Patent Publication Number: US-5841675-A

Title: Method and apparatus for monitoring quality of electrical wire connections

Description:
BACKGROUND OF THE INVENTION 
     This application relates to an improved method and apparatus for monitoring the quality of connections made by an electrical wire crimping machine. 
     In the prior art, crimping machines are utilized to attach electrical connectors to electrical wires. Essentially, a machine deforms or &#34;crimps&#34; a connector member onto an electrical wire. Complicated monitoring systems are utilized to monitor and assure the quality of each crimp. In general, the force experienced by the crimping machine when crimping the connector to the wire is captured and studied to determine whether the crimp would appear to be acceptable. As one example, if there are too few wire strands in the wire, than the force of the particular crimp would differ from that which is expected. If the force differs from the expected force by more than a predetermined amount then a determination is made that the particular connection is defective. In general, the prior art has looked at the entire force curve and compared it to desired force curves. If the actual force curve differs from the desired force curve by a predetermined amount, then the determination is made that the particular connection is defective. 
     In a second type of known monitoring, the system develops characteristics of the force curve and compares those characteristics to expected characteristics. In one successful system, the monitoring system captures the peak of the force curve, the area beneath the force curve, and also a &#34;peak factor&#34;. The peak factor is the area divided by the peak. By comparing these three characteristics to desired characteristics, a determination can be made whether a particular crimp is acceptable. If the particular force characteristics of a connection extend outside of preset boundaries then the determination is made that the connection is defective. 
     The prior art has set both outer and inner boundaries as a preset percentage of the mean of each characteristic. An operator is provided with the ability to adjust the preselected percentage. The outer boundaries are utilized to identify a &#34;gross&#34; or drastic problem with the system. When the force characteristic crosses the outer boundary, it is likely that there has been a jam or other misalignment within the crimping tool. Thus, a determination that a force characteristic has crossed this boundary may be associated with a shut down of the machine. An inner or &#34;fuzzy&#34; boundary is set to identify a connection which is proper. If a force characteristic of a particular connection crosses this boundary then the determination is made the particular connection is likely defective for some reason. However, it may not be necessary that the system be shut down when this inner or &#34;fuzzy&#34; boundary is crossed. 
     There are some deficiencies with this prior art system. One main problem, is that the boundaries are preset and subjective. They are not based on the variables for the particular machine. While this system is often still acceptable, it would be desirable to have the boundaries be associated more closely with the type wire or connection being performed, and also the particular machine that is being utilized. As an example, with different size wires or different type of connectors, the necessary boundaries to achieve an acceptable connection may change. With the prior art preset method it has been difficult to adjust the boundaries as necessary for the particular wire, connector, machinery system, etc. In addition, a particular crimping machine may be associated with other machinery in such a way that the forces or other stresses and strains on the system may vary the force curve. Thus, to some extent, each machine has individual acceptable boundaries. 
     With this type of system it is likely that the boundaries are often not set at optimum levels. If the boundaries are too &#34;tight,&#34; then there is an unnecessary high percentage of scrap. This is, of course, undesirable. On the other hand, if the boundaries are set too &#34;loose,&#34; then there may be defective connections which are not identified. This is also undesirable. 
     For the reasons set forth above the prior art method of presetting the boundaries is somewhat deficient. 
     SUMMARY OF THE INVENTION 
     In the disclosed embodiment of this invention, the boundaries for the peak, area and peak factor characteristics of a crimp monitoring tool are set based on learned samples for the particular machine, wire and connector. In one disclosed embodiment, a number of samples are ran with the monitor in a learning mode. The monitor captures the peak, area and peak factor for those samples. If any of the samples differ markedly from the other samples, then at least the particular different sample is not utilized. In one example, if any of the three characteristics differ by more than 2% from the prior sample then the system begins again to try and run consecutive samples that are each within 2% of each other. Once the system has ran a set number of samples (in one example 5) that are within the tolerance range, than the outer or &#34;gross&#34; boundaries are set based upon the sample characteristics. 
     In particular, the system sets the boundaries by determining the standard deviation for each of the characteristics and then spaces the boundaries from the mean by the standard deviation times a factor. In one example, the system utilizes five times the standard deviation to set the outer boundaries away from the mean for each of the three characteristics. 
     A number of other learn samples are then ran (in one example 64). Once this greater number of samples have been ran, the system again determines the mean and the standard deviation for each of the characteristics. The inner or &#34;fuzzy&#34; boundaries are also set. In one example, the fuzzy characteristics are set to be three standard deviations away from the mean. Once these boundaries are set, the system can proceed with routine or production crimping of connectors to the wires. If a particular part exceeds the gross limit, then the system preferably shuts the machine down such than an operator can determine why the outer limit has been exceeded. On the other hand, if the inner or &#34;fuzzy&#34; limit is exceeded then an indication is made that the particular connection should be discarded, or at least studied to determine whether it is acceptable. 
     Once the system begins to run production parts (i.e., after the fuzzy boundaries have been set) the mean is continuously recalculated. In one example, every five consecutive acceptable parts are utilized to recalculate the mean. This is desirable as conditions for the system will change as the machine runs. As an example, as the machine runs, the temperature of the machine will change. This will change the resulting force characteristics. By continuously recalculating the mean, the present invention is sure to accommodate those changes. The original preset inner and outer boundaries are preferably not recalculated. 
     In addition, in the event the machine is shut down for a predetermined period of time, the temperature change could cause slight variations to the process that could result in unnecessary scrap. For this reason, the monitor is preferably provided with a timer which can sense an idle time for the machine. In the event the idle time exceeds the predetermined time period, then the fuzzy limits are turned off. The fuzzy limits are then recalculated by taking a new set of samples once the machine is restarted. Those new samples are then utilized to recalculate the mean, and the standard deviation to reset the fuzzy limits and the outer limits. 
     The present invention also preferably displays the CPK for the system each time the fuzzy limits are recalculated. In the present invention, the CPK is calculated by selecting a small amount of force (in one example 50 pounds) and dividing that amount by three times the standard deviation. In this way, a relative value of the CPK for each relearned set of fuzzy limits is displayed to the operator. 
     In other features of this invention, it is preferred that when the first initial samples are ran to set the outer limits, an operator be given the opportunity to study those samples. In initially setting the outer limits, there are not yet any inner or &#34;fuzzy&#34; limits. Thus, the operator may wish to study those initial samples to determine whether any of the parts are defective. If so, the operator may wish to rerun the samples to eliminate any influence from an improper part that would still be within the outer or &#34;gross&#34; limits. 
     An improved monitoring system and a method of utilizing the system is disclosed. The improved invention allows a system to be quickly set up to change the type of wire, connector, or machinery associated with the tool which is utilized. The invention also eliminates scrap and down time by insuring that any part which is indicated as being defective is in fact defective for the particular type of part being ran. 
     By utilizing the standard deviation, the system ties the boundaries directly to the type of deviation experienced for the particular arrangement of wire, connector and machinery. The use of the standard deviation allows one to preset objectively what is thought of as a defective part. In the absence of such an objective characteristic the operator is left to subjectively determine boundaries. The invention is particularly valuable in addressing individual characteristics of the particular connection and particular tooling. 
     These and other features can be best understood from the following specification and drawings, of which the following is a brief description. 
    
    
     BRIEF DESCRIPTION OF THE DRAWING 
     FIG. 1 is a schematic view of a tool according to the present invention. 
     FIG. 2 shows a force curve for a crimping machine. 
     FIG. 3 is a flow chart of the inventive method. 
    
    
     DETAILED DESCRIPTION OF PREFERRED EMBODIMENT 
     FIG. 1 shows a crimping tool 20 for crimping a connector 22 onto a wire 24. A monitoring system 26 monitors the force experienced by tool 20 when crimping connector 22 onto wire 24. It should be understood that FIG. 1 is very schematic and is only utilized to describe the broad outlines of the system. 
     As shown in FIG. 2, force curve 28 can be set for each of the cycles of connecting a connector 22 to a wire 24. By plotting the load versus time for each connection, a curve 28 is generated. 
     A load sensor, which may be a piezo-electric type sensor, is placed adjacent machine 20 and monitors the force. Known components digitize the signal from the sensor such that monitoring system 26 determines the peak P of the force curve 28 and the area of the force curve 28. That is, the area beneath the force curve between two preset points in time. Once area and peak are determined, the peak factor can be determined by dividing the area by the peak. Monitoring system 26 preferably includes a CPU with the necessary software to achieve the described functions. On the other hand, other types of controls could be used and would still be within the scope of this invention. 
     The invention will be explained with reference to the flow chart shown in FIG. 3. Again, it should be understood that the monitoring system 26 includes the appropriate software, controls, or other elements necessary to achieve the method steps set forth with reference to FIG. 3. 
     As shown in FIG. 3, when a new system is set up, the crimp height, the size of the connector, the number of wire strands in a wire, or even the arrangement of a particular tool and its associated machinery may be different from any other system. Thus, the present invention initially moves the monitoring system 26 into a learning mode. An appropriate control is preferably actuated to move monitoring system 26 into a learn mode. In the learn mode a predetermined number of consecutive samples are made by the tool 20. In one example, five samples are ran. The control determines the peak, area and peak factor for each of those samples. If all of the samples fall within a predetermined percentage range (i.e., 2%) then those five samples are found acceptable. If the samples extend out of the 2% range then the system begins again to attempt to run five consecutive samples within the range. At some point, the system may indicate an error if it is unable to achieve sufficient consecutive acceptable samples. 
     Once consecutive samples within the range have been captured, the monitoring system next determines the mean and the standard deviation within the five samples for peak, area and peak factor. The monitoring system then sets outer or primary control limits based on the standard deviation. In one example, the boundaries are set to be five standard deviations away from the mean. These outer boundaries are utilized to determine a gross or serious problem. 
     The control then moves into the second portion of the learn phase, where additional samples are taken. Once a particular number of samples which fall within the outer or primary control limits occur, (i.e., 64 samples) the control then recomputes the mean and the standard deviation. The outer or primary control limits are recomputed, again based on five times the standard deviation. A second set of tolerances or boundaries called the &#34;fuzzy&#34; or inner control limits are set at three times the standard deviation. At this point, the system has established both its inner and outer boundaries. Since the boundaries are based on statistical information from actual samples, the boundaries are not subjective, but instead are objective. Moreover, since the boundaries are based on standard deviation, they provide a very real feedback on how close the particular run part is to the average part, and also how close the particular part is to the average difference from a typical part compared to the mean. In this way, the system optimally sets the tolerances. This then minimizes scrap and process down time. 
     Preferably, as production runs occur, the mean is continuously recalculated based upon a preset number of prior acceptable parts. In one example, the five previous parts are utilized to continuously recalculate the mean. The standard deviation and the boundaries are not reset with this recalculation of the mean. This recalculation of the mean ensures that changes within the system, which may occur as the temperature of the system changes, are accommodated. 
     In other features of this invention, the monitor system 26 has a timer 27 which monitors whether it has a significant amount of down time. After a significant amount of down time there may be variation within the system. If the timer determines that a significant amount of down time has occurred, the system may move into reestablishing its boundaries. As an example, in such an event the system may eliminate the inner control boundaries and recalculate those boundaries based on the first 64 samples after start up. In one example, the predetermined period of time is 30 minutes. 
     By resetting the boundaries after this particular amount of down time, the monitoring system again is sure to provide real feedback on the particular characteristics at the time of the operation of the system. Such recalculation may not have been necessary with the prior art subjectively selected boundaries. However, it is desirable with the instant invention which bases the boundaries on the characteristics of the system. 
     The system may be easily tailored to particular conditions. As one example, following the initial setting of the outer or primary control limits, the system may provide the operator the opportunity to check the learn samples. If one sample is not acceptable, it may still be within a particular range (i.e, 2%) of the other parts, and yet it would be more desirable to set the boundaries without that defective part. If the operator determines that one of the samples is defective, then it may be desirable to rerun those initial samples. 
     In addition, the control can be tailored for the number of defective parts that may be identified to result in shut down of the system. As an example, it may be desirable that one primary failure will lead to shut down of the system. On the other hand, it may be desirable to only shut down the system based on a greater number of consecutive inner or fuzzy boundary crossings. 
     A preferred embodiment of this invention has been disclosed, however, a worker of ordinary skill in the art would recognize that certain modifications would come within the scope of this invention. For that reason, the following claims should be studied to determine the true scope and content of this invention.