line 10 as shown in Fig. 1, and performs production management of this production line 10. The production line 10 in Fig. 1 is a surface mounting line for printed circuit boards. As shown in Fig. 1, the production line 10 according to this embodiment is provided with, in order from the upstream side, a solder printing device 10a, a post-solder printing inspection device 10b, a mounter 10c, a post-mount inspection device 10d, a reflow furnace 10e, and a post-reflow inspection device 10f.

[0032] The solder printing device 10a prints solder paste on the electrodes of a printed circuit board. The mounter 10c places a large number of electronic components to be mounted on the printed circuit board on the solder paste. The reflow furnace 10e is a heating device that solders the electronic components placed on the printed circuit board to the printed wiring on the board. Finally, the inspection devices 10b, 10d, and 10f inspect the condition of the printed circuit board at the exit of each process and automatically detect defects or potential defects.

[0033] The above-mentioned solder printing device 10a, mounter 10c, reflow furnace 10e (hereinafter collectively referred to as manufacturing devices), post-solder printing inspection device 10b, post-mount inspection device 10d, and post-reflow inspection device 10f (hereinafter collectively referred to as inspection devices) are connected to production management device 1a via a network such as a LAN. Production management device 1a is configured as a general-purpose computer system equipped with a CPU (processor), main storage device (memory), auxiliary storage device (hard disk, etc.), input devices (keyboard, mouse, controller, touch panel, etc.), output devices (display, printer, speaker, etc.), etc.

[0034] Here, using Figure 2, we will explain the difference between the best value and the actual value of production volume on production line 10. Figure 2 shows the production volume of printed circuit boards in two cases. The horizontal axis of the figure represents time, for example, a time range of one hour. Each arrow represents the time it takes to manufacture one board. The arrows in the upper row represent a case where production is carried out smoothly, while the arrows in the lower row represent actual cases where delays occur due to various problems (both known and unknown causes) or the effects of so-called 4M fluctuations.

[0035] The production volume when production is going smoothly, as shown in the upper row, can be said to be the actual value of the target production line, and this production volume is called the best value in this embodiment. In this case, as shown in Figure 2, if the average takt time T is 50 seconds, for example, it is possible to produce 3600 seconds / T = 72 pieces in one hour.

[0036] On the other hand, in the case of the lower part of Figure 2, an error and retry occurred due to component pickup failure in mounter 10c during the one hour period, which took extra time. Then, a series of errors due to component pickup failure occurred afterwards, causing the device to stop, work to resolve the error was carried out, and production resumed after the work was completed. In such a case, although it is originally possible to produce 72 pieces per hour, only 68 pieces can be produced, which is lower than the best value. The production volume will be four sheets less. In this case, the production volume is the actual value. As mentioned above, this actual value includes delays caused by the so-called 4M fluctuations.

[0037] In order to improve production efficiency in the production line 10, it is ultimately necessary to eliminate both accidental factors such as the above-mentioned troubles and planned factors such as the influence of 4M fluctuations. In this embodiment, a function is provided to clarify the actual state of declines in production volume due to factors such as various troubles and the influence of 4M fluctuations, and to report this.

[0038] FIG. 3 shows a schematic block diagram of a production management device 1a according to this embodiment. As shown in FIG. 3, the production management device 1a includes a data acquisition unit 11a that receives data from each manufacturing device and each inspection device on the production line 10, and a control unit 11b that calculates and reports the best value and actual value of the production line 10 based on the data acquired by the data acquisition unit 11a. The production management device 1a also includes a memory unit 11c that stores the data acquired by the data acquisition unit 11a, the best value, actual value, and report contents calculated by the control unit 11b, and an output unit 11d that can output various data and report contents. The control unit 11b further includes functional modules: an actual value calculation unit 110a, a best value calculation unit 110b, and a result reporting unit 110c. Each functional module is implemented, for example, by a CPU (not shown) reading and executing a program stored in the memory unit 11c.

[0039] The data acquisition unit 11a also receives inputs such as information related to inspection conditions from the user, a performance value calculation command to the performance value calculation unit 110a, a best value calculation command to the best value calculation unit 110b, and a report creation command to the result reporting unit 110c.

[0040] The actual value calculation unit 110a calculates the actual value of the production volume of the production line 10 for a specified period based on the data from each manufacturing device and each inspection device acquired by the data acquisition unit 11a. The best value calculation unit 110b calculates the best value of the production volume of the production line 10 based on the actual values ​​calculated by the actual value calculation unit 110a. The result reporting unit 110c creates a report based on the actual value of the production volume of the production line 10 calculated by the actual value calculation unit 110a and the best value of the production volume of the production line 10 calculated by the best value calculation unit 110b.

[0041] FIG. 4 shows a flowchart of the processing in the production management device 1a. When this flow is executed, first, in step S101, data on production performance and inspection results is acquired from each manufacturing device and each inspection device on the production line 10. This production performance data includes log data on the time of occurrence of errors, their contents, and the countermeasures taken. Furthermore, the inspection result data includes log data on the number of occurrences of each defect item and the time of occurrence. The acquired data is stored in the memory unit 11c. After the processing of step S101 is completed, the process proceeds to step S102. In step S102, the performance value of the production volume is calculated by the performance value calculation unit 110a and stored in the memory unit 11c. In this embodiment, the production volume per hour is calculated as the performance value, as shown in FIG. 2. The performance value may be stored hourly as the production volume per hour, or may be stored as an average value over the operating time of the production line 10, for example. After the processing of step S102 is completed, the process proceeds to step S103.

[0042] In step S103, the best value of the production quantity is calculated by the best value calculation unit 110b and stored in the storage unit 11c. When calculating the best value, a general method such as the Smirnolf-Grubbs test may be used, for example. A specific example of a method for calculating the best value is described below.

[0043] <Example 1 of best value calculation> When calculating the best value, for example, as shown in FIG. 5, For the histogram of the takt time of each product (board) related to the actual production volume, a normal distribution is assumed, and the test value - mean value / standard deviation σ is tested with a superiority level of 5%. Then, only the most outlying data is tested, and if it is determined to be an outlier, the next most outlying sample is tested using the remaining n-1 samples, and so on, until no outliers are detected. The average of the remaining takt times is the best takt time, and the value obtained by dividing one hour by the best takt time is the best value for the number of units produced per hour.

[0044] <Example 2 of calculating the best value> 6 shows a second example of calculating the best value in this embodiment. In this example, the best value for the pickup error rate when components are picked up by a pickup nozzle (not shown) of the mounter 10c is calculated. In this case, the ideal value is an error rate of 0%. The actual value is, for example, the pickup error rate (%) per hour = (number of errors / number of pickups). Then, the error rates are tallied every hour, and the error rates for each hour are used as data for testing. The average of the remaining pickup error rates (%) is then taken as the best value.

[0045] Figure 6(a) shows a graphical representation of the method for calculating the pickup error rate in this example. In Figure 6(a), the horizontal axis represents time. The horizontal length of the chronologically arranged rectangles represents the time during which the component mounting process is carried out on one board. Among them, hatched rectangles represent boards with zero pickup errors during operation. Open rectangles represent boards with pickup errors during operation. The number of x's written below the open rectangles corresponds to the number of pickup errors. Note that this figure assumes that, for example, 20 components are mounted on one board, and that a retry is performed when a pickup error occurs, so the number of pickup attempts increases accordingly.

[0046] FIG. 6(b) is a table showing the number of substrates produced (production number), total number of pick-ups, number of errors, and error rate for each time period. As shown in FIG. 6(b), in the midnight hour, six substrates were mounted, and one of the substrates experienced a pick-up error. The error rate for this time period was 0.83%. In the 1:00 hour, five substrates were mounted, and no pick-up errors occurred. The error rate for this time period was 0.00%. In the 2:00 hour, four substrates were mounted, and one of the substrates experienced two pick-up errors, and the other substrate experienced three pick-up errors, for a total of five pick-up errors. The error rate for this time period was 5.88%. The error rates thus obtained are tested, and the average of the error rates not excluded as outliers is the best error rate. Returning to the explanation of FIG. 4, once the processing of step S103 is completed, the process proceeds to step S104.

[0047] In step S104, a report is created in a format that allows the actual values ​​and the best values ​​to be compared. The report created in step S104 will be described below.

[0048] <Example of report creation> Figure 7 shows an example of a graph that is included when creating a report. The report includes a histogram, as shown in Figure 7(a), with production cycle time (takt time) on the horizontal axis and frequency on the vertical axis before excluding outliers. The data analysis results are also displayed along with the histogram. In this example, the average takt time is 80.2 seconds, the maximum is 3,445 seconds, the minimum is 43 seconds, and the number of samples is 1,075, indicating that the actual takt time is 80.2 seconds. The report also includes a histogram after excluding outliers, as shown in Figure 6(b). This graph shows that the average takt time after excluding outliers is 55.4 seconds, the maximum is 76 seconds, the minimum is 43 seconds, and the number of samples is 923, indicating that the best takt time is 55.4 seconds.

[0049] FIG. 8 shows an example of a message to be included in a report. The top row shows information about the production cycle time (takt time). The best and actual values ​​of the production cycle time (takt time), the ratio between the two values, and the percentage of outliers are listed. The difference between the best and ideal values ​​is also listed. Here, the ideal value is a target value for the production cycle time (takt time) that is set in advance for other reasons, such as a business plan, regardless of the actual value of the production line 10. This ideal value corresponds to the production target value in this disclosure. The bottom row shows information about the number of sheets to be produced. Here, the best and actual values ​​of the number of sheets to be produced are also displayed, and the difference between the best and actual values ​​is listed as the difference between the actual and actual capabilities. The difference between the ideal and best values ​​for the first number of sheets is also listed.

[0050] Figure 9 shows a bar graph plotting production time on the horizontal axis and cycle time on the vertical axis instead of a histogram. A graph like this can be included in a report. In this case, plots that correspond to outliers can be changed to a different color and made white.

[0051] Returning to the explanation of Fig. 4, when the processing of step S104 is completed, the process proceeds to step S105. In step S105, the report created in step S104 is output and provided to a predetermined reporting destination. The method of outputting (providing) the report will be described below.

[0052] <How to output a report> The following methods can be used to output a report: (1) Email In this case, the summary of the collection period, collection target, and topic can be written in the email body, and the report file can be attached to the email (Excel file, etc.). The following shows an example of the report content and attached report file.

[0053] (2) Download using a web browser In this case, reports for each creation date can be made available for download at a specific URL. This allows users to obtain the reports at any time by accessing the URL. Figure 11 shows an example of the download screen. In this example, reports in Excel files for each working day can be downloaded.

[0054] (3) Provided via web browser The report may be viewable on a specific web page using a web browser. Alternatively, the report may be embedded in a specific web page so that it can be linked to. Figure 12 shows the web browser screen.

[0055] In the above report, an example was explained in which the ideal and best values ​​for takt time and production volume, actual values ​​and the difference therebetween were recorded, but values ​​converted into monetary values ​​such as sales and profits may also be recorded.

[0056] Returning to the description of Fig. 4, when the process of step S105 ends, this routine is temporarily ended.

[0057] <Example 2> In the above-described first embodiment, an example was described in which the best value, which is the actual value on the production line, is calculated by excluding data corresponding to statistical outliers from data related to actual values ​​on the production line. In the present embodiment, an example will be described in which, instead of excluding statistical outliers, data affected by 4M fluctuations is excluded.

[0058] FIG. 13 shows a flowchart for calculating the best value in this embodiment. This flowchart explains in more detail the process corresponding to step S103 in FIG. 4. When this flow is executed, first, in step S201, data affected by 4M fluctuations in the production of the target product is searched for. That is, data on the product affected by the 4M fluctuations is searched for from the timing when the 4M fluctuations are implemented. Note that in this embodiment, no distinction is made between 4M fluctuations that are planned and those that are accidental.

[0059] Next, in step S202, for example, data affected by 4M fluctuations found in step S201 is excluded from the data used to calculate the production volume during a specified time or takt time. Then, in step S203, average values ​​of the production volume and takt time are calculated using only the data not affected by 4M fluctuations obtained in step S202. Note that, for example, the number of products affected by 4M fluctuations is subtracted from the production volume during a specified time, and the manufacturing time of products affected by 4M fluctuations is also subtracted from the specified time. Then, for example, the production volume per hour may be calculated using a proportional calculation.

[0060] In step S204, the result calculated in step S203 is stored as the best value in the storage unit 11c. When the processing of step S204 is completed, this flow is temporarily terminated. In this case, when outputting a report corresponding to step S105 in Figure 4, all 4M variations related to the data excluded in step S202 may be listed.

[0061] According to the above-described method for calculating the best value, the effects of the 4M variations can be excluded from the actual value, improving the accuracy of the best value and clarifying which of the 4M variations is affecting the performance of the process.

[0062] Example 3 In the above-described second embodiment, an example was described in which the best value, which is the actual value of the production line, is calculated by excluding data affected by 4M fluctuations from data related to actual values ​​of the production line. In this embodiment, an example is described in which, when calculating actual values ​​of the production line, data that are statistical outliers and that are affected by planned 4M fluctuations are excluded, and then, when calculating the best value of the production line, data that are statistical outliers and that are affected by accidental 4M fluctuations are excluded.

[0063] FIG. 14 shows a flowchart for calculating actual values ​​and best values ​​in this embodiment. This flowchart explains in more detail the processing corresponding to steps S102 and S103 in FIG. 4. When this flow is executed, first, in step S301, data corresponding to outliers is searched for among data on indicators related to the productivity or quality of the target product. Next, in step S302, data affected by planned 4M fluctuations that have been scheduled in advance is searched for among the data. Note that this planned 4M fluctuation corresponds to planned condition changes in this embodiment.

[0064] Then, in step S303, outliers in the data on indices related to the productivity or quality of the target product and that are affected by planned 4M fluctuations are excluded from the data used to calculate, for example, the number of products produced during a specified period of time and the takt time. Then, in step S304, the average values ​​of the number of products produced and the takt time are calculated using the data obtained in step S303 from which the outliers and the data affected by planned 4M fluctuations have been excluded. Then, in step S305, the calculated values ​​are stored in memory unit 11c as actual values.

[0065] Next, in step S306, among the data used to calculate the actual value, Data affected by accidental 4M variations that occur accidentally during the manufacturing and inspection processes of products are searched for. Note that these accidental 4M variations correspond to accidental condition changes in this example.

[0066] Then, in step S307, data that corresponds to outliers and is affected by accidental 4M fluctuations is further excluded from the data used to calculate the actual values. Then, in step S308, average values ​​of production volume and takt time are calculated using the data obtained in step S307, from which the outliers and data affected by accidental 4M fluctuations have been excluded. Then, in step S309, the calculated values ​​are stored as best values ​​in the memory unit 11c. When the processing of step S309 is completed, this flow is temporarily terminated. In this case, when outputting a report corresponding to step S105 in FIG. 4, all accidental 4M fluctuations related to the data excluded in step S308 may be listed.

[0067] According to the above-described method for calculating actual values ​​and best values, the effects of planned 4M variations and accidental 4M variations can be excluded from the actual values, improving the accuracy of the best values ​​and, in particular, making it possible to clarify which of the accidental 4M variations is affecting the best value of the process.

[0068] As will be explained in detail later, planned 4M variations include product model changes, planned maintenance, condition changes, etc. In the case of board manufacturing, accidental 4M variations include reel changes on mounters, emergency stops due to frequent mounting errors, adjustments made by workers, and condition changes made by workers.

[0069] Example 4 Next, as a fourth embodiment, a specific example of linking 4M variation information and evaluation data will be described. (Linking 4M fluctuation information and evaluation data) Specifically, the information on 4M fluctuations and the data for each product may be linked as follows: (1) In the case of 4M fluctuations that occur during mounting and inspection of a specified board (between board loading and unloading) The production cycle time (the difference between the removal time of a given board and the removal time of the next board) is linked to the next board. In this case, the impact of 4M fluctuations is reflected in the production cycle time of the next board. Additionally, the error rate is linked to the board in question. In this case, the impact of 4M fluctuations is reflected in the sample of the board in question (number of mounted and inspected components and number of error components). (2) In the case of 4M fluctuations that occur other than those mentioned above (other than during mounting or inspection) The production cycle time (the difference between the removal time of a given board and the removal time of the next board) is linked to the next board. In this case, the impact of 4M fluctuations is reflected in the production cycle time of the next board. In addition, the error rate excludes the sample of the board in question (number of components mounted and inspected, and number of error components). In this case, the impact of 4M fluctuations is reflected in the sample of that board (number of components mounted and inspected, and number of error components). From the above, any 4M fluctuations that occur after a given board is removed and before the next board is removed will be linked to the next board.

[0070] (Classification and acquisition method of 4M fluctuation information) Next, examples of classification of 4M variation information and methods for acquiring each type of 4M variation will be described. (1) Planned 4M Changes (1-1) Product model changeover (setup change) The program name is obtained from the mounting and inspection data (on the premise that the oldest program is processed for each device), and when the program name is changed from the previous board, it is linked to the board. Regarding the information that the program of the inspection machine has been replaced (the program name and time after replacement), the information is output from the machine to the production management device 1a, and the information of the machine at that time is Link it to the next board. (1-2) Planned work on equipment (maintenance, condition changes, etc.) A work plan for a device is registered in advance, and any changes made to the planned device are output from the device to the production management device 1a. If a work plan for that device is nearby (within 30 minutes before or after, for example), it is linked to the board for that device immediately after that time. Also, the worker registers the fact that he or she has performed planned work in the production management device 1a on his or her terminal, and it is linked to the board for that device immediately after that time. (2) Accidental 4M fluctuations (2-1) Reel replacement for mounter The reel ID attached to the feeder is obtained from the mounting data (assuming that processing is performed for each device starting from the oldest), and when the reel ID changes from the previous board or partway through the current board, it is linked to that board.In addition, information that a feeder has been attached or detached on the mounting machine is output from the device to the production management device 1a along with the reel ID, and when the reel ID has changed, it is linked to the board on that device immediately after that time. (2-2) Emergency shutdown due to frequent implementation errors Information that the mounting machine has stopped is output from the device to the production management device 1a, and is linked to the board of that device immediately after that time. (2-3) Work on equipment that was not planned (adjustments, changes in conditions, etc. based on the worker's judgment) A work plan for a device is registered in advance, and any changes made to the planned device are output from the device to the production management device 1a. If there is no work plan for that device in the vicinity (within 30 minutes before or after, for example), the device is linked to the board immediately after that time for that device. Also, the worker registers in the production management device 1a on their terminal that they have performed work that is not in the plan, and the device is linked to the board immediately after that time for that device. Note that the immediately after board does not have to be specified as being within a certain number of minutes, but may refer to the oldest board after that time.

[0071] <Example 5> As a more specific example, the manner in which data for each board is handled when the production cycle time is used as an index relating to the productivity or quality of the product and the (actual value and) best value is calculated will be described below. [First aspect] Figure 15 shows the data for board serial numbers 1 to 8. In this case, when calculating the best value, the data for board serial number 1 is excluded from the statistical sample because there is no previous board. The data for board serial number 3 is an outlier, but there is no 4M fluctuation, so it is not excluded from the sample. The data for board serial number 5 is an accidental fluctuation and an outlier, but it is not excluded from the sample. The data for board serial number 7 is a planned fluctuation and an outlier, so it is excluded from the sample. Then, the actual value is calculated using the data for the remaining boards.

[0072] In addition to the above, when calculating the best value, board serial number 3 is an outlier, but is not excluded because there is no 4M variation (it can be excluded and the best value calculated. In this case, the improvement details are unknown and cannot be presented. The best value is defined as a target value that could be achieved if the areas for improvement are eliminated, even though the areas for improvement are unknown at this time). Furthermore, board serial number 4 is an accidental variation, but is not an outlier, so it is not excluded from the sample. Board serial number 5 is both an accidental variation and an outlier, so it is excluded from the sample. Then, the actual value is calculated using the remaining boards. In other words, the best value is defined as a target value that could be achieved if the areas for improvement are known and eliminated.

[0073] That is, in this embodiment, actual values ​​are calculated by excluding samples that have been affected by planned 4M variations and have become outliers from the process data, and the best values ​​are calculated by further excluding samples that have been affected by accidental 4M variations and have become outliers. As a result, the best values ​​are calculated by excluding samples that have been affected by 4M variations and have become outliers.

[0074] [Second Aspect] Next, we will explain the second way of handling data when calculating the best value using production cycle time as an index. This is a way of excluding outliers. Here, board serial number 1 in Figure 15 has no previous board, so it is excluded from the sample. Board serial numbers 3, 5, and 7 are outliers, so they are also excluded from the sample. Then, the actual value is calculated using the remaining boards. In this case, the best value is defined as a target value that can be achieved if the areas for improvement are eliminated, even though the areas where improvement is needed are currently unknown.

[0075] That is, in this embodiment, the best value is calculated by excluding outlier samples from the process data.

[0076] [Third Aspect] Next, we will explain a third method of handling data when calculating the best value using production cycle time as an index. This method does not distinguish between planned and accidental 4M fluctuations. Here, in Figure 16, board serial number 1 is excluded from the sample because there is no previous board. Board serial number 3 is an outlier but does not have 4M fluctuations, so it is not excluded. (Although the details of improvement cannot be shown, it may be excluded and the actual value calculated.) Board serial number 4 has 4M fluctuations but is not an outlier, so it is not excluded from the sample. Board serial number 5 has 4M fluctuations and is an outlier, so it is excluded from the sample. Board serial number 7 has 4M fluctuations and is an outlier, so it is excluded from the sample. The best value is then calculated using the remaining boards. In this method, planned (understood) 4M fluctuation factors are also listed as targets for improvement.

[0077] [Fourth aspect] Next, we will explain a fourth mode of data handling when calculating the best value using the production cycle time as an index. Figure 16 shows data for board serial numbers 1 to 8. This is a mode that does not use outliers. Here, board serial number 1 has no previous board, so it is excluded from the sample. Board serial number 5 is an accidental variation, so it is not excluded from the sample. Board serial number 7 is a planned variation, so it is excluded from the sample. Then, the actual value is calculated using the remaining boards. Furthermore, (in addition to the above), board serial numbers 4 and 5 are also accidental variations, so they are excluded from the sample. Then, the best value is calculated using the remaining boards. In this case, the best value is defined as the target value that would be achievable if the known 4M variations were eliminated (the target value that could be achieved if things that would be better off not existing were eliminated).

[0078] [Fifth aspect] Next, we will explain how to present the improvement target. Here, when calculating the best value using the production cycle time as an index, the 4M variation (reel change) of the sample excluded when calculating the best value in the first data handling mode is presented as the improvement target. Figure 17(a) again shows the data for board serial numbers 1 to 8. Also, Figure 17(b) shows an example of the text to be presented. The text states that the actual production cycle time is 1 minute 42 seconds, that the best production cycle time is 1 minute 35 seconds, that the production cycle time can be reduced by 7 seconds, and that the improvement target is "reel change." The improvement target may also be presented along with the number of times: "reel change (total 12 times)" and "stops due to frequent errors (total 4 times)." The improvement target may also be presented along with the total time, such as "reel change (total 22 minutes 32 seconds)" and "stops due to frequent errors (total 5 minutes 16 seconds)." Here, the total time is the sum of "value of the excluded sample - best value" (the amount increased by the 4M variation). Furthermore, the improvement targets may be presented along with the number of times and the total time, such as "reel replacement (total 12 times, 22 minutes 32 seconds)" or "stops due to many errors (total 4 times, 5 minutes 16 seconds)."

[0079] [Sixth Aspect] Next, we will explain another aspect of presenting improvement targets. An example of the presented text is shown in Figure 18(a). Here, the following is presented: the actual production cycle time is 1 minute 42 seconds, the best production cycle time is 1 minute 35 seconds, the production cycle time can be reduced by 7 seconds, and the improvement target is "reel replacement." Here, as shown in Figure 18(b), specific tasks can be registered in the system in advance as improvement targets, and these can be presented as additional examples.

[0080] In the following, the constituent elements of the present invention will be noted with the reference numerals in the drawings in order to make it possible to compare the constituent elements of the present invention with the configurations of the embodiments. <Appendix 1> A production management system (1) for a production line (10) having one or more manufacturing devices and inspection devices, in which a product manufacturing process and an inspection process are performed by the manufacturing devices and the inspection devices, a performance value calculation unit (110a) for calculating a production performance value, which is a performance value of an index related to productivity or quality of the product in the production line (10); an actual production value calculation unit (110a) that calculates an actual production value, which is an actual value of an index related to the productivity or quality of the product in the production line, based on the actual performance value; Equipped with The production management system (1) is characterized in that the production capability value is an index related to the productivity or quality of the product, calculated by excluding data on the index that corresponds to a statistical outlier in the distribution of the actual production values ​​and / or data on the index that has been affected by a predetermined change in conditions on the production line, from data on the index related to the productivity or quality of the product on the production line. <Appendix 6> A production management method for a production line (10) having one or more manufacturing devices and inspection devices, in which a product manufacturing process and an inspection process are carried out by the manufacturing devices and the inspection devices, comprising: a performance value calculation step (S102) of calculating a performance value of an index relating to the productivity or quality of the product in the production line (10); a production capability value calculation step (S103) of calculating a production capability value, which is a capability value of an index related to the productivity or quality of the product in the production line, based on the performance value; and A production management method characterized in that the production capability value is an index related to the productivity or quality of the product, calculated by excluding, from data on an index related to the productivity or quality of the product on the production line, data on the index that corresponds to a statistical outlier in the distribution of the actual production values ​​and / or data on the index that has been affected by a predetermined change in conditions on the production line. <Appendix 11> A computer (1a) for a production line (10) having one or more manufacturing devices and inspection devices, in which a manufacturing process and an inspection process of a product are performed by the manufacturing device and the inspection device, an actual production value calculation step (S102) of calculating an actual production value which is an actual value of an index related to the productivity or quality of the product in the production line; an actual value calculation step (S103) of calculating an actual production value, which is an actual value of an index related to the productivity or quality of the product in the production line, based on the actual performance value; Execute The production capability value is an index relating to the productivity or quality of the product, calculated by excluding data on the index that corresponds to a statistical outlier in the distribution of the production performance values ​​and / or data on the index that is affected by a predetermined change in conditions on the production line from data on the index relating to the productivity or quality of the product on the production line. ,program. [Explanation of symbols]

[0081] 1. Production control system 1a Production control device 10. Production Line 10a Solder printing device 10b: Post-solder printing inspection device 10c Mounter 10d...Post-mount inspection equipment 10e···Reflow oven 10f...Post-reflow inspection equipment 11a Data acquisition section 11b Control section 11c...Storage section 11d Output section 110a... Actual value calculation section 110b Best value calculation section 110c...Result reporting department

Claims

1. A production management system for a production line having one or more manufacturing devices and inspection devices, in which a manufacturing process and an inspection process of a product are carried out by the manufacturing devices and the inspection devices, a performance value calculation unit that calculates a production performance value that is a performance value of an index related to the productivity or quality of the product on the production line; an actual production value calculation unit that calculates an actual production value, which is an actual value of an index related to the productivity or quality of the product on the production line, based on the actual performance value; Equipped with the production capability value is an index related to the productivity or quality of the product, calculated by excluding, from data on the index related to the productivity or quality of the product on the production line, data on the index corresponding to a statistical outlier in the distribution of the actual production values ​​and / or data on the index affected by a predetermined change in conditions on the production line; the predetermined condition change includes a planned condition change that is planned in advance for the production line and an accidental condition change that occurs accidentally on the production line, the actual production value calculation unit calculates the actual production value by excluding, from data on an index related to the productivity or quality of the product on the production line, data on the index that corresponds to a statistical outlier in the distribution of the actual production values ​​and that has been affected by a planned change in conditions on the production line; a production management system characterized in that the capability value calculation unit calculates the production capability value by excluding, from data on an index related to productivity or quality of the product used in calculating the production performance value, data on the index that corresponds to a statistical outlier in the distribution of the production performance values ​​and that has been affected by an accidental change in conditions on the production line.

2. 2. The production management system according to claim 1, wherein the indicators relating to the productivity or quality of the products on the production line include at least one of the production volume of the products per predetermined time, the manufacturing takt time of the products, and the error rate of the products.

3. 3. The production management system according to claim 1, further comprising a result reporting unit that creates a result report that allows comparison between the actual production value and the production capability value for a predetermined period. Tem.

4. a result reporting unit that creates a result report that allows a comparison between the actual production value and the production capability value for a predetermined period of time; 2. The production management system according to claim 1, wherein the result reporting unit reports the content of the accidental change in conditions, which is related to the data of the index that was excluded when the production capability value calculation unit calculated the production capability value.

5. 1. A production management method for a production line having one or more manufacturing devices and inspection devices, in which a manufacturing process and an inspection process for a product are carried out by the manufacturing device and the inspection device, comprising: a performance value calculation step of calculating a performance value of an index relating to the productivity or quality of the product on the production line; a production capability value calculation step of calculating a production capability value, which is a capability value of an index related to the productivity or quality of the product in the production line, based on the actual performance value; and the production capability value is an index related to the productivity or quality of the product, calculated by excluding, from data on the index related to the productivity or quality of the product on the production line, data on the index corresponding to a statistical outlier in the distribution of the actual production values ​​and / or data on the index affected by a predetermined change in conditions on the production line; the predetermined condition change includes a planned condition change that is planned in advance for the production line and an accidental condition change that occurs accidentally on the production line, In the actual value calculation step, the actual production value is calculated by excluding data of the index related to the productivity or quality of the product on the production line, the data of the index corresponding to a statistical outlier in the distribution of the actual production values ​​and affected by a planned change in conditions on the production line; a production management method characterized in that, in the step of calculating the actual capability value, the production capability value is calculated by further excluding, from data on an index related to the productivity or quality of the product used in calculating the actual production value, data on the index that corresponds to a statistical outlier in the distribution of the actual production values ​​and that is affected by an accidental change in conditions on the production line.

6. 6. The production management method according to claim 5, wherein the indicators relating to the productivity or quality of the products on the production line include at least one of the production volume of the products per predetermined time, the manufacturing takt time of the products, and the error rate of the products.

7. 7. The production management method according to claim 5, further comprising a result reporting step of creating a result report that enables comparison between the actual production value and the production capability value.

8. The method further comprises a result reporting step of creating a result report that allows the actual production value and the production capability value to be compared, 6. The production management method according to claim 5, wherein the result reporting step includes reporting the content of the accidental change in conditions related to the data of the index excluded when calculating the production capability value in the capability value calculation step.

9. A production line has one or more manufacturing devices and inspection devices, and a manufacturing process and an inspection process of a product are performed by the manufacturing device and the inspection device. a performance value calculation step of calculating a production performance value which is a performance value of an index related to productivity or quality of the product on the production line; a production capability value calculation step of calculating a production capability value, which is a capability value of an index related to the productivity or quality of the product in the production line, based on the actual performance value; Execute the production capability value is an index related to the productivity or quality of the product, calculated by excluding, from data on the index related to the productivity or quality of the product on the production line, data on the index corresponding to a statistical outlier in the distribution of the actual production values ​​and / or data on the index affected by a predetermined change in conditions on the production line; the predetermined condition change includes a planned condition change that is planned in advance for the production line and an accidental condition change that occurs accidentally on the production line, In the actual value calculation step, the actual production value is calculated by excluding data of the index related to the productivity or quality of the product on the production line, the data of the index corresponding to a statistical outlier in the distribution of the actual production values ​​and affected by a planned change in conditions on the production line; the program, characterized in that in the actual capability value calculation step, the production capability value is calculated by excluding, from data on an index related to the productivity or quality of the product used in calculating the actual production value, data on the index that corresponds to a statistical outlier in the distribution of the actual production values ​​and that has been affected by an accidental change in conditions on the production line.

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