Reliability Bathtub Curve is a method used in reliability analysis. It is commonly used in statistics and reliability engineering to understand the behavior of a system or process over time. In the reliability analysis, it is important to model the characteristics of time, which is utilized to not only predict the probability of success and life cycle, but also predict time until the next failure and repair or maintenance rates. $($Breznick$,$ Alena, et al$.)$ The Reliability Bathtub Curve demonstrates the significant increase in a product's failure rate as it ages. In actuality, the curve described by the bathtub model is a combination of three curves with J shaped, U shaped, and gradually increasing slopes. The major concepts illustrated by the bathtub curve are the three possible modes of failure. These are: Early Failures or Infants Mortality, Random Failures and Wear out Failures.

The Bathtub Curve gets its name because the graph representing the rate of failure of a product over time has a steep downward slope at the beginning, which soon flattens out. The line then becomes steep again as time progresses, forming the shape of a bathtub $($Rao$,$ Manaswini$).$ Depending on the product, the initial failure rate may not actually be very high, but it is the rate at which the product's design faults are found. These faults are rectified, and the product begins to function much more efficiently until coming to the Random Failure period. The increase in failure rate begins the Wear out Failures phase where product efficiency and functioning decrease, encountering more downtime and maintenance until the product's total failure $($Rao$,$ Manaswini$).$ This could apply to all products which should not have a high infant mortality rate and should function at its best until total failure.

Now, why is the reliability bathtub curve important? Reliability is a quality that is vital to assure the efficient and effective performance of a product. Without reliability, the product is useless. The reliability bathtub curve can give any reliability engineers enhanced perspective into the ways design change can affect product reliability. Properly understanding this concept can provide them with a powerful decision$-$making tool.

The bathtub curve depicts the various stages of a product's lifecycle. These stages include an infant mortality period, a useful$($normal$)$ life period, and an aging$($wear$-$out$)$ period $($Quality Gurus$).$ The firm attempts to improve the reliability of its product through design changes. The firm's goal might be to increase the length of the useful life period or to reduce the aging period $($Rao$).$ In order to assess the effectiveness of design changes, the engineer can use the bathtub curve to compare the old and new curves. By focusing on the concept of an embedded reliability assessment, one can compare the old and new curves to isolate where and why the old design was better or where and why the new design is better. This can assist the engineer in weeding out less effective design changes and in the end produce a more reliable product. Overall, a better knowledge of the causes of failure allows you to implement the right preventive and predictive maintenance strategies $($Rao$).$

To add, the more complex and modern the product, the more complex the system of the product. No longer are products made up of a single part or component. To assess the impact of each specific design change, the engineer needs a method to relate individual part reliability to the reliability of the entire system, and available methods are somewhat lacking. By applying the concept of the bathtub curve to individual components and part systems, one can provide a bridge from part reliability assessment to system reliability assessment. This can allow the engineer to better understand the impact of individual design changes, potentially preventing changes that have negative effects on overall product reliability.

Another important application of the bathtub curve is in the area of maintenance strategy $($MCIM$).$ The name of the game today is to provide customers with products that require little or no maintenance but are still affordable. Typically, the firm would want to provide a long useful life period with small amounts of maintenance at the end. By plotting the maintenance factor as a separate bathtub curve, one can choose the most suitable maintenance strategy for their product and determine the most effective changes for product reliability $($MCIM$).$

The life cycle of the bathtub curve can be broken down into three distinct phases which coincide with the cost of the product at that time. This early life phase is crucial to both the manufacturer and customer. During the early life phase, which is also referred to as the infant mortality phase, the system has a decreasing failure rate $($UpKeep$).$ The manufacturer is concerned with infant mortality while the customer focuses on reliability. Infant mortality is the phase of increased failure ra