EP2436816B1

EP2436816B1 - Sewing machine work analyzing device and sewing machine work analysis method

Info

Publication number: EP2436816B1
Application number: EP11183220.0A
Authority: EP
Inventors: Masami Minami; Masahiko Ueta; Natsuko Yashiro
Original assignee: Juki Corp
Current assignee: Juki Corp
Priority date: 2010-09-29
Filing date: 2011-09-29
Publication date: 2016-08-31
Anticipated expiration: 2031-09-29
Also published as: CN102433690A; EP2436816A1; CN102433690B

Description

[Technical Field]

The present invention relates to a sewing machine work analyzing device and a sewing machine work analysis method as defined in the preambles of claims 1 and 15.

[Background Art]

A production process control system is known from EP 0 160 317 A2 .
For efficient production of workpieces by a sewing machine, sewing machine work analyzing devices have been developed. A conventional sewing machine work analyzing device measures and calculates, for example, transition of the number of rotations of the upper shaft of a sewing machine with elapse of time and indexes relating to production efficiency such as the number of workpieces per unit time, and informs a user of quantified results or graphs of results by displaying these on an operation panel.
Patent Document 1 discloses a sewing machine work analyzing device that records changes in the number of rotations of a sewing machine and sewing work times for individual sewing work units in a time-oriented manner. The sewing machine work analyzing device described in Patent Document 1 measures sewing machine working situations of operators at a sewing plant and indicates a pitch diagram. Accordingly, from a work time that an operator needs to perform one process, process allocation (line balance) can be checked. In addition, progress management for grasping a status of the sewing work achievement can be performed. Further, actions of an operator can be analyzed by graphically indicating the sewing speed in a time-oriented manner.
Patent Document 2 discloses a sewing machine production management device in which a push-button switch is disposed near a sewing operator and the push-button switch is pressed each time the sewing operator performs a sewing work of one process. The sewing machine production management device described in Patent Document 2 measures pitch times of one process by measuring intervals of times at which the push-button switch is pressed. Further, instead of the push-button switch, from time intervals of thread-cutting signals of the sewing machine, the pitch times are measured.
Patent Document 3 discloses a sewing machine sewing recording device that records drive/stop of a sewing machine motor and a rotation speed when driving and indicates these as a graph showing time on the horizontal axis and the number of rotations on the vertical axis.
Hereinafter, in this specification, the time that an operator needs to perform a sewing work of one process will be referred to as "pitch time." The pitch time is a time interval from thread cutting to the next thread cutting of a sewing machine. In this specification, the pitch time is defined as showing a time from thread cutting to the next thread cutting, however, the definition of the pitch time is not limited to this. The pitch time may be, for example, a period from a timing at which an operator takes a cloth that has not been sewn yet to a timing at which the operator places the sewn cloth. Specifically, the pitch time means a period (one cycle) that can represent one time of sewing work. However, definition of the pitch time as a time from thread cutting to the next thread cutting is preferable because the pitch time can be easily calculated.
Works that an operator performs in a day are classified into "regular work times" as work times that occur in every process of processing a product, and "irregular work times" as work times that directly occur irregularly in one process of processing a product.
The regular work times are work times that occur in every process of processing a product, including the times of operator's works of taking a cloth that has not been sewn yet (taking a cloth), sewing the cloth with a sewing machine, turning the workpiece, sewing with the sewing machine, and placing the workpiece.
The irregular work times are work times that occur irregularly in one process of processing a product except for the works that occur in every process, including the times of operator's works of carrying a product (workpiece) and correcting a defective product, the times of failures due to thread breakage or needle breakage, holding a meeting for arrangement and consultation, entry in a sewing record sheet, looking away, and talking, etc.
The ratio of the irregular work times to the regular work times is referred to as "idle ratio." The productivity can be improved by lowering (reducing) the idle ratio.
Figs. 1A and 1B are diagrams showing work times of an operator. Fig. 1A shows pitch times when regular works are repeated, and Fig. 1B shows pitch times when an irregular work is inserted.
As shown in Fig. 1A, an operator performs sewing by repeating works of taking a cloth that has not been sewn yet, sewing the cloth, turning the cloth, sewing the cloth, placing the sewn cloth, taking a cloth that has not been sewn yet, sewing. Sewing of one cloth in regular works is from the work of taking the cloth that has not been sewn yet to the work of placing the sewn cloth. Sewing of one cloth is as described above. In Fig. 1A, the "pitch time" that an operator needs to perform a sewing work of one process is measured as a time interval from thread cutting to the next thread cutting of a sewing machine.
The pitch time when an irregular work is inserted is shown in Fig. 1B. In Fig. 1B, after placing the sewn cloth, an irregular work (here, waiting for thread replacement) is inserted. As shown in Fig. 1B, the work time of the operator is a time obtained by adding the irregular work to the regular works. The pitch time is a time interval from thread cutting to the next thread cutting of a sewing machine, so that when an irregular work is inserted, the pitch time of the works becomes longer.

[Patent Document 1] JP-A-2009-160084
[Patent Document 2] JP-A-2004-105392
[Patent Document 3] JP-A-2006-167069

However, this conventional sewing machine work analyzing device has the following problems.

(1) The sewing machine work analyzing device according to Patent Document 1 cannot classify work times measured in a sewing machine into "regular work times" and "irregular work times" and cannot calculate the "idle ratio."
In order to calculate the idle ratio, measurement of a work time necessary for processing a product, calculation of a regular work time from the number of workpieces sewn in a day, and calculation of a ratio of the regular work time to a working time of a day must be performed for all operators.
As a work time necessary for processing a product, several work times are measured with a stop watch while observing sewing works of an operator by the side of the operator, and an average of the work times is calculated. This measurement is performed for all operators, so that a great deal of time is taken.
(2) Similarly to the sewing machine work analyzing device described in Patent Document 1, the sewing machine production management device described in Patent Document 2 cannot distinguish between regular works of "taking, sewing, and placing" a workpiece, and irregular works of going to a bathroom, carrying an object, and holding a meeting.
(3) The sewing machine sewing recording device described in Patent Document 3 can record work times, but cannot judge variations in the work times.

Normally, the "sewing work" is influenced by the skill of an operator, but the work time thereof has fewer variations.
The possible causes for great variations in sewing work times are (1) negligence of an operator during the work, and (2) difficulty in the sewing work due to the material and shape of the workpiece, etc.

[SUMMARY OF THE INVENTION]

An object of the present invention is to provide a sewing machine work analyzing device and a sewing machine work analysis method by which "regular work times" necessary for processing products and other "irregular work times" are automatically classified.
A sewing machine work analyzing device according to the present invention includes: a pitch time measuring means for measuring a pitch time; a pitch time frequency distribution calculating means for calculating a pitch time frequency distribution based on the measured pitch time; a work time classifying means for classifying a work time into a regular work time and an irregular work time based on the calculated pitch time frequency distribution; and an output means for outputting the classified regular work time and irregular work time in an identifiable manner.
A sewing machine work analysis method according to the invention includes: measuring a pitch time; calculating a pitch time frequency distribution based on the measured pitch time; classifying a work time into a regular work time and an irregular work time based on the calculated pitch time frequency distribution; and outputting the classified regular work time and irregular work time in an identifiable manner.

[Effect of the Invention]

According to the present invention, all work times of an operator can be collected and automatically classified into "regular work times" necessary for processing products and other "irregular work times" based on the tendency of the work time data, and the "idle ratio" as a ratio of the irregular work times to the regular work times can be calculated.
Accordingly, the work time for man-powered investigation using a stop watch, etc., can be omitted. The production situation can be grasped by observing the ratio of the regular work times as times necessary for processing products, and this can lead to the discovery of and a countermeasure in response to a sewing machine in question in a production line. Further, the levels of the skills of operators can be known, and wasteful work times can be known.

[BRIEF DESCRIPTION OF THE DRAWINGS]

The following description of a preferred embodiment of the present invention serves to explain the invention in greater detail in conjoint with the drawings. These show:

Figs. 1A and 1B are explanatory views of work times of an operator;
Fig. 2 is a view showing an entire configuration of a sewing machine work analyzing system according to a first embodiment of the present invention;
Fig. 3 is a block diagram showing a configuration of the sewing machine work analyzing device according to the first embodiment;
Figs. 4A and 4B are flowcharts showing a work analyzing operation of the sewing machine work analyzing device according to the first embodiment;
Figs. 5A and 5B are diagrams showing pitch time frequency distributions of Example 1 of the sewing machine work analyzing device according to the first embodiment;
Figs. 6A and 6B are diagrams showing a regular work time data range of Example 1;
Figs. 7A and 7B are diagrams showing pitch time frequency distributions in units of 1 second of Example 2 of the sewing machine work analyzing device according to the first embodiment;
Figs. 8A and 8B are diagrams showing a data range of the largest number of data of Example 2;
Fig. 9 is a diagram showing extraction of average ±σ measurement data of Example 3 of the sewing machine work analyzing device according to the first embodiment;
Figs. 10A and 10B are diagrams showing calculation of an idle ratio by using a plurality of sewing machines by the sewing machine work analyzing device according to the first embodiment;
Fig. 11 is a diagram showing comparison in idle ratio among the sewing machines by the sewing machine work analyzing device according to the first embodiment;
Fig. 12 is a diagram showing comparison in idle ratio among production lines by the sewing machine work analyzing device according to the first embodiment;
Figs. 13A to 13C are diagrams showing editing of regular work classification by the sewing machine work analyzing device according to the first embodiment;
Fig. 14 is a diagram showing transition of the idle ratio in the sewing machine work analyzing device according to the first embodiment;
Fig. 15 is a block diagram showing a configuration of a sewing machine work analyzing device according to a second embodiment of the present invention;
Fig. 16 is a diagram showing sewing work times in regular work times in the sewing machine work analyzing device according to the second embodiment;
Figs. 17A and 17B are diagrams showing calculation of variations in sewing work time and abnormal value determination by the sewing machine work analyzing device according to the second embodiment;
Fig. 18 is a diagram graphically showing the calculated variations in sewing work time among operators by showing the operators on the horizontal axis in the sewing machine work analyzing device according to the second embodiment;
Fig. 19 is a diagram graphically showing the average of Fig. 18 as transition of variations in sewing work time of the operators by showing the time on the horizontal axis;
Fig. 20 is a diagram showing a graph comparing average variations among lines when a plurality of lines are included in the sewing machine work analyzing device according to the second embodiment;
Fig. 21 is a diagram showing frequency distributions of irregular work times of a sewing machine work analyzing device according to a third embodiment of the present invention;
Fig. 22 is a diagram showing sums of irregular work times of the sewing machine work analyzing device according to the third embodiment;
Fig. 23 is a diagram showing sums of operator-specific irregular work times of the sewing machine work analyzing device according to the third embodiment;
Fig. 24 is a diagram showing sums of time-specific irregular work times of the sewing machine work analyzing device according to the third embodiment;
Fig. 25 is a diagram showing operator-specific idle ratios of the sewing machine work analyzing device according to the third embodiment;
Fig. 26 is a diagram showing sums of irregular work times of a selected operator of the sewing machine work analyzing device according to the third embodiment;
Figs. 27A and 27B are views showing an entire configuration of a sewing machine work analyzing system according to the present invention; and
Figs. 28A and 28B are views showing an entire configuration of a work analyzing system of a sewing machine work analyzing device according to the present invention.

[Best Mode for Carrying Out the Invention]

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

(First Embodiment)

Fig. 2 is a view showing an entire configuration of a sewing machine work analyzing system according to a first embodiment of the present invention. The present embodiment is an example of application to a sewing machine work analyzing system that calculates "regular work time," "irregular work time," and "idle ratio."
A time necessary for an operator to perform a sewing work of one process is referred to as a pitch time. Processes are allocated so that the pitch time is 30 to 120 seconds, generally. Sewing works are performed by humans, so that the pitch time varies by approximately 5 seconds.
As shown in Fig. 2, the sewing machine work analyzing system includes a plurality of sewing machines 1, 2... N, a router 10 that connects the sewing machines 1, 2... N, and a work analyzing device 100 that collects and analyzes information of the sewing machines 1, 2... N connected via the router 10.
The router 10 may be a wired LAN or a wireless LAN.
As the sewing machine work analyzing device 100, a personal computer or work station is used.
Fig. 3 is a block diagram showing a configuration of the sewing machine work analyzing device.
As shown in Fig. 3, the sewing machine work analyzing device 100 includes a pitch time gauge 110, a pitch time frequency distribution calculator 120, a work time classifier 130, an idle ratio calculator 140, and an output section 150.
The pitch time gauge 110 measures a pitch time that is a time interval from thread cutting to the next thread cutting of a sewing machine by using operation start/stop/thread cutting signals of the sewing machine. The pitch time gauge 110 measures pitch times from the time intervals of thread cutting signals output from the sewing machines 1, 2... N. Alternatively, the pitch time gauge 110 measures pitch times of one process by measuring time intervals of depressing the of press-button switches provided in the sewing machines or near the sewing machines and connected to the router 10.
The pitch time frequency distribution calculator 120 calculates pitch time frequency distributions based on the pitch times measured by the pitch time gauge 110. The pitch time frequency distribution calculator 120 extracts work time data whose occurrence frequency is high from the pitch time data measured a plurality of times.
The work time classifier 130 classifies the work times into regular work times and irregular work times based on the calculated pitch time frequency distributions.
In detail, the work time classifier 130 includes a data search section 131, an average calculator 132, a regular work time calculator 133, and an irregular work time calculator 134.
The data search section 131 searches for a data range of a highest frequency value or the largest number of data from the created pitch time frequency distributions.
The average calculator 132 calculates an average of the pitch times from measurement data belonging to the searched data range.
The regular work time calculator 133 calculates a regular work time based on a product of the calculated average and the production quantity.
The irregular work time calculator 134 calculates an irregular work time by subtracting the calculated regular work time from the total work time of the operator.
The idle ratio calculator 140 calculates an idle ratio from a ratio of the irregular work time to the regular work time.
The output section 150 outputs the classified regular work times and irregular work times and/or the idle ratio in an identifiable manner. The output section 150 outputs a ratio of the calculated regular work time to a total working time or to the irregular work time. The output section 150 outputs work analysis results for comparison of idle ratios calculated from a single sewing machine or a plurality of sewing machines in the single sewing machine or among the plurality of sewing machines.
The output section 150 includes, for example, a display/printing section that displays/prints analysis results, an output port that outputs analysis results to an external memory, etc., or a communicator that transmits analysis results by wire or wirelessly.
The sewing machine work analyzing device 100 collects all work times of an operator, automatically classifies the work times into "regular work times" that occur in every process of processing a product and other "irregular work times" from the tendencies of the work time data, and calculates an "idle ratio" as a ratio of the irregular work times to the regular work times.
Hereinafter, operations of the sewing machine work analyzing device 100 configured as described above will be described.
First, an operation of automatically classifying work times of an operator into regular work times and irregular work times will be described.
Figs. 4A and 4B are flowcharts showing a work analyzing operation of the sewing machine work analyzing device 100, and Fig. 4A shows an entire flow, and Fig. 4B shows a flow of calculation of regular work times/irregular work times. In the drawings, "S" denotes each step of the flow.
At Step S1, the pitch time gauge 110 measures pitch times by using signals of operation start, operation stop and thread cutting of a sewing machine. The thread cutting signal is a thread cutting signal from the sewing machine or a detection signal of the press-button switch to be operated by an operator when cutting a thread.
At Step S2, the pitch time frequency distribution calculator 120 calculates pitch time frequency distributions based on the pitch times measured by the pitch time gauge 110. The pitch time frequency distribution calculator 120 extracts work time data whose occurrence frequency is high from the pitch time data measured a plurality of times.
At Step S3, the work time classifier 130 classifies the work times into regular work times and irregular work times based on the calculated pitch time frequency distributions.
At Step S4, the idle ratio calculator 140 calculates an idle ratio from a ratio of the irregular work times to the regular work times.
At Step S5, the output section 150 outputs the classified regular work times and irregular work times and/or the idle ratio in an identifiable manner, and then, this flow is ended.
In Fig. 4B, the following operations are performed at Step S3 described above.
At Step S11, the data search section 131 searches for a data range of a highest frequency value or the largest number of data from the created pitch time frequency distributions.
At Step S12, the average calculator 132 calculates an average of the pitch times from measurement data belonging to the searched data range.
At Step S13, the regular work time calculator 133 calculates a regular work time based on a product of the calculated average and the production quantity.
At Step S14, the irregular work time calculator 134 calculates an irregular work time by subtracting the calculated regular work time from the total work time of the operator.
Next, an example of the sewing machine work analyzing device 100 will be described.

[Example 1]

Figs. 5A and 5B are diagrams showing pitch time frequency distributions of Example 1 of the sewing machine work analyzing device 100, and Fig. 5A shows an example of pitch time frequency distributions, and Fig. 5B shows values at a selected position or in a selected section of the frequency distributions.
Figs. 6A and 6B are diagrams showing a regular work time data range of Example 1 of the sewing machine work analyzing device 100, and Fig. 6A shows an example of a regular work time data range, and Fig. 6B shows values at a selected position or in a selected section of the data range.

(1) As shown in Figs. 5A and 5B, the pitch time frequency distribution calculator 120 creates pitch time frequency distributions in data ranges of 5 seconds that are a variation normally occurring when an operator who does not have a significant variation works.
(2) The data search section 131 detects a data range of the highest frequency (the hatched section in Fig. 5A).
(3) The average calculator 132 calculates a reference value X (sec) that is an average of measurement data belonging to the data range of the highest frequency.
(4) As shown in Figs. 6A and 6B, the average calculator 132 extracts measurement data belonging to the data range of ±10% of the reference value X (sec), and calculates a regular work time average Y (sec) (refer to the hatched section in Fig. 6A).
(5) The regular work time calculator 133 calculates a total regular work time A (sec) that is a sum of the regular work times according to the following equation (1) based on a product of the regular work time average Y (sec) calculated in (4) above and the total production quantity M (number of workpieces). The total regular work time A includes regular work times in processes (pitch times) including irregular works. $Total regular work time A (\sec) = Regular work pitch time average Y (\sec) \times Total production quantity M (number of workpieces)$
(6) The irregular work time calculator 134 calculates a total irregular work time as a sum of the irregular work times by subtracting the calculated total regular work time from the total work time of the operator. As shown in the following equation (2), the time obtained by subtracting the total regular work time from the total work time S (sec) of the operator is the total irregular work time B (sec). $Total regular work time B (\sec) = Total work time S (\sec) \times Total regular work time A (\sec)$

[Example 2]

Figs. 7A and 7B are diagrams showing pitch time frequency distributions in units of 1 second of Example 2 of the sewing machine work analyzing device 100, and Fig. 7A shows an example of the pitch time frequency distributions in units of 1 second, and Fig. 7B shows values at a selected position or in a selected section of the frequency distributions.
Figs. 8A and 8B are diagrams showing a data range of the largest number of data of Example 2 of the sewing machine work analyzing device 100, and Fig. 8A shows an example of the data range of the largest number of data, and Fig. 8B shows values at a selected position or in a selected section in the data range.

(1) As shown in Figs. 7A and 7B, the pitch time frequency distribution calculator 120 creates pitch time frequency distributions in 1-second ranges.
(2) The data search section 131 shifts a data acquisition range of 5 seconds by every one second at a time in such a manner that the data acquisition range shifts from the range of 0 to 5 seconds to the range from 1 to 6 seconds in the range from the minimum value to the maximum value of the pitch times (refer to Fig. 7A) to search for a data range of the largest number of data (number of workpieces) within the data acquisition range (refer to the hatched section in Fig. 8A).
(3) As shown in Figs. 8A and 8B, the average calculator 132 calculates a regular work time average X (sec) that is an average of the pitch times belonging to the data acquisition range as a search result.
(4) The total regular work time A (sec) is calculated based on a product of the calculated regular work time average X (sec) and the production quantity M (number of workpieces).
(5) The irregular work time calculator 134 calculates an irregular work time by subtracting the calculated regular work time from the total work time of the operator. As shown in equation (2) described above, a time obtained by excluding the regular work time A (sec) from the total work time S (sec) of the operator is the irregular work time B (sec).

[Example 3]

Fig. 9 is a diagram showing extraction of measurement data of average ±σ in Example 3 of the sewing machine work analyzing device 100.

(1) As shown in Fig. 5A, the pitch time frequency distribution calculator 120 creates pitch time frequency distributions in 5-second ranges.
(2) The data search section 131 detects a data range of a highest frequency value (refer to the hatched section in Fig. 5A).
(3) The average calculator 132 calculates a reference value X (sec) that is an average from measurement data belonging to the data range of the highest frequency value.
(4) As shown in Fig. 9, the average calculator 132 calculates a standard deviation σ according to the following equation (3) from all measurement data. $standard deviation σ = \sqrt{\sum (pitch time - reference value X^{2})}$
(5) As shown in Fig. 9, the average calculator 132 extracts measurement data belonging to ±σ from the reference value calculated in (3) above.
(6) The average calculator 132 calculates a regular work time average Y (sec) of the extracted measurement data (refer to the hatched section in Fig. 9).
(7) The regular work time calculator 133 calculates a total regular work time A (sec) based on a product of the regular work time average Y (sec) calculated in (6) above and the total production quantity M (number of workpieces).
(8) The irregular work time calculator 134 calculates a total irregular work time by subtracting the calculated total regular work time from the total work time of the operator. As shown in the equation (2) above, a time obtained by excluding the total regular work time A (sec) from the total work time S (sec) of the operator is the irregular work time B (sec).

Three examples of methods for extracting work time data whose occurrence frequency is high from the tendency of all work time data of an operator collected in a sewing machine are described above. Other methods for extracting work time data whose occurrence frequency is high may also be adopted.
Next, calculation of idle ratios by the idle ratio calculator 140 will be described.

[Calculation of idle ratios]

In the present embodiment, in a single sewing machine or a plurality of selected sewing machines, idle ratios are calculated. An idle ratio is calculated based on a ratio of a total irregular work time to a total regular work time according to the following equation (4). $Idle ratio (%) = Total irregular work time (\sec) / Total regular work time (\sec) \times 100$
Figs. 10A and 10B are views showing calculation of idle ratios of a plurality of sewing machines.
As shown in Fig. 10A, a total regular work time and a total irregular work time of each of the selected sewing machines are calculated. Calculations of a total regular work time and a total irregular work time are described above. As shown in Fig. 10B, the idle ratio is calculated from a ratio of the total irregular work time to the total regular work time.
When a plurality of sewing machines are selected and idle ratios are calculated, a total regular work time and a total irregular work time are classified in each sewing machine. Then, according to the following equation (5), sums of work times are obtained, and then, the idle ratio is calculated. $Idle ratio (%) = Total irregular work time (\sec) / Total regular work time (\sec) \times 100$

[Comparison of idle ratios]

Fig. 11 and Fig. 12 are views showing comparison of idle ratios, Fig. 11 shows comparison in idle ratio among sewing machines, and Fig. 12 shows comparison in idle ratio among production lines.
The calculated idle ratios can be compared among the sewing machines or among the production lines each consisting of the plurality of sewing machines.
By comparison among sewing machines performing a work of the same process (refer to Fig. 11) and comparison among production lines producing the same item (refer to Fig. 12), it can be determined whether the productivities of the sewing machines or production lines are good, and the results can lead to discovery of problems in the sewing machines or production lines and countermeasures in response to the problems. For example, as shown in Fig. 11, the sewing machine A, the sewing machine B, and the sewing machine C have idle ratios smaller than an average, and it is proved that among these, the sewing machine B has an idle ratio of 25% (refer to the circle in Fig. 11) and is excellent in production efficiency. As shown in Fig. 12, the production line C, the production line D, and the production line E are production lines having idle ratios smaller than an average.
Even by comparison with 20% that is regarded as an average idle ratio of general production lines regardless of the sewn items, the production lines can be evaluated.

[Editing of regular work times]

Concerning regular work times and irregular work times, the regular work times occur in every process of processing a product and are necessary for the work, and the irregular work times are distinguished as times that are not always necessary other than the regular work times. The distinction criteria (as to whether the work is necessary) differ depending on the plant management method and the analysis viewpoint of a person in charge of management.

(Case I)

A person A (sewing machine A) does both a sewing work and a clerical work. The clerical work does not occur in every process of sewing, however, it is a necessary work. Therefore, it is desired to select a time during which the person A does a clerical work among irregular work times and include the clerical work in a regular work time.

(Case II)

When the layout of a sewing machine is not good, small carrying works are mixed with the automatically extracted regular works. Therefore, it is desired to extract more accurate regular work time data.
As in the above-mentioned Cases I and II, the classification of the extracted regular work times and irregular work times must be edited.
Figs. 13A to 13C are diagrams showing editing of regular work time classification.
As shown in Fig. 13A, first, a target sewing machine is selected, and pitch time frequency distributions of regular work times and irregular work times automatically extracted from the selected sewing machine are indicated.
Then, for example, the following editing operations (1) to (3) are performed. The editing operations (1) to (3) are examples of editing.

(1) Editing to change the classification of data automatically extracted as a regular work time to an irregular work time is performed.
(2) Editing to change the classification of data automatically extracted as an irregular work time to a regular work time is performed. As shown by "a." in Fig. 13A, when it is desired to change the classification of a time classified as an irregular work time to a regular work time, a person in charge of work analysis, etc., performs this editing to change the classification. Then, as shown in the hatched section in Fig. 13B, the work analyzing device 100 calculates an idle ratio from the editing result.
(3) Arbitrary data is excluded from data automatically extracted as irregular work times. As shown by "b." in Fig. 13A, when it is desired to exclude pitch times not less than 1 hour, a person in charge of analysis, etc., performs editing to change this classification. Then, as shown in Fig. 13C, from the editing result of Fig. 13A, the work analyzing device 100 excludes pitch times not less than 1 hour shown by "b." in Fig. 13A, and calculates an idle ratio.

[Transition of idle ratio]

Fig. 14 is a diagram showing transition of an idle ratio.
As shown in Fig. 14, a sewing machine is regarded as a target, an idle ratio of the target sewing machine is calculated at fixed time intervals, and transition of the idle ratio can be confirmed graphically. Alternatively, an idle ratio automatically calculated from a production line consisting of a plurality of sewing machines may be calculated at fixed time intervals, and transition thereof may be confirmed graphically.
Monthly, daily, and hourly indications are possible, and transition of an idle ratio before and after improvement can be confirmed.
As described in detail above, the sewing machine work analyzing device 100 of the present embodiment includes a pitch time gauge 110 that measures pitch times as time intervals from thread cutting to the next thread cutting of a sewing machine, and a pitch time frequency distribution calculator 120 that calculates pitch time frequency distributions based on the measured pitch times. The sewing machine work analyzing device 100 includes a work time classifier 130 that classifies work times into regular work times and irregular work times based on calculated pitch time frequency distributions, and an idle ratio calculator 140 that calculates an idle ratio from a ratio of the irregular work times to the regular work times. The output section 150 outputs the classified regular work times and irregular work times and/or an idle ratio in an identifiable manner.
With the above-described configuration, the sewing machine work analyzing device 100 collects all work times of an operator, automatically classifies the work times into "regular work times" necessary for processing products and other "irregular work times" based on the tendency of the work time data, and calculates "idle ratio" that is a ratio of the irregular work times to the regular work times, so that the work time for man-powered investigation using a stop watch, etc., can be omitted. In detail, the following effects are obtained.

(1) An average idle ratio of production lines is generally approximately 20% although it slightly differs depending on the sewing item. In a production line, operators appear to be sitting in front of sewing machines and working smoothly, however, in actuality, there is the possibility that productivity falls due to various factors such as delay in the flow of products or occurrence of waiting, slow sewing works of operators, and chatting with neighbors. The production situation that cannot be grasped at one glance can be grasped by checking a ratio of regular work times that are times necessary for processing products. The above-described confirmation can be made with each sewing machine, so that this can lead to discovery of a sewing machine in question in a production line and a countermeasure in response to the problematic sewing machine.
(2) By classifying "regular work times" and "irregular work times", it can be distinguished whether a work time is a necessary and essential time that occurs in every process of processing a product or another time, and this can be used as base data for the following analysis.

First, by more finely analyzing the regular work times, the level of skill of an operator can be known.
By more finely analyzing the irregular work times, a work during which an operator wastes time can be known.
The sewing machine work analyzing device 100 can arbitrarily edit the classified "regular work times" or "irregular work times," so that classification suitable for the viewpoint of a person in charge of analysis can be performed.
For example, by calculating an idle ratio of a selected sewing machine group (sewing machines/whole plant/production line), judgment of good/not good regarding the following is made, and an abnormality can be informed.
First, by comparing idle ratios of production lines processing the same item, a problem can be discovered, and a measure for improving the productivity can be taken.
The idle ratio of a production line can be indicated in a time-oriented manner and transition thereof can be observed, so that effects of an improvement can be confirmed.
In the present embodiment, a limited case where one process is assigned to one sewing machine is described, however, the present invention is also applicable to a case where a plurality of processes with different works and different sewing quantities are assigned to one sewing machine.
Specifically, among sewing record data of the same process, the number of stitches is the same because the same product is sewn. By utilizing this, first, pitch time data are classified by the number of stitches, and thereafter, regular work times can be determined by the method of the present embodiment.

(Second Embodiment)

In the first embodiment, all work times of an operator are collected, and automatically classified into "regular work times" necessary for processing products and other "irregular work times" from the tendency of the work time data, and an "idle ratio" as a ratio of the irregular work times to the regular work times can be calculated.
The second embodiment is an example of variation analysis of pitch times of regular work times.
Fig. 15 is a block diagram showing a configuration of a sewing machine work analyzing device 200 according to the second embodiment of the present invention. In the description of the present embodiment, the same components as in Fig. 3 are indicated by the same reference numerals and descriptions thereof will be omitted.
As shown in Fig. 15, the sewing machine work analyzing device 200 includes a pitch time gauge 110, a variation analyzer 220, a pitch time frequency distribution calculator 120, a work time classifier 130, an idle ratio calculator 140, and an output section 150.
The variation analyzer 220 analyzes variations in pitch times of regular work times. In detail, the variation analyzer 220 analyzes variations in pitch time of regular work times among operators or lines from a plurality of pitch time data obtained from the pitch time gauge 110.
Hereinafter, operations of the sewing machine work analyzing device 200 configured as described above will be described.
Fig. 16 is a diagram showing sewing operation times in regular work times.
First, the sewing machine work analyzing device 200 measures pitch times by the pitch time gauge 110. Then, as in the first embodiment, the sewing machine work analyzing device 200 automatically classifies the pitch times into "regular work times" and other "irregular work times."
Based on pitch time data classified into regular work times transmitted from the work data classifier 130, the variation analyzer 220 calculates variations in the pitch times of the regular work times. In detail, calculation is performed according to the following equation (6) by using the shortest pitch time which is the shortest among the pitch times of the regular work times, a total regular work time, and a total number of workpieces. $Total regular work times - (shortest pitch time \times total number of workpieces) / irregular work times = deviation of regular work time$
Other than the equation (6), there are calculation methods for calculating an index showing the degree of variation by using a standard deviation and an interquartile range.
Similarly, variation analysis of pitch times of regular work times of the whole line is also possible.
Fig. 18 is a diagram graphically showing calculated variations in pitch times of regular work times among operators by showing the operators on the horizontal axis. In Fig. 18, an average of the whole line is also calculated and indicated.
Fig. 19 is a diagram graphically showing transition of the average of Fig. 18 of variations in sewing operation time among operators with elapse of time by showing the time on the horizontal axis.
Fig. 20 is a diagram showing a graph comparing average variations among lines when a plurality of lines exist.
For calculation of variations, various methods can be used other than the equation (6) above. Hereinafter, an example using a standard deviation and an example using an interquartile range will be described.
Various factors lower the efficiency of the sewing work, and among these, main factors that cause variation in sewing operation time are (1) negligence of an operator during the work and (2) unstable naps and bends of the material and difficulty in the sewing work. Specifically, when a variation occurs, if the material is stable, the variation may be caused by negligence of an operator.
According to the present embodiment, the sewing machine work analyzing device 200 includes the variation analyzer 220 that measures pitch times and analyzes variations in pitch time of regular work times among operators or lines from the pitch times of a plurality of regular work times, so that the following effects are obtained.

(1) By knowing variations in sewing operation time of operators, it can be specified whether the factor that lowers the work efficiency is attributed to an operator or a material.
(2) By knowing variations in sewing operation time of operators, work unevenness can be grasped as data.
(3) By calculating and indicating a line average of variations in sewing operation time of operators, an operator can grasp his/her level in the whole.
(4) By indicating the calculated variations in sewing operation time of operators side by side, a person in charge of management can compare and evaluate the operators.
(5) Transitions of variations in sewing operation time of operators can be observed, so that changes before and after an improvement measure are taken and improvement effects can be confirmed.

(Third Embodiment)

In the first embodiment, "regular work times," "irregular work times," and "idle ratios" are automatically classified. In the second embodiment, analysis of variations in sewing operation time in the "regular work times" is described.
In the third embodiment, a sewing machine work analyzing device that grasps the tendency of occurrence of "irregular work times" will be described.
Basic configuration and operation of the sewing machine work analyzing device in the third embodiment of the present invention are the same as in the first embodiment.
The sewing machine work analyzing device in the present embodiment graphically indicates irregular work times automatically classified from work data measured in one or a plurality of sewing machines in a production line consisting of the one or a plurality of sewing machines by using pitch times of the irregular work times and sums of the irregular work times. Then, by indicating a graph analyzing in greater detail the above-described graph indication, a person in charge of plant management or the like is informed of an abnormal point. The person in charge of plant management or the like grasps the tendency of occurrence of irregular work times and an operator who causes the productivity to lower, and can lead to an improvement activity for improving the productivity.

[Graph indication of pitch times and sums of irregular work times]

Fig. 21 is a diagram showing irregular work time frequency distributions of the sewing machine work analyzing device.
As described above, a work time necessary for an operator to perform processing of one process is referred to as a pitch time.
The sewing machine work analyzing device according to the present embodiment creates pitch time frequency distributions from work data measured by sewing machines 1, 2... N (refer to Fig. 2) and performs classification into regular work times and irregular work times in the same manner as in the first embodiment.
As shown in Fig. 21, the sewing machine work analyzing device according to the present embodiment creates frequency distributions of pitch times belonging to irregular work times by excluding data extracted as regular work times from the created pitch time frequency distributions.
Fig. 22 is a diagram showing sums of irregular work times of the sewing machine work analyzing device.
In order to grasp the tendency of occurrence of irregular work times from the graph of Fig. 22, sums (sec) of irregular work times shown in Fig. 22 are indicated graphically. The sums (sec) of the irregular work times are expressed by the following equation (7). $Sum (\sec) of irregular work times = irregular work time \times the number of times of occurrence$
As shown in Fig. 22, pitch times of irregular work times and sums of the irregular work times are graphically indicated. From the graph of Fig. 22, it can be grasped which irregular work time unit occupies much time and has influence.
For example, as shown in Fig. 22, when a sum of irregular work times (sec) is indicated for each irregular work time (sec), tendency of occurrence of the irregular work times appears. Here, three irregular work time distributions appear. It is presumed that these irregular work times are caused by different factors. Concerning the irregular work times of 13 to 15 (sec) enclosed by the dashed line in Fig. 22, the irregular work time of 14 (sec) influences the irregular work times. Therefore, the irregular work times of 13 to 15 (sec) enclosed by the dashed line in Fig. 22 are selected as a selected range, and are further analyzed.

[Operator analysis]

Fig. 23 is a diagram showing sums of operator-specific irregular work times.
A person in charge of plant management or the like selects a data range to be analyzed in detail from the graph of Fig. 22 (refer to the dashed line in Fig. 22).
A person in charge of plant management or the like selects the data range and changes the item on the horizontal axis to operator. Then, as shown in Fig. 23, the sewing machine work analyzing device according to the present embodiment indicates an operator-specific graph of sums of irregular work times selected by the person in charge of plant management or the like. The person in charge of plant management or the like can grasp which operator significantly influences the irregular work times by operator-specific graph indication by the sewing machine work analyzing device according to the present embodiment.
For example, by operator-specific graph indication by the sewing machine work analyzing device according to the present embodiment, the person in charge of plant management or the like can know the following.

(1) A specific operator occupies much of the irregular work times.
(2) Irregular work times of all operators occur uniformly.

From the results described above, the person in charge of plant management or the like can perform an activity for improving a specific operator or all operators belonging to the production line. When much irregular work times are often detected, it is presumed that there is room for improvement, and this result can be utilized for an improvement of operators.

[Time analysis]

Fig. 24 is a diagram showing sums of hourly irregular work times.
The person in charge of plant management or the like selects a data range to be analyzed in detail from the graph of Fig. 22 (refer to the dashed line in Fig. 22).
The person in charge of plant management or the like selects a data range and changes the item on the horizontal axis to time. Then, as shown in Fig. 24, the sewing machine work analyzing device of the present embodiment graphically indicates sums of hourly selected irregular work times. The person in charge of plant management or the like can grasp which time slots the irregular work times are concentrated in by hourly graph indication by the sewing machine work analyzing device according to the present embodiment.
For example, by hourly graph indication by the sewing machine work analyzing device according to the present embodiment, the person in charge of plant management or the like can know the following.

(1) Irregular work times are concentrated in time slots sandwiching a break.
(2) Irregular work times are concentrated in a time slot in which parts arrive.
(3) Irregular work times are concentrated in a time slot in which operator fatigue accumulates in the evening.

From the results described above, the person in charge of plant management or the like can perform an improvement activity for the time slots in which irregular work times are concentrated.

[Operator analysis and time analysis]

The person in charge of plant management or the like performs operator analysis and time analysis from the graph of the irregular work time units and sums of irregular work times of Fig. 22. In addition, the person in charge of plant management or the like can select a certain operator and perform time analysis of sums of irregular work times of the operator from the graph of operator analysis of Fig. 23. Further, the person in charge of plant management or the like can select a certain time slot and perform operator analysis of a sum of irregular work times in the time slot.

[Operator-specific idle ratios]

Fig. 25 is a diagram showing operator-specific idle ratios.
The sewing machine work analyzing device according to the present embodiment automatically classifies work data measured in a production line consisting of a plurality of sewing machines 1, 2... N into regular work times and irregular work times. The sewing machine work analyzing device according to the present embodiment further classifies the classified irregular work times by operator, and calculates idle ratios.
As shown in Fig. 25, the sewing machine work analyzing device according to the present embodiment creates an operator-specific graph of the calculated idle ratios. The person in charge of plant management or the like can grasp which operator is idle from the graph of Fig. 25.

[Analysis of irregular work times]

Fig. 26 is a diagram showing sums of irregular work times of a selected operator (J).
The person in charge of plant management or the like selects an operator he or she desires to analyze in detail from the operator-specific graph of idle ratios of Fig. 25 (refer to the circled portion in Fig. 25).
The sewing machine work analyzing device according to the present embodiment creates a graph of irregular work time units and sums of the irregular work times of the selected operator (J).
The person in charge of plant management or the like can grasp which irregular work time unit occupies much time of the selected operator (J) from the graph of Fig. 26.
Further, the person in charge of plant management or the like can grasp the tendency of occurrence of the irregular work times by selecting a data range that the person in charge of plant management or the like desires to analyze in detail and performing operator analysis and time analysis.
In the sewing machine work analyzing device in the present embodiment, the analysis result output section 150 (Fig. 3 described above) outputs sums of irregular work times in irregular work time units. For example, by graph indication of sums of irregular work times with respect to one irregular work time, the person in charge of plant management or the like can grasp the tendency of occurrence of irregular work times.
Further, with the sewing machine work analyzing device in the present embodiment, an operator who needs improvement can be clarified by performing operator analysis by the person in charge of plant management or the like. This can lead to an improvement in productivity.
Similarly, with the sewing machine work analyzing device in the present embodiment, the person in charge of plant management or the like can grasp time slots in which irregular work times are concentrated and the tendency of occurrence by performing time analysis. This can lead to an improvement in productivity.
Further, the sewing machine work analyzing device in the present embodiment graphically indicates operator-specific idle ratios. The person in charge of plant management or the like can clarify an operator who needs improvement, and can grasp the tendency of occurrence of irregular work times by analyzing the irregular work times of the operator.
The description given above exemplifies preferred embodiments of the present invention, and the scope of the present invention is not limited thereto.
In the embodiments described above, a mode in which pitch times, numbers of times of turning, turning times, reserve times, and average numbers of rotations of the sewing machines are compared among operators, however, any one or more of these may be used. For example, the sewing machine work analyzing device may analyze only the pitch times, the numbers of times of turning, and reserve times.
In the embodiments described above, the title "a sewing machine work analyzing device and a sewing machine work analysis method" is used, however, this is used for convenience of description, and the device may be a sewing machine production management device or a sewing line diagnostic system, and the method may be a sewing work analysis method or the like.
Further, the components of the sewing machine work analyzing device, for example, the kind of the analyzing device, the method for data transmission to and data receiving from sewing machines, and the number of sewing machines to be managed are not limited to those of the embodiments described above.
For example, a sewing machine work analyzing system may have the following configuration.
Figs. 27A and 27B and Figs. 28A and 28B are views showing the entire configuration of a work analyzing system of the present invention.
As shown in Figs. 27A and 27B, the sewing machine work analyzing system includes a plurality of sewing machines 11, 12... N, and a sewing machine work analyzing device 200 that collects and analyzes information of the sewing machines 11, 12... N.
Each of the sewing machines 11, 12... N includes a transmission and receiving section (not shown) that transmits sewing operation time data to the sewing machine work analyzing device 200 as a host, and receives analysis data, etc., from the sewing machine work analyzing device 200, and an operation panel 20 (refer to Fig. 27A) capable of displaying data.
The sewing machine work analyzing device 200 as a host collects sewing operation time data from the sewing machines 11, 12... N as clients, and analyzes variations in sewing operation time and creates a graph thereof. The analysis method is the same as described in the first and second embodiments.
The sewing machine work analyzing device 200 transmits analyzed and calculated data of variations in sewing operation time or a variation average of the whole line to the sewing machines 11, 12... N.
The sewing machines 11, 12... N receive the data from the sewing machine work analyzing device 200 and display the data on the operation panels 20.
As shown in Figs. 28A and 28B, each of the sewing machines 11, 12... N includes an I/O section (not shown) which an external memory 30 such as a USB memory can be inserted into and removed from. The sewing machines 11, 12... N output data such as sewing operation time data, etc., to the external memory 30.
The sewing machine work analyzing device 200 collects sewing operation time data from the sewing machines 11, 12... N by using the external memory 30 (refer to Fig. 28A), and analyzes variations in sewing operation time and creates a graph thereof (refer to Fig. 28B).

[Industrial Applicability]

The sewing machine work analyzing device and the sewing machine work analysis method according to the present invention are useful as a work analyzing device and a production management method for industrial sewing machines.

Claims

A sewing machine work analyzing device (100; 200) comprising:
a pitch time measuring means (110) for measuring a pitch time,

a pitch time frequency distribution calculating means (120) for calculating a pitch time frequency distribution based on the measured pitch time, and an output means,

characterized by a work time classifying means (130) for classifying a work time into a regular work time necessary for processing products and an irregular work time based on the calculated pitch time frequency distribution, and

the output means (150) is designed for outputting the classified regular work time and irregular work time in an identifiable manner.
The device according to Claim 1, wherein the work time classifying means (130) is designed for calculating a total irregular work time which is a sum of the irregular work time by subtracting a total regular work time which is a sum of the regular work time from a total work time of an operator.
The device according to Claim 1, wherein the pitch time measuring means (110) is designed for performing a measurement by using an operation-start signal, an operation-stop signal and a thread-cutting signal of a sewing machine.
The device according to Claim 1, further comprising:
an idle ratio calculating means (140) for calculating an idle ratio from a ratio of the total irregular work time to the total regular work time.
The device according to Claim 4, wherein the idle ratio calculating means (140) for calculating an idle ratio from a ratio of the total irregular work time to the total regular work time is formed by an idle ratio calculator (140).
The device according to Claim 4 or 5, wherein the output means (150) is designed for outputting the classified total regular work time and total irregular work time and/or the idle ratio in an identifiable manner.
The device according to Claim 1, wherein the output means (150) is designed for outputtting a ratio of the classified total regular work time to a total work time of an operator or a ratio of the classified total regular work time to a total irregular work time.
The device according to Claim 4, wherein the output means (150) is designed for comparing idle ratios calculated from one or a plurality of sewing machines, and for outputting a comparison result of the idle ratios as a work analysis result.
The device according to Claim 1, further comprising:
a variation analyzing means (220) for analyzing variations in a pitch time of a regular work of an operator from a plurality of measured pitch time data.
The device according to Claim 9, wherein the variation analyzing means (220) for analyzing variations in a pitch time of a regular work of an operator from a plurality of measured pitch time data is formed by a variation analyzer (220).
The device according to any one of Claim 1 to 10, characterized in that the pitch time measuring means (110) for measuring a pitch time is formed by a pitch time gauge (110).
The device according to any one of Claim 1 to 11, characterized in that the pitch time frequency distribution calculating means (120) for calculating a pitch time frequency distribution based on the measured pitch time is formed by a pitch time frequency distribution calculator (120).
The device according to any one of Claim 1 to 12, characterized in that the work time classifying means (130) for classifying a work time into a regular work time and an irregular work time based on the calculated pitch time frequency distribution is formed by a work time classifier (130).
The device according to any one of Claim 1 to 13, characterized in that the output means (150) is designed for outputting the classified regular work time and irregular work time in an identifiable manner comprise a display/ printing section for displaying/printing analysis results.
A sewing machine work analysis method comprising:
measuring a pitch time;

calculating a pitch time frequency distribution based on the measured pitch time;
characterized by
classifying a work time into a regular work time and an irregular work time based on the calculated pitch time frequency distribution; and

outputting the classified regular work time and irregular work time in an identifiable manner.