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Imagine a production machine that has just been installed on the factory floor, even though all the components are new, it does not mean that the machine is free from the risk of failure.
On the other hand, machines that have been in operation for many years are also at risk of experiencing damage due to wear and tear. This phenomenon can be explained using the bathtub curve, a graphical model that depicts the relationship between a component’s failure rate and its operating time.
This graph is called the bathtub curve because it resembles a bathtub, with a high failure rate early in life, a low and stable rate during normal operation, and then a rise again as the component reaches the end of its useful life (Elsayed, 2021). This model is a fundamental concept in reliability engineering because it helps engineers understand failure characteristics throughout an asset’s life cycle.
The first phase of the bathtub curve is known as the early failure or infant mortality period. During this stage, the failure rate is relatively high because the component is still in its early stages of operation. Failures are generally not caused by component age, but rather by manufacturing defects, assembly errors, substandard materials, or installation and commissioning errors (Jardine and Tsang, 2013). For example, bearings installed misaligned can fail within a short time, even before reaching their design life. Therefore, various industries implement burn-in testing, quality inspection, and commissioning tests to identify potential failures early, before the equipment is fully operational.
After passing through the initial phase, components enter their useful life, a period when the failure rate is low and relatively constant. During this phase, most components have outgrown their initial potential defects and can operate within their design specifications. Failures that occur during the useful life are generally random and influenced by external factors such as load fluctuations, operating errors, environmental conditions, or events that cannot be fully predicted (Moubray, 1997). Common maintenance strategies implemented in this phase are condition-based maintenance and predictive maintenance, where component condition is regularly monitored using techniques such as vibration analysis, thermography, and oil analysis so that maintenance actions can be taken before more serious failures occur.
As operating time increases, components enter the wear-out failure phase, a period when the failure rate increases significantly due to wear, fatigue, corrosion, deformation, and degradation of mechanical and electrical properties. At this stage, damage is no longer random but a natural consequence of component aging. For example, gears that have undergone millions of loading cycles are prone to fatigue cracking, while the insulation in electric motors can degrade due to continuous exposure to high temperatures. Therefore, preventive maintenance strategies, overhauls, and age-based component replacement are crucial to prevent unplanned downtime and maintain production system reliability (Dhillon, 2006).
Thus, the bathtub curve is a crucial tool in understanding component failure patterns throughout its life cycle. By understanding the characteristics of early failure, useful life, and wear-out failure, companies can determine the most effective maintenance strategy according to the condition of their assets. This approach not only helps improve equipment reliability and availability but also reduces maintenance costs, extends asset life, and minimizes the risk of operational disruptions. In the modern industrial era, which increasingly relies on productivity and efficiency, implementing the bathtub curve concept is an important foundation for building a proactive, planned, and sustainable maintenance system.
Author: Brian Arga Prasidio Putra
Editor: Brian Arga Prasidio Putra
References
Dhillon, B.S. (2006). Maintainability, Maintenance, and Reliability for Engineers. Boca Raton, FL: CRC Press.
Elsayed, E.A. (2021). Reliability Engineering. Edisi ke-3. Hoboken, NJ: Wiley.
Jardine, A.K.S. dan Tsang, A.H.C. (2013). Maintenance, Replacement, and Reliability: Theory and Applications. Edisi ke-2. Boca Raton, FL: CRC Press.
Moubray, J. (1997). Reliability-Centered Maintenance. Edisi ke-2. Oxford: Butterworth-Heinemann.
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