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Testing and calcu­lating

Using different methods to deter­mine service life

A real­istic eval­u­a­tion of service life for durable, electro­mechan­ical compo­nents like fans is an impor­tant deciding factor for users. Because manu­fac­turers cannot test for decades before supplying customers, they rely on a mix of theo­ret­ical approaches and real­world values. The calcu­la­tion and test proce­dures and the mix of both varies widely from manu­fac­turer to manu­fac­turer. This is why it is impor­tant to be able to eval­uate the resulting spec­i­fi­ca­tions and values correctly.

Bathtub curve

Different weighting

Two commonly used values are service life and reli­a­bility. However, these cannot be converted back and forth, as they have different impact on the failure perfor­mance of compo­nents. Thus the service life spec­i­fies the time period in hours up to the point where ten percent of the devices have failed. In contrast, reli­a­bility indi­cates what is known as the mean time between fail­ures (MTBF) value – the average time when one device fails out of a group started simul­ta­ne­ously. So-called classic failure perfor­mance says that a few compo­nents can fail at the begin­ning of oper­a­tion due to faulty parts or instal­la­tion errors. In the subse­quent period, the devices endure long oper­ating times with only a few, random fail­ures. The MTBF value describes this range. Towards the end, wear then becomes notice­able and the failure rate increases again. The service life is delim­ited this way.

Test reduc­tion

In order to reduce the test period, manu­fac­turers often operate a large number of devices over a period of six to twelve months. Then the service lifeis extrap­o­lated from the result using different methods. However, these methods provide incor­rect results if the test does not include cases of wear. In that case the service life infor­ma­tion turns out too opti­misti­cally. The test period is often short­ened by achieving accel­er­ated ageing using external influ­ences such as increased temper­a­tures, temper­a­ture changes or shocks. The often unre­al­istic, ascer­tain­able effects of temper­a­ture influ­ences and their retroac­tive projec­tion to normal oper­a­tion are a disad­van­tage compared to real, long-term tests.
For example, many computing models assume a doubling of service life at a temper­a­ture drop of 10 to 15 kelvin. If manu­fac­turers use this extrap­o­la­tion multiple times, absurdly high service life values quickly result. Here it is useful for the user to compare the service life infor­ma­tion at high temper­a­tures. If these are similar, but differ greatly at low temper­a­tures, then the service life is not different, just the math­e­mat­ical model that was used.

Hands-on eval­u­a­tion

New prod­ucts

Despite similar results in an accel­er­ated service life test, the spec­i­fi­ca­tions of various manu­fac­turers can differ­en­tiate in multiple ways. Thus, a conser­v­a­tive esti­mate of all influ­encing factors is essen­tial for real­istic spec­i­fi­ca­tions. However, long-term expe­ri­ence and constantly opti­mised arith­metic oper­a­tions are absolutely neces­sary for such prac­tical eval­u­a­tions.

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