As manufacturers make the move to advanced Industry 4.0 frameworks, they face a familiar frustration: machine failures.
According to the Deloitte 2025 Smart Manufacturing Survey, 85% of companies say that smart manufacturing will transform how products are made, but 65% say managing operational risk is their highest priority during this transition.
Machine failure is where operational risk shows up on the plant floor. If critical equipment breaks down unexpectedly, the results range from production delays to product defects, safety risks, and significant financial losses.
This is further complicated by the heterogeneous nature of machine failures. The more organizations know about the types of machine failures, the better prepared they are to identify root causes, create reliability strategies and prevent recurring issues.
What is machine failure?
Machine failure is the loss of equipment functionality. This loss may be sudden or developed over time. It may be unexpected or anticipated, and it may require repair, refurbishment, or replacement.
There are two broad categories of machine failures: degradation and catastrophic.
Degradation happens over time. These failures are often connected to general equipment wear and tear or stem from small imperfections in parts that become more pronounced over time. These failures typically lead to a slow loss in performance over time.
Catastrophic failures happen without warning. Machines that appear to be in perfect working condition abruptly stop working, immediately halting production and putting staff safety at risk. Stress and strain are often connected to catastrophic failures. For example, uneven pressure distribution on the steel frame of assembly line equipment could lead to sudden structural failure when materials become too weak.
No matter the category, failure leads to:
- Slowed (or stopped) production output
- Decreased product quality
- Reduced safety
- Increased operational costs
Improving equipment reliability limits the risk of both degradation and catastrophic failures, in turn boosting production line and business performance.
Why understanding failure types matters
Within these two categories, there are multiple failure types, also called failure modes. Understanding these types lays the groundwork for maintenance teams to:
- Enable root cause analysis
- Improve maintenance planning
- Identify recurring patterns
- Support reliability-centered maintenance
- Build predictive maintenance programs
- Enhance asset lifecycle management
Separating failures into multiple types also helps streamline the process of data collection and analysis. Instead of curating failure data from multiple sources and formats, data is stored according to characteristics such as the type of failure, its impact and its resolution priority.
Types of machine failures
There are seven broad types of machine failures.
Mechanical failures
Mechanical failures occur when systems that use physical force break down, leading to machine failure. Common physical processes include shaping, cutting, shearing, and molding. Mechanical processes also support equipment functions, such as bearings that enable rotation, which underpins the movement of conveyor belts. If these bearings fail, the result is a sudden machine stoppage.
Other types of mechanical failures include:
- Mechanical wear of gears or bolts
- Shaft misalignment
- Component fatigue
- Loose fasteners
- Mechanical overload
- Friction and lubrication issues
Electrical failures
Electrical failures are tied to wires, circuitry and power sources. Even small electrical interruptions can lead to significant downtime, especially if these issues cause a cascading effect. For example, if an electrical component fails, it can cause faults such as shorts, trips or control instability that stop the machine or take it out of safe operating limits. If these machines are highly specialized or difficult to repair, electrical issues could last days or weeks.
Maintenance teams may encounter electrical failures such as:
- Motor failures
- Electrical short circuits
- Overheating components
- Insulation breakdown
- Power supply instability
- Control system failures
- Wiring damage
Electrical failures are especially problematic for automated systems that depend on operational reliability to deliver consistent results.
Hydraulic system failures
Machines that use hydraulics are also prone to failure. Hydraulic systems are operated or affected by liquids, such as water or oil. Die-cast molding machines are one example; these assets use high-pressure hydraulics to generate the force required for die mold clamps.
Common causes of hydraulic failures include:
- Fluid contamination
- Seal degradation
- Surface degradation
- Pressure imbalances
- Pump failures
- Valve malfunctions
- Leaks in hydraulic lines
Because hydraulic systems operate under high pressure, some failures can escalate quickly—especially when leaks, contamination or pressure control issues aren’t caught early. Machinery failure may cause equipment to completely seize up and stop working, or it may lead to the explosive ejection of fluids or metal components.
Pneumatic system failures
Pneumatic systems use compressed air or gas to generate energy for mechanical work. They include components such as compressors, valves and actuators to control the volume and velocity of compressed gases.
Pneumatic failures are often preceded by:
- Air leaks
- Compressor failure
- Moisture contamination
- Pressure regulation issues
- Valve malfunctions
These compressed gas systems are used in automated lifting, packaging and moving equipment. Failure can create the need for manual processes that are less efficient and less reliable.
Operational or human-related failures
Operator‑related issues are rarely intentional. Most unplanned downtime tied to human factors comes from gaps in training, unclear procedures or setup errors that put equipment at risk.
Possible human-related failures include:
- Improper equipment operation
- Incorrect machine setup
- Failure to follow operating procedures
- Overloading equipment
- Lack of training
All these failure points are tied to the misuse of machinery. For example, a lack of training can lead staff to use equipment in ways it was not intended. While this may not result in immediate failure, it can set the stage for catastrophic issues.
Wear and tear failures
Wear and tear failures are caused by everyday machine use. Although components typically indicate their projected useful lifespan, operating conditions can shorten this expectation.
Teams should be prepared for wear and tear failures, such as:
- Component degradation over time
- Fatigue failures are tied to continual use
- Material deterioration
- Seal and gasket wear
- Aging electrical components
It is impossible to avoid wear and tear, but manufacturers can mitigate the impact with preventive maintenance processes, repair or replace key components before they fail.
Environmental failures
Machines are also affected by the local environment. Poor conditions can reduce the expected lifespan of assets or increase the likelihood of specific equipment malfunctions. Problematic environmental issues include:
- Temperature extremes
- Dust and debris contamination
- Moisture exposure
- Parts corrosion
- Vibration from surrounding equipment
Addressing these issues requires regular assessment of facility conditions. If issues are identified, companies are better served by taking machines offline for planned repair downtime, rather than running the risk of unexpected failures.
Sudden vs. gradual machine failures
Manufacturing companies must account for both sudden and gradual (also called progressive) failures. While sudden failures are often more damaging up-front, they’re easier to identify and resolve. Gradual failures, meanwhile, can masquerade as small performance drops or accuracy issues that are difficult to track and pinpoint.
Failure type | Description | Example |
Sudden failure | Immediate equipment breakdown with little warning | Electrical short, broken shaft |
Gradual failure | Performance slowly degrades over time | Bearing wear, lack of proper lubrication |
Detecting early signs of machine failure
So how do maintenance teams spot potential machine failure? First is knowing what to look for. Some early signs of machine failure include (but aren’t limited to):
- Unusual vibrations
- Steadily rising operating temperatures
- Increased energy consumption
- Changes in machine noise
- Reduced production efficiency
- Fluid leaks
- Abnormal product defects
Machines may display one, some or none of these signs. As a result, observation isn’t enough in isolation.
Preventing machine failures through maintenance strategies
Maintenance strategies are next on the failure prevention checklist. These strategies help teams go beyond basic observation to more fully investigate machine operations.
To reduce failure risks, teams can implement:
- Preventive maintenance programs: Preventive maintenance programs focus on solving common issues, such as wear and tear, before they cause failures. As a result, these programs often rely on regular maintenance schedules to ensure issues aren’t missed.
- Predictive maintenance technologies: Predictive maintenance uses AI and analytics to collect, analyze and draw conclusions from manufacturing data. These tools are typically paired with CMMS and ERP technologies to provide increased visibility. Predictive analytics help reduce reliance on breakdown maintenance, which sees machine failures addressed only after they fail.
- Root cause failure analysis (RCFA): RCFA targets the root cause rather than the symptoms of failure. For example, reduced production performance is typically a symptom. The root cause may be anything from worn-down components to failing electrical connections to a lack of operator knowledge.
- Equipment condition monitoring: Condition monitoring helps detect the early warning signs of failure. Consider a hydraulic system that appears to be in good working condition. IIoT-connected sensors, however, report a steady pressure increase. Teams are notified, allowing them to take action and identify the root cause.
- Operator training: Continuous operator training provides staff with the knowledge and skills they need to operate machines safely and identify possible risks that should be reported to maintenance teams.
Ultimately, the goal of manufacturing maintenance strategies is to lay the foundation for reliability-centered maintenance (RCM). This maintenance approach focuses on maximizing uptime and minimizing machine downtime through the use of comprehensive failure pattern monitoring and management.
Using data and technology to prevent equipment failures
Finally, companies need to make use of data and technology to limit risk and prevent failures.
The advent of connected, always-on networks has enabled a fundamental shift in maintenance operations. Teams are no longer confined to historical effects analysis, but can instead combine previously collected and real-time data to gain on-demand insight.
Technology-focused functions include:
- IIoT sensors such as those used for vibration monitoring, pressure detection and thermal imaging.
- AI-driven analytics tools capable of collecting and curating data to identify operational trends.
- Machine health monitoring solutions that track machine status in real time and automatically send alerts to maintenance staff.
- Predictive maintenance systems that capture and compare machine data in real-time to identify possible failure points.
- The integration of sensors, programmable logic controllers (PLCs) and other industrial systems with CMMS and EAS platforms.
Understanding failures to improve reliability
The complex and changing nature of production lines means that machine failures can occur for a host of connected or unrelated reasons. From sudden electrical issues to gradual wear-and-tear to untrained operator mistakes, failure can happen anytime, anywhere.
Understanding failure types helps teams identify potential issues early, in turn allowing organizations to design and implement proactive and preventive plans that help them stay ahead of potential problems.
Not sure where to start solving for failures? ATS can help. Our experienced team of technicians can implement predictive maintenance solutions, deploy condition-based monitoring tools, perform root cause failure analysis, and set the stage for data-driven reliability improvements.
Better manage machine failure and improve maintenance operations with ATS. Let’s talk.
References
Gaus, T. & Schlotterbeck, M. (2025, May 1). 2025 smart manufacturing and operations survey: Navigating challenges to implementation. Deloitte Insights. https://www.deloitte.com/us/en/insights/industry/manufacturing-industrial-products/2025-smart-manufacturing-survey.html
