JPH0790733A - Control system for spinning machine - Google Patents

Abstract

PURPOSE:To provide a spinning machine control system capable of discriminating the spindle defect from ending apparatus defect. CONSTITUTION:This control system for a spinning machine is provided with an ending apparatus moving among a number of spinning spindles and performing the ending service. The control system detects the ending failure of each spindle and takes the statistics of the detection frequency. When a deviation is found between the ending failure frequencies in the spindles, it is judged that the defect is present on the spindles and when the ending failure frequency is high over the whole spindles, the ending apparatus is estimated to be defective.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a spinning machine management system for estimating a defect in a weight and a yarn splicing device from a statistic of a yarn splicing failure, and particularly distinguishes a defect in a spindle from a defect in the yarn splicing device. The present invention relates to a spinning machine management system that can be used.

[0002]

2. Description of the Related Art As shown in FIG. 9, a spinning machine 71 has a large number of weights (spinning units) 72 for spinning on one machine base.
Is equipped with. For each weight 72, a draft device 73 for supplying a draft sliver, a jet spinning type nozzle 74 for spinning the draft sliver as a yarn, a winding device 75 for winding the spun yarn into a package, and A yarn clearer 76 for detecting a yarn defect and removing the yarn defect is provided between the nozzle and the winding device. The weights 72 are arranged in a line. One yarn splicing device 77 including a knotter and a splicer for splicing yarns is provided for each machine, and can be loaded on a carriage to move between the weights along the row of weights 72. When the yarn clearer cuts the yarn when removing the yarn defect, or when the yarn is broken due to other causes, the yarn joining device 7
7 stops at the dead weight of the thread to perform the piecing service.

The spinning machine 71 is provided with a monitoring device 78 for monitoring various operations of the weights 72 and the yarn joining device 77 in the machine base. Further, in a spinning equipment management system including a large number of spinning machines 71, a centralized management device for centrally managing the entire machine stand may be provided. A personal computer or the like is used as the central control device.

The yarn joining device 77 carries out (tries) yarn joining.
At this time, splicing may fail due to various causes.
The monitoring device 78 constantly monitors, as one of the various operations described above, whether the splicing is successful or unsuccessful. Specifically, for each weight,
The number of trials and the number of failures (or the number of successes) can be counted for each machine, and the statistics can be obtained. Centralized control device is also each monitoring device 7
Collect statistical data from 8 and manage the spinning equipment as a whole. In the conventional management system, the failure rate obtained by dividing the number of failures by the number of trials is used as the statistic. The management content is to presume that some failure has occurred in the machine with a high failure rate, notify the operator of this, and prompt the improvement.

A defect estimation method in the conventional management system will be described using the statistical contents according to the embodiment of the present invention shown in FIG.

The upper and lower two bar graphs in FIG. 2 show statistical data for 30 machines. In the above graph, the horizontal axis represents the machine number and the vertical axis represents the number of failures per unit for each machine. In the lower graph, the horizontal axis represents the machine number, and the vertical axis represents the failure rate for each machine (the average failure rate within the measurement period of all spindles in each machine, for example, within the shift). However, since the machine numbers are given in random numbers, there are No. 74, No. 79, etc. The numbers of various statistical data are shown on the right side of FIG.

The average failure rate of the entire machine is [MI
It is 13.6% as shown in the Miss term in the [LL] column. However, looking at the graph below, we can see that some machines have high failure rates and some machines have low failure rates. For example, in the No. 79 machine where the cursor 21 is located, the failure rate is 2 as shown in the Miss section of the [MACHINE] column beside the graph.
It is 2.8%, and it can be seen from the graph below that the failure rate of Unit 79 is higher than the others. The operator sees this graph and the statistical data and knows that some defect has occurred in the No. 79 machine, and can look around the No. 79 machine to find the cause of the defect and perform repairs.

[0008]

By the way, there are two causes of yarn splicing failure due to defective weight 72 and defective yarn splicing device 77. In the conventional management system described above, it can be seen that some defect has occurred in the machine base. However, the defective machine base is the defective weight 72 or the yarn splicing device 77.
It was unclear whether it was bad. Empirically, when the failure rate of the machine exceeds a predetermined value (for example, 20%), the yarn joining device 77 is estimated to be defective, but this estimation is not always correct. For this reason, it is troublesome and time-consuming for the operator to find the cause of the defect, which is a factor of reducing the operating efficiency of the spinning machine.

Therefore, an object of the present invention is to solve the above problems and provide a spinning machine management system capable of distinguishing between a defective weight and a defective yarn splicing device.

[0010]

In order to achieve the above object, the present invention provides a spinning machine management system provided with a large number of spindles for spinning and a yarn splicing device for moving the yarns to perform a yarn splicing service. In the above, the yarn splicing failure in each weight is detected, and the number of times of detection is statistically estimated.If the number of yarn splicing failure in each weight is uneven, the weight is estimated to be defective, and the yarn splicing failure rate is When the value is high, it indicates that the yarn joining device is defective.

[0011]

Function: There are many weights in one machine, but one yarn splicing device. If the weight is defective, many splice failures will occur at that weight. When the number of detections is statistic, the number of failure of yarn splicing in a specific weight increases and the failure rate of yarn splicing in the specific weight increases. On the other hand, if the yarn joining device is defective, it is considered that yarn joining failures will occur at any weight, and the yarn joining failures will increase as a whole. When the number of detections is statistic, the number of failure of yarn splicing in all spindles increases and the rate of failure of yarn splicing in all spindles increases. Therefore, it is considered that the defective weight or the defective yarn splicing device can be distinguished by checking the number of failed yarn splices or the failed yarn splicing rate for each weight and checking the number of failed splicing or the yarn splicing failure rate for all the weights. .

[0012] However, if a thread splice failure happens to occur in a weight that has few yarn breakages and therefore has a small number of thread splice attempts, the splicing failure rate increases even if the number of thread splice failures of the weight is small. In fact, a normal weight causes less thread breakage. If the yarn splicing failure happens to occur with a normal weight, the number of trials is small and the yarn splicing failure rate becomes abnormally high. Since the number of trials does not increase much after that, the yarn splicing failure rate remains high. Therefore, if a defective weight is estimated from the yarn splicing failure rate, the normal weight may be mistaken for a defective weight. Therefore, the failure rate of yarn splicing for each weight is not suitable for estimating defectiveness of the weight.

On the other hand, since the number of failure times of yarn splicing always increases in a defective weight, the number of times of failure of yarn splicing for each weight can be used for estimation. However, even if the yarn splicing device is defective, the number of yarn splicing failures for each weight increases, and therefore the defect of the weight cannot be directly estimated from the number of yarn splicing failures for each weight. Therefore, in the present invention,
If the number of failed splices for each weight is uneven, it is estimated that the weight is defective. Specifically, this deviation is detected from the frequency distribution of the yarn splicing failure frequency or by comparison with the standard deviation. That is, it can be presumed that a weight having an extremely high frequency in the frequency distribution of the failure times of yarn splicing is a defective weight. Alternatively, the number of yarn splicing failures of each weight is statistically calculated to obtain a standard deviation for all the spindles, and a spindle having a number of yarn splicing failures larger than a predetermined multiple of this standard deviation can be estimated as a defective weight.

On the other hand, since the yarn splicing device splices all the weights, the number of trials as a yarn splicing device is large even if the number of trials with each individual weight is small, and it is sufficient to obtain reliable statistics. Is. For this statistic, the number of failures (total or average) of yarn splicing in all weights or the average failure rate of yarn splicing in all weights may be used. In particular, the average yarn splicing failure rate for all weights is not affected by the number of weights, which is preferable. As described above, it has been conventionally empirically estimated that the yarn splicing device is defective when the average yarn splicing failure rate in all the weights exceeds 20%. However, if the number of failures in splicing is abnormally large in a specific weight, the average failure rate of splicing in all the weights is pushed up by this specific weight even if the yarn splicing device is not defective. Therefore, the failure of the yarn splicing device cannot be estimated directly from the average yarn splicing failure rate for all the weights.

Therefore, in the present invention, when the yarn splicing failure rate is high over the entire weight, it is estimated that the yarn splicing device is defective. Whether the yarn splicing failure rate is high over all the weights can be determined from the average yarn splicing failure rate in all the spindles and the deviation in the number of yarn splicing failures for each spindle. That is, when the average yarn splicing failure rate for all spindles is high and the deviation in the number of yarn splicing failures for each spindle is small, the yarn splicing failure rate is high for all spindles. If the weight failure is already estimated due to a large deviation in the number of thread splicing failures among the weights, the defective thread is excluded and the average thread splicing failure rate of the remaining weights is calculated. Since the average yarn joining failure rate is high, it can be determined that the yarn joining failure rate is high over the entire weight.
Of course, when there is no defective weight, it is possible to immediately determine that the yarn splicing failure rate is high over the entire weight because the average yarn splicing failure rate for the entire weight is high.

[0016]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described in detail below with reference to the accompanying drawings.

As shown in FIG. 1, the spinning machine management system of the present invention comprises a large number of spinning machines (machines) 1, a centralized management device 2 for centrally managing these machines, and a communication line 3. Composed of. Each spinning machine 1 is the one described in FIG. 9, and includes a monitoring device 4 and 72 weights, respectively.
In the present embodiment, 30 spinning machines 1 are provided, of which No. 7 machine and No. 79 machine are included. The centralized management device 2 including a personal computer and a workstation can collect data from the monitoring device 4 of each machine through the communication line 3. The centralized management device 2 includes a display 5, a keyboard 6, a modem 7 for communicating with the outside, and the like. The contents displayed on the display unit 5 are collected data and processed data. For example, the operating status of each weight, short-term and long-term operation details, machine-specific loss efficiency analysis results, weight-specific efficiency frequency distribution, There is a wide variety of information such as thread breakage information by machine base.

In the above structure, the monitoring device 4 has a function related to the present invention to detect a yarn splicing failure at each weight and to count the number of detections. The number of times this detection is performed is a part of the collected data, and the central control device
Sent to. As a function related to the present invention, the centralized management device 2 statistically counts the number of times of detection, estimates the defect of the weight when the number of times of failure of yarn splicing for each weight is uneven, and determines the failure rate of yarn splicing over the entire weight. When it is high, it has a function of estimating the defect of the yarn joining device. The display contents of the display unit 5 related to the present invention include the failure frequency and failure rate for each machine, the failure frequency and failure rate for each spindle, the frequency distribution of failure frequency and the frequency distribution of failure rate, and the number of trials for each machine. And the number of successes, and the number of trials and successes for each weight. The display screens are shown in FIGS. The operator can switch the display screen by operating the keyboard 6 using the cursor or menu (or function) on each display screen.

Next, the operation of the embodiment will be described.

The display screen of FIG. 2 is displayed on the display unit 5. In the graph of Fig. 2, the average failure rate of 30 machines is 1
It was 3.6%, and it was already explained that the average failure rate of the whole weight of Unit 79 indicated by the cursor was 22.8%. Next, the data of each weight of Unit 79 is displayed on the display screen of FIG. Of the two upper and lower bar graphs in Figure 3, the upper graph is
The horizontal axis represents the weight number, and the vertical axis represents the number of failures per hour for each weight. In the lower graph, the horizontal axis represents the weight number, and the vertical axis represents the failure rate within the measurement period for each weight (40% or more is rounded down). Unit 79 has 72 weights.
On this display screen, the average failure rate of 22.8% for the weight as a whole is shown in the Miss section in the [AVERAGE] column beside the graph. Since the average failure rate of the whole weight exceeds 20%,
The conventional system corresponds to a defect in the yarn joining device. However, looking at the graph above, it can be seen that there are weights with an extremely high number of failures. For the 18th weight where the cursor is located, the number of failures is M in the [SPIDLE] column beside the graph.
As shown in the sknt term, it is 1.5 times / hour.
The failure rate of the 18th weight shown in the Miss item in the [SPIDLE] column is abnormally high at 81.8%, but many other weights have a high failure rate in the graph below. In this way, the failure rate may be high even for a spindle with a small number of failures, and the failure rate cannot be used for estimating a defective spindle.

Next, the display screen of FIG. 4 is displayed. Left and right 2
One graph is a frequency distribution graph of the number of failures of the weight in Unit 79, failure rate, the left graph is the number of failures on the horizontal axis,
The vertical axis represents the number of weights having the number of failures. In the graph on the right, the horizontal axis represents the failure rate and the vertical axis represents the number of weights having the failure rate. Further, next to the graph, the number of failures, the average value, the standard deviation, the coefficient and the allowable limit value, the number of defective weights, etc. are shown numerically for each failure rate. The broken line in each graph shows the allowable limit value. In this embodiment, the coefficient is set to 4, so the allowable limit value is four times the standard deviation.

In FIG. 4, as shown in the STD-dev term, the standard deviation of the number of failures and failure rate in the No. 79 machine is 0.20 times / hour, 20.41%. It can be seen from the graph on the left that there is one weight whose number of failures exceeds the allowable limit. That is, it is estimated that there is a defect in the weight, because the number of failed yarn splicing for each weight is uneven. Then, the weight exceeding the allowable limit is specified to be the 18th weight.

Whether or not the yarn splicing failure rate is high over the entire weight is determined by excluding the 18th weight. Here, on the display screen of FIG. 7, the number of trials (KNT column) and the number of successes (RU) for each machine are shown.
Column N) is shown. As shown in FIG. 7, 7
The total number of trials for Unit 9 is 386, and the number of successes is 298. In addition, the display screen of FIG. 8 shows the number of trials (KNT column) and the number of successes (R
UN column) is shown. The number of trials with the 18th weight is 22 and the number of successes is 4. 79 excluding 18th weight
When calculating the average failure rate of the units, {(386-22)-(298-4)} / (386-2
2) = 19.2%. As a result, since the average failure rate does not exceed 20%, it is estimated that the yarn joining device is not defective.

Next, returning to the display screen of FIG. 2, comparing the sizes of the bars in the bar graph at each machine stand, it can be seen that the No. 7 machine is similar to the No. 79 machine. Therefore, the cursor 21 is moved to the No. 7 machine to display the display screen of FIG. The display screen of FIG. 5 shows the statistical results for each weight of the No. 7 machine, like the display screen of FIG. Looking at the display screen in FIG. 5, yarn splicing failures are distributed to many weights in Unit 7, and there is no extreme weight. In the Miss section of the [AVERAGE] column, the average failure rate of the entire weight is 22.7%, which is 7
It is almost equal to Unit 9.

Next, the display screen of FIG. 6 is displayed. The display screen of FIG. 6 shows the statistical results of the weights in the No. 7 machine, like the display screen of FIG. As shown in the STD-dev section, the standard deviation of the number of failures in Unit 7 is 0.17 times / hour. As shown in the Preset term, the tolerance limit is 0.8 times / hour. From the graph on the left, it can be seen that there is no weight whose number of failures exceeds the allowable limit.
That is, since there is no bias in the number of failed yarn splicing for each weight, it is estimated that there is no defect in the weight. Then, since the average failure rate of the whole weight exceeds 20%, it is judged that the yarn joining failure rate is high over the entire weight, and it is estimated that the yarn joining device is defective.

In the above embodiment, the case where the yarn splicing device is normal with only one defective weight and the case where the yarn splicing device has no defective weight and the yarn splicing device is defective have been described. It is needless to say that it is also effective when the defect of the yarn splicing device overlaps the defect of 1.

[0027]

The present invention exhibits the following excellent effects.

(1) Since the defective weight and the defective yarn splicing device can be distinguished from each other, the operator can immediately start the repair work, and it is possible to prevent the operating efficiency of the spinning machine from lowering.

[Brief description of drawings]

FIG. 1 is a block diagram of a management system for a spinning machine according to the present invention.

FIG. 2 is a display screen diagram showing an example of a display screen according to the present invention.

FIG. 3 is a display screen diagram showing an example of a display screen according to the present invention.

FIG. 4 is a display screen diagram showing an example of a display screen according to the present invention.

FIG. 5 is a display screen diagram showing an example of a display screen according to the present invention.

FIG. 6 is a display screen diagram showing an example of a display screen according to the present invention.

FIG. 7 is a display screen diagram showing an example of a display screen according to the present invention.

FIG. 8 is a display screen diagram showing an example of a display screen according to the present invention.

FIG. 9 is a side view of the spinning machine.

[Explanation of symbols] 1, 71 spinning machine 2 centralized control device 3 communication line 4, 77 monitoring device 5 indicator 72 weight (spinning unit)

Claims (1)

[Claims] 1. A spinning machine management system comprising a large number of spinning spindles and a yarn splicing device that moves between the spindles to perform a yarn splicing service, and detects a yarn splicing failure at each spindle and its detection. It is characterized in that the number of times is statistically estimated, and if there is a deviation in the number of yarn splicing failures for each weight, a defect in the weight is estimated, and if the yarn splicing failure rate is high over the entire weight, a defect in the yarn splicing device is estimated. Spinning machine management system.