What Is Infant Mortality in Maintenance and Reliability? The Complete Guide

The term “infant mortality” is often mentioned when new equipment fails unexpectedly or when assets break down shortly after maintenance, yet it is frequently treated as unavoidable or simply “bad luck.”

In reality, infant mortality refers to early-life failures that occur shortly after an asset is installed, commissioned, or returned to service, and these failures are rarely random.

Infant mortality is not about equipment wearing out. It is about defects, errors, or conditions that are introduced before stable operation begins. These weaknesses remain hidden until the asset is exposed to real operating conditions, at which point failures appear quickly and often repeatedly.

What Is Infant Mortality in Maintenance and Reliability?

The term “Infant mortality” is widely used, but not always consistently understood, which can lead to confusion when analyzing early failures.

Origin of the term

The concept of infant mortality is borrowed directly from reliability engineering and product life cycle theory. It originates from the classic reliability curve used to describe how failure rates change over time.

In this context, infant mortality represents the initial phase of an asset’s life where failures occur more frequently than expected. The term does not imply randomness, it reflects the idea that certain issues are “born into” the asset or introduced before it ever reaches stable operation.

Definition of Infant Mortality

In maintenance terms, infant mortality refers to a higher-than-normal failure rate occurring early in an asset’s life or shortly after maintenance activities such as installation, overhaul, or major intervention.

These failures are not driven by age or wear. Instead, they stem from conditions that existed from the start or were introduced during recent work.

Infant Mortality vs Normal Early Wear

A common source of misunderstanding is the assumption that all early failures are simply part of normal early wear.

This is not the case.

• Infant mortality is caused by defects, such as design flaws, manufacturing issues, installation errors, or incorrect setup.
• Normal early wear reflects expected behavior as components settle, mate, or stabilize under operating conditions.

The key difference is predictability and intent. Early wear is anticipated and accounted for in design and maintenance planning. Infant mortality, on the other hand, signals that something went wrong earlier in the asset’s lifecycle and should trigger investigation rather than acceptance.

Where Infant Mortality Occurs

Infant mortality can surface at several points, not just when equipment is brand new.

Understanding the Bathtub Curve: The Foundation of Infant Mortality

The concept of infant mortality is closely tied to one of the most well-known models in reliability engineering: the bathtub curve. While often referenced, it is also frequently oversimplified. Understanding what the curve represents is essential to using it correctly in modern maintenance environments.

What Is the Bathtub Curve?

The bathtub curve describes a three-phase pattern of failure rates over time. When plotted, the curve resembles the shape of a bathtub, which is where it gets its name.

The three phases are:

• An early failure phase, where failure rates are initially high and then decrease
• A useful life phase, characterized by a relatively low and stable failure rate
• A wear-out phase, where failures increase again as components reach the end of their service life

The Early Failure Zone

The early failure zone is not driven by time-in-service in the traditional sense. Instead, it reflects issues that were present from the beginning or introduced before normal operation began.

Common contributors include:

• Defects that escape quality assurance during manufacturing
• Damage or contamination caused by poor handling or storage
• Installation issues such as misalignment, incorrect assembly, or improper setup

These failures surface quickly because the asset is exposed to real operating conditions that reveal weaknesses not detected earlier.

Does the Bathtub Curve Still Apply Today?

In theory, the bathtub curve provides a useful framework for thinking about failure behavior. However, modern digital reliability data has shown that real-world patterns are often more complex.

CMMS and APM systems reveal significant variation between asset types, operating environments, and maintenance practices. Some assets clearly exhibit early-life failure clustering, while others move directly into a stable failure rate with little or no infant mortality phase.

Furthermore, one of the main criticisms of the bathtub curve is that it is often treated as a universal rule rather than a conceptual model.

For example:

• Certain electronic components may fail randomly rather than following a clear early-life trend
• Software-driven systems may experience failures related to logic or configuration changes rather than age

These exceptions don’t invalidate the concept of infant mortality, but they do highlight the danger of assuming the bathtub curve applies automatically.

Causes of Infant Mortality Failures

Infant mortality failures rarely have a single cause. In most cases, they are the result of weaknesses introduced across the asset lifecycle. Understanding these causes helps shift the conversation from “what failed” to “what allowed the failure to exist in the first place.”

Manufacturing Defects

Poor QA or component defects

Even with established quality systems, defects can pass through manufacturing undetected. These hidden flaws may remain dormant until the asset is exposed to real operating loads, temperatures, or speeds.

Sub-supplier quality issues

Variability introduced by tier-2 or tier-3 suppliers is a common but often overlooked contributor. Components sourced indirectly may not meet the same quality standards as primary parts, introducing inconsistency that is invisible at the final assembly stage.

Assembly and Installation Errors that can cause Infant Mortality

Assembly and installation activities are a frequent source of infant mortality, particularly when precision is required but not verified.

Misalignment

Improper alignment during installation can place excessive loads on bearings, couplings, and seals. While the equipment may run initially, the added stress accelerates failure, often within days or weeks of startup.

Soft foot

Poor base preparation or uneven mounting surfaces create soft foot conditions that distort machine frames. This distortion introduces vibration and mechanical stress that significantly reduces component life, even if alignment appears acceptable.

Electrical installation errors

Electrical issues such as poor connections, incorrect torque on terminals, or inadequate grounding can lead to overheating, nuisance trips, or early component degradation.

Human Factors that Can Cause Infant Mortality

Technician skill variability

Many maintenance tasks are highly dependent on individual skill and experience. When outcomes vary from one technician to another, so does reliability.

Lack of standard work

Without clearly defined and enforced procedures, overhauls and installations are performed inconsistently.

Poor Commissioning Practices that Can Cause Infant Mortality

Incomplete commissioning checklists

Commissioning is often treated as a formality rather than a critical reliability gate. When functional, safety, or performance checks are skipped or rushed, latent issues remain undiscovered.

Insufficient run-in time

Assets that are loaded too early are forced into full service before minor issues can be detected and corrected.

Handling and Storage Issues that Can Cause Infant Mortality

Contamination

Exposure to dust, moisture, or corrosive environments during storage or handling can compromise components before installation even begins.

Transportation damage

Small shocks or vibrations during transportation may not be visible, but they can degrade precision components.

Incorrect Operating Conditions that Can Cause Infant Mortality

Wrong lubrication type or quantity

Using the wrong lubricant or the right lubricant in the wrong amount, creates immediate stress on bearings and moving components. These errors often lead to rapid degradation that is mistaken for manufacturing failure.

Overload, overspeed, or improper process settings

When new assets are operated outside their design envelopes, failure becomes a matter of time rather than chance.

Software & Firmware Failure Mechanisms that Can Cause Infant Mortality

Control logic bugs

Errors in PLC programs, HMI logic, or embedded software can create unstable operating conditions.

Incorrect setpoints

Improper calibration or incorrect setpoints can cause assets to shut down prematurely or operate under unintended conditions. While the hardware may be fully capable, the software configuration introduces failure mechanisms early in the asset’s life.

How to Identify Infant Mortality in Your Plant

The key is to combine data analysis with physical evidence and frontline feedback. When these signals align, early-life failures become easier to distinguish from normal operational variability.

Data Patterns in CMMS and APM Systems

Early recurrence after maintenance

One of the clearest indicators of infant mortality is the rapid recurrence of work orders following maintenance. When the same asset or component fails again within 30 days of installation, overhaul, or repair, the likelihood of an early-life defect is high.

High failure rate in the first 5–10% of asset life

APM systems make it possible to view failures relative to asset age or lifecycle stage. A noticeable spike in failures during the first 5–10% of life is a strong signal of infant mortality.

Statistical Methods

Weibull distribution

Weibull analysis remains one of the most effective tools for identifying infant mortality. When the shape parameter β is less than 1, it indicates a decreasing failure rate over time, a classic signature of early-life failures.

MTTF and MTBF abnormalities

Another useful signal comes from unusually short mean time to failure (MTTF) or mean time between failures (MTBF) during early operation.

Visual and Physical Indicators

Data alone rarely tells the full story. Physical inspection and condition monitoring provide critical confirmation.

Vibration spikes

Sudden increases in vibration shortly after installation often indicate misalignment, looseness, or improper assembly.

Thermal anomalies

Abnormal temperature patterns can reveal overload conditions, lubrication issues, or electrical resistance.

Operator Feedback

Early noise, smell, or instability

Operators are often the first to notice subtle changes. Unusual noises, burning smells, or unstable operation shortly after startup are classic symptoms of infant mortality.

These observations frequently trace back to assembly, installation, or configuration errors.

The Business Impact of Infant Mortality

Early-life failures directly affect financial performance, safety, and the organization’s ability to achieve stable, predictable production.

Financial Costs

Downtime

Failures that occur during ramp-up are particularly disruptive. Assets are expected to move quickly from installation to productive service, and unplanned outages at this stage interrupt schedules, delay output, and create cascading impacts across operations.

Wasted labor

When assets fail shortly after maintenance or installation, the labor invested in the original work delivers no lasting value. Technicians are pulled back to redo tasks, troubleshoot avoidable issues, and correct errors that should have been eliminated earlier.

Warranty claims

Early failures frequently trigger warranty claims, but these rarely translate into cost-free solutions. Even when parts are covered, the administrative effort, diagnostic time, and coordination with OEMs create friction.

Safety Implications

Failures during commissioning can be hazardous and can expose personnel to elevated risk, particularly when systems behave unexpectedly.

Unexpected trips, mechanical failures, or control issues during early operation increase the likelihood of incidents, especially when teams are under pressure to bring equipment online quickly.

Effect on Production Reliability

Instead of a smooth ramp-up, organizations experience repeated interruptions that erode confidence in new equipment.

These delays extend the time required to achieve design capacity and can distort performance expectations, making it harder to separate true asset capability from avoidable early-life issues.

Prevention: How to Reduce Infant Mortality Failures

Reducing infant mortality is where reliability efforts deliver their highest return. Most early-life failures are not inevitable, they are the result of controllable practices. By focusing on how assets are installed, commissioned, maintained, and supported, organizations can significantly lower the risk of failures occurring before equipment reaches stable operation.

Improve Installation and Commissioning

Strong installation and commissioning practices act as the first line of defense against infant mortality.

• Use precision alignment tools
• Follow Torque procedures
• Standardize Commissioning checklists

Strengthen Quality Control

Quality control should extend beyond the factory and into the plant environment.

• Incoming QC inspections
• Factory Acceptance Testing (FAT) and Site Acceptance Testing (SAT)

Training and Workforce Competency

Human performance plays a critical role in early asset reliability.

• Certification programs
• Cross-training

Spare Parts and Storage Management

Spare parts are assets too, and their condition directly affects early-life reliability.

• Climate-controlled storage
• Preservation routines

Lubrication Excellence

Lubrication errors are a frequent and preventable cause of infant mortality.

• Lubricant selection
• Maintaining lubricant cleanliness

Conclusion

Infant mortality failures are one of the clearest indicators of how well an organization controls its reliability fundamentals. When assets fail early, the issue is rarely hidden inside the machine itself. Treating these failures as unavoidable masks learning opportunities and allows the same conditions to repeat across assets, projects, and teams.

Organizations that consistently reduce infant mortality do not rely on luck or heroics. They design reliability into every transition point: from manufacturing and installation, to commissioning, to the first days of operation. They use early failures as feedback, not frustration, and they close the loop between engineering, maintenance, operations, and supply chain.

Ultimately, minimizing infant mortality is less about extending asset life and more about achieving predictable performance sooner. The faster an asset reaches stable operation without disruption, the faster it begins delivering real value. In that sense, infant mortality is not just a maintenance problem.

Frequently Asked Questions (FAQ)

What is infant mortality?

Infant mortality in maintenance refers to early-life asset failures that occur shortly after installation, overhaul, or maintenance work, typically before the equipment reaches stable operation.

What causes infant mortality failures?

Infant mortality failures are most commonly caused by installation errors, manufacturing defects, poor commissioning practices, contamination introduced during handling or storage, or incorrect lubrication selection or application.

How can you reduce infant mortality in industrial equipment?

Infant mortality can be reduced through standardized and audited commissioning processes, optimized preventive maintenance strategies, effective condition monitoring, workforce training, and the use of precision installation and maintenance tools.

How do you detect infant mortality using reliability data?

Infant mortality can be detected using reliability data by analyzing APM patterns that show early-life failure clustering, applying Weibull analysis, and identifying repeat failures occurring shortly after maintenance or installation.

Can lubrication errors cause infant mortality?

Lubrication errors are one of the most common causes of infant mortality, as using the wrong lubricant type, incorrect quantities, or contaminated lubricants can lead to rapid component failure.