Bathtub Curve: Definition, Failure Stages and Maintenance Strategy

The Three Phases of the Bathtub Curve

Phase 1: Infant Mortality (Early Failures)

New equipment experiences high initial failure rates. This phase typically lasts weeks to months, depending on the asset type and manufacturing quality. Failures result from manufacturing defects, assembly errors, design flaws, component defects, and misinstallation.

Examples include a bearing installed with incorrect clearance, a welds that failed inspection undetected, or a control board with a latent soldering defect. These failures are random and unpredictable; they occur at high frequency initially but decline as defective units fail and are removed from service.

Burn-in testing, rigorous quality control, and accelerated start-up monitoring reduce infant mortality. Many manufacturers warranty against early failures and replace defective units outright, accepting the cost of detection as part of quality assurance.

Phase 2: Useful Life (Constant Failure Rate)

After surviving the infant mortality phase, equipment enters its useful life, where failure rates stabilize at a low, nearly constant level. This is the longest phase, often spanning years or decades depending on asset class. Failures during useful life are typically random, caused by unexpected overload, operator error, environmental stress, or rare component defects.

The predictable, low failure rate during useful life makes this the ideal window for preventive maintenance and condition monitoring. Since failure rates are low and somewhat random, time-based maintenance (e.g., oil changes every 1,000 hours) is cost-effective and reliable.

Mean time between failure (MTBF) is high during useful life, making this phase optimal for production scheduling and capacity planning.

Phase 3: Wearout (Accelerating Failures)

As equipment approaches the end of its designed operational life, material degradation accelerates. Bearings wear, seals fail, metal fatigues, electrical insulation breaks down, and components reach their fatigue limits. Failure rates climb sharply, and failures become frequent and predictable based on operating hours or cycles.

Once equipment enters wearout, failures occur more frequently, and mean time to repair increases (parts may be hard to source). Planning a replacement, major overhaul, or end-of-life decision becomes urgent. Continuing operation in wearout risks unplanned breakdown maintenance, production disruption, and safety hazards.

Why the Bathtub Curve Matters for Maintenance

The bathtub curve informs three distinct maintenance strategies:

• Early phase: Detect and replace defective units quickly, run burn-in tests, monitor closely for early signs of failure.
• Useful life phase: Apply preventive maintenance on a schedule, use condition monitoring to extend intervals, avoid over-maintenance.
• Wearout phase: Plan replacement, major overhaul, or end-of-life decisions; increase inspection frequency; prepare for higher downtime risk.

Without understanding the bathtub curve, organizations may over-maintain healthy equipment during useful life or fail to plan for wearout, leading to unexpected failures and emergency repairs.

Measuring the Bathtub Curve

The vertical axis represents failure rate (failures per unit time). The horizontal axis represents equipment age or operating time. The curve is typically measured by tracking:

• Time to failure for individual units
• Percentage of units failed at each age milestone
• Mean time between failure (MTBF) at each phase
• Mean time to repair (MTTR) as it relates to phase

Practical Examples of the Bathtub Curve

Manufacturing Motors

A new electric motor may fail within the first week due to a winding defect (infant mortality). If it survives that period, it reliably runs for 10 years with predictable failure rates during useful life. After 10 years, bearing wear accelerates, and failures become frequent. At year 12, replacement is planned rather than repair.

Hydraulic Pumps

A hydraulic pump installed in a press may fail in the first month due to contaminated fluid or installation error (infant mortality). During years 2-8, it operates with occasional random failures due to foreign objects or extreme pressure spikes (useful life). In year 9, seal wear and internal corrosion cause frequent leaks and pressure loss (wearout).

Conveyor Belts

A new conveyor belt may break in the first weeks if splicing was poor or the belt was pinched during installation (infant mortality). For 3-4 years, it runs with rare failures caused by overload or debris impact (useful life). In year 5-6, the belt becomes brittle, tears frequently, and replacement is scheduled (wearout).

Bathtub Curve and Equipment Reliability

The bathtub curve is central to asset reliability engineering. By understanding where an asset sits on the curve, maintenance teams can optimize spending. Over-maintaining in useful life wastes resources. Under-maintaining in wearout invites failure.

Reliability improvement focuses on reducing failure rates at each phase: improving manufacturing quality to shorten infant mortality, selecting durable designs to extend useful life, and planning end-of-life transitions to avoid wearout surprises.

Limitations of the Bathtub Curve Model

The classic bathtub curve assumes a simple failure pattern, which does not always hold:

• Complex systems with many components may show different patterns; failure of one subsystem can trigger cascading failures.
• Software and firmware, if well-tested, may skip the infant mortality phase entirely.
• Maintenance interventions themselves can reset the curve; a major overhaul restarts the asset on a new curve.
• Harsh or variable operating environments may compress useful life or accelerate wearout.

Despite limitations, the bathtub curve remains a foundational tool for maintenance planning and asset lifecycle management.

Applying the Bathtub Curve to Maintenance Strategy

Infant Mortality

Run equipment under load in a test environment before deployment. Monitor closely for the first weeks of operation. Replace any units showing early failure symptoms. Keep spare components on hand in case of rapid failure.

Useful Life

Implement preventive maintenance on a fixed schedule (e.g., oil changes every 500 hours). Use condition monitoring to extend intervals if condition remains good. Avoid reactive breakdown maintenance during this phase; the cost of planned maintenance is far lower.

Wearout

Plan replacement or major overhaul well in advance. Increase inspection and maintenance frequency. Consider running critical equipment redundantly if failure risk is unacceptable. Do not wait for failure to occur in this phase; proactively transition to newer equipment.

Frequently Asked Questions

The Bottom Line

The bathtub curve is a powerful model for understanding how equipment failure rates evolve over time. By recognizing the three phases (infant mortality, useful life, and wearout), maintenance teams can shift from reactive to proactive strategies, optimize spending, and improve asset reliability.

Modern condition monitoring and predictive maintenance extend the useful life phase and help detect the transition to wearout early, allowing planned replacements rather than emergency repairs. Understanding where your equipment sits on the curve is fundamental to effective lifecycle management.