What is equipment failure and how can you prevent it?

According to the International Organization for Standardization (ISO) 14224, failure is the “termination of the ability of an item to perform a required function.” This definition includes functional failure (when an asset still operates yet at a diminished capacity) and potential failure (when detectable conditions indicate that a functional failure is imminent). 

Equipment failure can result from multiple causes, including operator error, machine error, environmental factors or overdue equipment maintenance. A major concern for industrial and manufacturing operations, the failure of critical assets can easily cause unplanned downtime, completely halting a business’s ability to produce goods or operate profitably. 

Equipment failure does not necessarily imply that machinery has stopped working completely. It can also mean the loss of a piece of machinery’s ability to function to the required code, quality or safety standards.

A complete failure can manifest as a motor that will not start or a pump that cannot sufficiently drain fluids. A partial failure can manifest as a motor that runs but operates at dangerously high temperatures. A partial failure can also manifest as a pump that, while operational, can present an unacceptable safety risk for the operators.

This distinction is important because a partial failure can also present an opportunity for timely intervention before a total failure brings operations to a complete standstill.

Industrial organizations depend on their equipment assets to produce goods, deliver services and maintain continuous operations. When equipment fails and cannot perform as required, the downstream effects can have a larger ripple effect beyond the loss of a single machine.

Because these companies often rely on equipment as part of a series of sequential operations, the failure of a singular piece of equipment can bring the entire production line to a halt. This operational disruption can have an exponential impact on production schedules, product quality, maintenance budgets and supply chain timelines. 

Preventing equipment failure is a main concern for most asset management initiatives. Even a temporary stop-down can trigger expensive downtime for the entire production process. Because of this risk, efforts associated with avoiding, mitigating and responding to equipment failure are a primary goal and function of industrial maintenance operations.

Any adequately healthy, robust or mature industrial maintenance strategy should help organizations better understand why equipment might fail in the first place. It should also prioritize any necessary precautions or responses to either prevent equipment failure from happening at all (or quickly recover from unavoidable breakdowns).

Condition monitoring (CM), operator observations and regular inspections can reveal early indicators, such as excess vibration, leakage, unusual noise, heat or declining output. Early detection can help recover full operational capacity before equipment failure causes excessive financial losses or even worse, loss of human life.

Proactive maintenance strategies, including predictive maintenance, preventive maintenance, condition-based maintenance and corrective maintenance, are all designed to decrease machine failure and increase equipment reliability.

The cost of downtime can easily exceed repair costs. This cost imbalance means that allocating operational budgets to improving and maintaining asset reliability is typically far more efficient than funds spent on reactive maintenance and emergency maintenance. However, depending on the type of equipment and its function, deferred maintenance and run-to-failure strategies can be employed when machine failure won’t cause catastrophic results. 

The financial impact of equipment failure and especially any resulting unplanned downtime is often high. Unplanned downtime costs industrial manufacturers an estimated USD 50 billion annually. Contributing to potential lost production cycles, emergency labor premiums such as overtime and expedited logistics expenses including overnight shipping for replacement parts, equipment failure can have rippling effects throughout operations.

According to the Information Technology Intelligence Consulting (ITIC) 2024–2025 hourly cost of downtime survey, a single hour of downtime can result in losses averaging more than USD 300,000. 

Essentially, when equipment fails and a machine breaks down, revenue production slows or stops, while operating costs continue. Rent paid on unproductive facilities and salaries paid for employees unable to continue working all contribute to the financial impact of equipment failure. Not to mention the potential damage done to an organization’s reputation when delayed production leads to missed delivery deadlines or delayed product shipments. 

The four primary types of equipment failure are sudden failure, gradual failure, intermittent failure and functional failure.

Although all types of equipment failure can result in unplanned downtime, lost revenue and dangerous working conditions, the nature of an equipment failure can vary by root cause, severity, urgency and remedy.

Understanding the different types of equipment failure helps maintenance teams develop multi-faceted strategies. An ideal maintenance strategy can prioritize resources to address the most urgent asset maintenance issues, while still monitoring equipment that is functional but will require future attention.

Different types of equipment failure will have a different impact on asset and operational performance.

Sudden failures occur with little or no warning. Often resulting from a broken machine part, electrical fault, overload or external event, sudden failures are especially dangerous and damaging because they are unexpected.

Although sudden failures cannot be planned for, most effective maintenance and safety plans will incorporate emergency response strategies and dedicated funds designed to respond to these types of failures. 

Gradual failures occur over time and typically stem from issues such as wear, corrosion, fatigue, contamination or equipment misalignment.

This type of equipment failure can begin to degrade equipment performance and reduce efficient production well before an actual breakdown. Gradual failures can be avoided through regular inspection and maintenance during planned downtime. 

Intermittent failures arise repeatedly, but inconsistently. Often resulting from loose connections, unstable sensors, software issues, vibrations or temperature changes, this type of failure can be predictable only up to a degree of probability.

Modern networked equipment sensors enabled with machine learning IoT technology can be effective in identifying, predicting and preventing intermittent failure. 

Functional failure occurs when equipment is still operable to an extent but cannot meet its required standards for either output or safety.

These types of failures can impact operational performance as severely as other types of failures. However, they can be easier to remedy depending on the root cause of the failure and the required repairs.

While sudden failures happen quickly and all at once, equipment failure can generally be understood in stages that track how equipment declines over time. These stages range from the first sign of reduced capability to the point at which an asset can no longer adequately perform.

The P-F curve is used to illustrate this process to help maintenance teams better identify the best time frame for intervention before equipment decline becomes a major issue. 

The P-F curve calculates various variables to predict when a potential failure (P) can result in a functional failure (F), as follows:

Potential failure (P): The first variable noted as P, represents the earliest point at which a developing issue can be detected. Abnormal vibrations or noises, rising temperatures, leakage or declining outputs can all be indicators of a potential failure. 

Functional failure (F): Functional failure noted as F, represents the point at which a piece of equipment is no longer capable of functioning at a sufficient capacity. It also represents the point at which the equipment can no longer operate up to established safety standards. While a machine can still be technically functional, if it is incapable of operating effectively, it is in a state of functional failure.

P-F interval: The P-F interval measures the period between first diagnosing a potential failure and when that potential failure is most likely to result in a functional failure, when left unresolved. The P-F curve is used to determine the opportune time frame within the P-F interval when maintenance can be performed on a piece of equipment to prevent failure. It can also help extend equipment lifespans and avoid unplanned downtime.

Equipment failure is measured and quantified through various metrics used by maintenance teams to establish and track equipment reliability, failure and repair performance. 

These metrics are the most important indicators for monitoring equipment reliability and addressing malfunctions or heavy equipment failure:

• Mean time between failure (MTBF): Mean time between failure (MTBF) measures the average operating time between breakdowns (either partial or total) for reparable machinery. A higher MTBF indicates longer periods of uptime and greater equipment reliability. 
  
  
• Mean time to repair (MTTR): Mean time to repair (MTTR) measures the average time required to repair equipment and restore it to operational capacity after a failure. A lower MTTR means faster recovery and decreased costs associated with unplanned downtime.  
   
• Mean time to failure (MTTF): Mean time to failure (MTTF) measures general uptime by tracking the average operating time before equipment or a component fails. MTTF is a valuable metric for maintenance teams strategically scheduling planned maintenance and helps lengthen the lifespan of new and aging equipment by avoiding over-maintenance. 
  
  
• Overall equipment effectiveness (OEE): Overall equipment effectiveness (OEE) measures the effectiveness of an individual piece of equipment by multiplying availability, performance and quality scores to provide a single standardized reference for general equipment health and availability. 

The most common causes of equipment failure include general wear and tear, corrosion from normal operations or harsh environments, improper use and insufficient preventive maintenance.

The general goal of any organization’s maintenance strategy should be to effectively predict and implement all required maintenance to prevent equipment failure. Ideally, these strategies should prevent all instances of equipment failure. However, depending on the industry and operation, some degree of equipment failure can be expected. 

A critical preliminary element of any robust maintenance strategy is recognizing equipment failure as an opportunity to capture valuable equipment data. By using frameworks such as root cause analysis (RCA) and failure modes and effects analysis (FMEA), businesses can take advantage of normally undesired equipment failure. They can use it to gain a better understanding of how and why equipment fails and might fail again.

This data can be used to inform robust maintenance strategies and fed into computerized maintenance management systems (CMMS). Real-time data from Internet of Things (IoT)-enabled sensors can empower these systems to better predict and prevent future downtimes.

The following are some of the leading causes of equipment failure.

This type of failure often results from wear and tear. Mechanical stressors can cause critical equipment parts to break because of fatigue, friction, vibration or excessive heat.

Improper operation, such as the misalignment of moving parts or inadequate lubrication, can exacerbate physical degradation and accelerate surface damage, thermal expansion or in extreme situations, seizures. 

Vibration analysis data can be applicable in determining the operational viability of heavy equipment. It can help maintenance teams identify imbalances, looseness, bearing degradation and alignment problems before they lead to critical failures. 

Maintenance can be reactive, preventive, predictive or corrective:

• Reactive maintenance follows failure
• Preventive maintenance uses scheduled services
• Predictive maintenance uses condition data to detect emerging problems
• Corrective maintenance fixes known defects before failure occurs

When maintenance is deferred, overdue or declined, minor issues can escalate into equipment failures. Wear, poor lubrication, misalignment, corrosion and declining performance can worsen, increasing repair costs, unplanned downtime and safety or quality risks. Prioritizing critical work helps preserve asset reliability and useful life.

Operator errors, such as improper usage or operation, are a common cause of equipment failure. User errors are highly likely to cause equipment failure and unplanned downtime. Common examples include operating an asset beyond its rated load, bypassing standard operating procedures (SOPs) and selecting the wrong raw materials, lubrication or fuel. They also include continuing operation despite warning signs of abnormal performance, overheating or malfunction.

Despite advances in automated maintenance platforms, the keeping and sharing of institutional knowledge and proper training remain irreplaceable. These elements help create a reliability culture that can instill and reinforce the value of proper maintenance and operational safety into complex operations.