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  MYMS  

Woven fabrics used in the papermaking industry require yarns that are defect free and have carefully controlled diameters.   The MYMS is a specially designed system used for high resolution in-line measurement of yarn properties and defects. The system has been applied to the measurement of monofilament yarn diameter with a precision of 2.5 microns and “slub” detection on 60 ends traveling at line speeds of up to 600 feet per minute.

 

Operating Principle

The MYMS system uses high precision laser gauges to measure yarn diameter and to detect "slubs" (small thickness variations).  The detectors used in the MYMS work on a shadow principle as illustrated in the Figure below  A thin, collimated, line of light (infrared portion of the light spectrum) from a laser diode is projected onto a detector.  The light intensity is measure by a photo detector which is specifically designed to measure the light in the emitter's frequency band.

When there is no object blocking the light, the detector outputs its maximum voltage. If a yarn is present then the shadowing of the detector results in a reduction in the output voltage.  This reduction is, within certain limits, directly proportional to the yarn diameter.   The MYMS uses 60 laser detectors in combination with a high speed data acquisition system to detect "slubs" and continuously monitor the yarn diameter of all 60 ends.

 

MYMS System Overview

Sixty high resolution laser micrometers with precision of better than 2.5 microns (.0001”) are used to measure each yarn.  High speed, multi-channel data acquisition methods are used to sample each detector at a rate of 6000 times per second.  This yields a machine direction resolution of  .02” for the raw sampled data. For a typical 25,000-yard spool this amounts to over 3,750,000 individual measurements. (22,500,000 measurements for a 60 end doff). 

The MYMS is intended to be primarily a “slub” detector.  As such it is optimized to look for rare short-term fluctuations in the yarn diameter.  These types of variations will not be detected using conventional statistical process control methods. 

System software has been developed to measure and store the average, minimum, and maximum diameters for each of the 60 spools.  This system is also designed to capture high-resolution data “events”  whenever the yarn exceeds customer specifications.  This data can be viewed by the operator in real-time and also is archived for post processing.

The graphical user interface has been designed so that it can be easily configured and calibrated.  Once configured the system is designed to run continuously.  A Completion Sequence database and software allows the user to easily relate end position to the order of spool completion.  All yarn products, along with the appropriate specification limits, are part of a comprehensive product database.  The user simply has to select the product from a drop-down menu and inspection limits are automatically downloaded to the system.  All configuration and data display is accessible from a single monitor window. 

At run-time the display allows the user to obtain numerical values for the yarn diameter for each end (see Figure2).  Other statistics, such as minimum value, maximum value and standard deviation in yarn diameter, are also available.  The system automatically compares the measured values with specification limits.  Whenever the yarn diameter exceeds the specification limits, the “event” is recorded.  The run-time display shows a count of the number of “events” for each spool.  The user has the ability to individually visualize each of those events and their location.

The MYMS has powerful data archiving and visualization software.  Data can either be visualized at run-time or looked at off-line.  Data visualization includes radar plots, bar charts, and tabular display for the multi-end data.  For each spool, individual events above threshold, diameter vs. distance, and histograms can be visualized.  Provisions are also made for calculating and viewing conventional QC statistical data such as X-bar and R-bar charts for each end and calculating statistical measures of the process.

 
 

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