The name is derived from the cross-sectional shape of a bathtub: steep sides and a flat bottom.
The bathtub curve is generated by mapping the rate of early "infant mortality" failures when first introduced, the rate of random failures with constant failure rate during its "useful life", and finally the rate of "wear out" failures as the product exceeds its design lifetime.
In less technical terms, in the early life of a product adhering to the bathtub curve, the failure rate is high but rapidly decreasing as defective products are identified and discarded, and early sources of potential failure such as handling and installation error are surmounted. In the mid-life of a product—generally speaking for consumer products—the failure rate is low and constant. In the late life of the product, the failure rate increases, as age and wear take their toll on the product. Many electronic consumer product life cycles strongly exhibit the bathtub curve.
While the bathtub curve is useful, not every product or system follows a bathtub curve hazard function; for example, if units are retired or have decreased use during or before the onset of the wear-out period, they will show fewer failures per unit calendar time (not per unit use time) than the bathtub curve.
Hang Zhou, Ajith Kumar Parlikad, and Andrew Harrison from the University of Glasgow, University of Cambridge, and Rolls Royce have demonstrated and mathematically proved that the wear-out stage of the 'bathtub curve' can be further brought to a higher dimension, and is developed into the concept of reliability surface, with its dimensionality reduction projection as the reliability contour map.