Scientifically calculating connector life and reducing test costs

    Because of the fierce market competition in the connector industry, connector manufacturers are also asking designers to find suitable materials in a variety of production materials to reduce the production costs of connector manufacturers. In the case of these requirements, the combined result of these trends makes the copper alloy material of the connector, etc., closer to its performance limit in the operating characteristics.
    Initial contact force is an important factor in connector design and material properties. If the contact force of the connector is below a certain critical level, the contact will fail, because in the contact, the elastic deformation will change into plastic deformation, so the stress release will cause the contact force to decrease. Therefore, predicting stress release as a function of time and temperature correlation is naturally a key factor in ensuring connector reliability.
    Stress-releasing data is an effective tool for designers to predict the life of an electronic connector, making decisions about the contact material of the connector based on available data. These data technologies are now widely used in the computer, communications and automotive electronics industries. Because the current data on the life cycle of the product is very scarce, especially in the field of computers. Not only that, but the technology is a powerful data that shortens product development cycles and expiration dates.
    Most connector designers now use stress-releasing data primarily to reduce the choice of contact material depending on the application. There are also many designers who are looking for appropriate test methods to more accurately predict the characteristics of the connector‘s useful life. This greatly reduces the number of samples required for testing and the associated costs associated with testing many samples.
    We also reached the following seven conclusions in the stress release test:

1. When stress is used as a correlation function for test time, it is often found that the slope changes. Therefore, the test time should be lengthened to get this feature.
2. When the measured data has a certain correlation with temperature, it is very useful to linearize the existing data to a longer test time. The shortcoming is that when the test time exceeds the specified time, the slope turns sometimes, and the performance cannot be predicted at other temperatures.
   
3. The factors that drive the performance of the connector to the limit of alloy performance may continue to exist. This shows that accurate prediction of stress relief is the key to connector design.
   
4. The data obtained from the strip has certain limitations. Since the bending is done during the connector manufacturing process, it does not reflect any negative effects.
   
5. The rolling of the copper strip can simulate the manufacture of the connector, which has the opposite effect as the C7025 and C17410.
   
6. In a single diagram, the Larsen-Miller parameter is very useful when plotting data curves at various temperatures. This method is also extremely useful for predicting the performance of materials between the two temperatures of completed and expected short-term tests and thereby simulating the long-term performance of the material. However, if the test temperature range is exceeded, it cannot be used to estimate it.
   
7. These methods can be combined to retest the estimated values.