The analysis of the main maintenance failures is a strategy used by management teams, where it plays a fundamental role in the asset monitoring process. This is how problems that directly affect the availability and reliability of machinery and equipment are identified and analyzed. In other words, it is an analysis focused on ensuring that operations continue as planned, reducing unscheduled downtime and corrective maintenance costs, and increasing the overall efficiency of assets.
In this article, you will learn about the main maintenance failures, which were identified on thousands of assets monitored by the Dynamox solution. Understand how they impact the industry’s daily routine and how the analysis of these failures improves the availability of industrial machinery.
Main mechanical failures in maintenance
Failures are part of the everyday life of industries, due to the large volume of machines and high production demands. Based on this principle, that failures or possible failures are part of the industrial scenario, maintenance teams work to monitor these occurrences through predictive maintenance.
Here at Dynamox, through the reports generated by our platform, we have mapped out this year’s main failures, indicated by our technology. Check out the image below:
1- Bearing wear: This occurs when bearings, which are essential components in the operation of various rotating machines, suffer physical wear due to surface fatigue, excessive stress or lubrication deficiency. It can appear in the spectrum as fundamental frequencies of BPFI (Ball Pass Frequency Inner Race), BPFO (Ball Pass Frequency Outer Race), BSF (Ball Spin Frequency) and FTF (Fundamental Train Frequency). Here we will use both the acceleration and the acceleration envelope to carry out the diagnosis.
Read more about bearing defects in our success case “Dynamox’s solution identifies bearing housing defect”.
2- Rotating looseness: this type of failure can be caused by incorrect mounting or wear due to contact between the components (bearing/shaft and/or bearing/housing). This defect is visible in the spectrum through the fundamental frequency of the machine’s rotation followed by multiple harmonics, an indicator of severity being the presence of inter- and sub-harmonics. Here we will use the velocity and, in some cases, the acceleration envelope.
3- Misalignment: When the shafts or components of a machine are not correctly aligned, the other components of an asset can wear out excessively: bearings, couplings, elastic elements, gears, bearing housings, etc. This defect can appear in a spectrum in 3 ways. When the misalignment is parallel, we will usually have the machine’s rotation frequency in terms of velocity (1x RPM) together with its 2nd harmonic (sometimes with more energy than the fundamental) in the radial direction. Axial misalignment manifests itself mostly in the axial direction, with behavior similar to the first case, 1x and 2x the rotation. Combined misalignment can also occur, which is a combination of the two cases mentioned above. This type of defect can usually be assessed and diagnosed using the velocity and acceleration spectrum.
4- Low structural stiffness: Lack of structural stability in a machine can lead to unwanted movements. This happens when structural weaknesses, loose bolts, cracks, punctured ducts and/or pipes and even dangerous resonance (when natural frequencies coincide with frequencies excited by the asset) are present. The spectrum shows the machine’s rotation frequency in terms of velocity, with high energy in only 1 of the directions (vertical or horizontal, depending on the amount of leeway). Low structural stiffness is usually the starting point for other defects, such as dynamic misalignment, cracked bases and/or supports, resonance.
5- Unbalance: Unbalance occurs when there is an uneven distribution of mass in a rotating machine. Unbalance is a large-scale defect in industries and there are 3 types: Static unbalance, Dynamic unbalance and Combined unbalance. It can be observed in the velocity spectrum with high energy at the machine’s rotation frequency (1x RPM), generally in the radial and vertical directions simultaneously, it can happen in only one direction depending on the type of rotor construction. When correcting unbalance, it is always important to observe the maximum residual allowed for each type of rotor.
Read more about unbalance in our success case “Dynamox identifies circulating pump unbalance”.
6- Gear defect: defects in the gears can affect the correct functioning of the asset, cause malfunctions and performance problems and lead to bearing wear due to the presence of metallic particles in the lubricant. In the spectrum, we can observe the gear frequency (GMF) and we calculate it by multiplying the machine’s rotation frequency (1x RPM) and the number of teeth of the gear analyzed. We treat this spectrum as characteristic of a defect when we have GMF harmonics and/or signal modulations through sidebands. Gear defects can be observed both at acceleration and velocity, and the time waveform and Cepstrum are great tools for detecting this type of defect.
Read more about gear defects in our success case “Internal sensor installation identifies gearbox gear defects”.
7- Lubrication deficiency: when machine parts are not properly lubricated, excessive friction, overheating and premature wear of components can occur. In vibration analysis, we treat lubrication deficiency as the excess or absence of lubricant and contamination by external agents (water, cross-contamination, dirt, etc.). In the acceleration spectrum, we can see more concentrated energy in the bearing resonance region (generally between 2 Khz and 6 Khz). In this context, having quality vibration signals and specific analysis tools are essential to be able to detect the defect correctly, taking into account the defect itself and the severity of this potential failure mode.
Main impacts of mechanical failures
As mentioned earlier, failures are part of industries’ routine and even if they are monitored, they have a major impact on the maintenance sector. This is because any change in the assets directly affects the production process, causing unscheduled downtime, delays in the production line and reduction of asset reliability and availability.
The main impacts caused by mechanical failures include:
Production downtime: this is when a mechanical asset fails and production has to be interrupted. This has an even greater impact when we talk about a continuous production line, where each stage of the process is directly linked to another; so, when part of the line is interrupted, the rest of the process is affected.
High corrective maintenance costs: when an asset needs to be repaired or replaced, this includes the costs of spare parts, labor, downtime, urgent transportation costs, among others.
Operational overload: when mechanical failures occur in one part of production, other parts of the system become overloaded, forcing other components to operate at higher capacity levels, which can lead to more failures.
Safety risks: mechanical failures also pose serious risks to the safety of both the work environment and employees. Especially in sectors such as the chemical industry, oil and gas, among others, which have components that are considered critical.
How to carry out a mechanical failure analysis
There are numerous options for carrying out a mechanical failure analysis, including the use of methodologies and tools that can also help in this process. The definition of these aspects vary from industry to industry, depending on the assets each has and their level of criticality.
Though there are different methodologies, which will be defined by each manager, there is a universal scope that serves as a basis for using them. Within this scope, there are basic questions such as the frequency of occurrence, whether the failure occurred abruptly or gradually, whether the failure began after a change in design, material or manufacturing process, or whether the failure occurred in a specific product.
Below is a detailed guide on how to perform a mechanical failure analysis:
- Define a scope: determine which asset or system is failing and define the objectives of the analysis.
- Collect information: gather all available information about the failure, including technical drawings, specifications, maintenance histories, operating records and previous tests. With the Dynamox solution, you can gather this information through sensing, using wireless sensors, and sensitive inspection, using a routine inspection checklist.
- Make a complete analysis of the event: do a detailed visual examination of the failed component or system. Look for cracks, deformations, abnormal wear, corrosion and damage. The use of tools such as Dynamox’s automated failure diagnosis assists in this process.
- Identify the root causes: here you can use techniques such as failure tree analysis, the “5 whys” analysis or other methodologies to identify the root causes of the failure.
- Make a complete failure analysis report: document all the information, analysis and recommendations in a clear, well-structured report, including images, graphs and tables as needed.
- Implement the recommendations: put the recommended preventive and corrective actions into practice to monitor their effectiveness over time.
- Create a predictive maintenance plan: set up a continuous monitoring system to prevent similar failures in the future. The plan can include regular inspections, sensor installation, trend analysis, and the use of asset management dashboards, such as DynaNeo.
Main failures during asset vibration analysis
Predicting failures as accurately as possible and avoiding unplanned downtime is a common challenge in the maintenance sector, which relies on vibration analysis to diagnose the behavior of equipment.
Vibration analysis is versatile and can be used on the most diverse types of assets (motors, pumps, gearboxes, bearings, among others) but it is important to be aware of some mistakes, which are recurrent and can go unnoticed:
- Not considering the criticality of assets
- Sizing sensors incorrectly
- Using incorrect configurations
- Not setting alarms
- Disregarding important parameters
Not considering the criticality of assets
Some equipment can stop the production process, create safety risks or even contaminate the environment if it fails. Therefore, defining the criticality of assets is a crucial step in identifying how often assets should be monitored.
“Should the equipment be monitored daily, weekly or monthly? A criticality plan acts as a guide for the maintenance team. This point is often overlooked when implementing a routine,” says Victor Brandao, a predictive maintenance specialist at a sugar-energy group.
By detailing the criticality of the equipment, the maintenance team can define data collection cadence. The higher the criticality, the more frequently data should be collected, prioritizing the availability of the most important assets. Therefore, considering the criticality of assets plays a crucial role in the availability of a production plant, avoiding unplanned downtime.
Sizing sensors incorrectly
Inadequate sizing can affect the results of asset monitoring. In a gearbox that contains four shafts, for example, it is important that monitoring considers all of them. On the other hand, in equipment such as small bearings, it is not necessary to monitor all the shafts, as the equipment’s characteristics do not require a high level of analysis points.
In this context, understanding and having a deep knowledge of how the monitored assets work helps us to understand the crucial aspects to prevent failures and accurately size the sensor.
Using incorrect configurations
Each asset is unique and requires a specific setup in a specialized solution for failure analysis and prognosis. This is why you should avoid using a single configuration for all equipment, disregarding the type of operation, rotation and mounting position. Differentiating between the parameters of a motor and a gearbox, for example, is crucial to avoid inaccurate diagnoses.
Duplicating parameters can be useful for similar equipment, but it must consider the specific characteristics of each one in order to guarantee reliable data. This way, spectrum generation will be of higher quality, preventing failures from being detected in analyses.
“Only those who have reliable data truly monitor their assets,” stresses Alisson Moura, Dynamox’s technical consultant.
Not using sensors that are properly mounted and in good condition
Avoid collecting data under random conditions of rotation or load, without keeping the location or position in the measurement history. In this sense, try to always maintain the best possible standard between measurements, preventing conditions from changing.
On motors, for example, it is essential to avoid the side of the junction box when mounting sensors. In equipment that has a frequency inverter, it is important to create a rotation pattern for the data collection times. This way, the history generated will be more reliable, providing accurate analysis.
Not setting alarms
Another common mistake in vibration analysis is to create a standard alarm for all equipment, and not adjust it regularly over time. Each machine has its own vibration signature, making it possible to identify trend curves. A specific motor, for example, can have different vibration values, even if it has similar characteristics to other assets.
Thus, the definition of alarms should follow the pattern of individualized operation, avoiding setting up generic alerts. A routine for fine-tuning these warnings based on optimal operating history helps the maintenance team to visualize the health of the asset tree as a whole, improving productivity.
Disregarding important parameters
Have you ever measured in an axial direction only? One of the most valuable aspects in vibration analysis is to consider all the parameters involved in an asset. That is why it is also important to consider the acceleration and envelope spectra in measurements, for example.
By avoiding the errors described, your maintenance team can achieve even more effective results through sensing carried out using the best market practices in vibration analysis. By avoiding errors, it is possible to reduce operating costs, detect failures early and avoid unscheduled maintenance downtime.
How to increase asset availability
After talking about the main mechanical failures in the industry, their impacts and how to carry out a complete analysis to take the right actions, we also need to talk about asset availability, since both go hand in hand in an efficient maintenance process.
Asset availability is the ability of an asset, be it a device, machine or piece of equipment, to work and perform its intended function when needed. This is particularly relevant when we talk about the industrial sector, which operates with production lines and with critical assets, whose failure or unscheduled shutdown can lead to losses, accidents and catastrophic plant downtime.
The availability of an asset is calculated using variables that include total operating hours and total planned operating hours. Their ratio generates the percentage that indicates how long an asset is available for use in relation to the total time. To make this explanation a little easier, check out the image below with the formula used:
Once the calculation has been made, it is possible to identify how efficiently your asset is working and how likely it is to negatively affect a production process, for example. Therefore, the ultimate goal is to always work to ensure that this percentage is high, guaranteeing greater operational efficiency.
For increased availability to really happen, there are some strategies used by managers that allow for the complete monitoring of these assets, reducing the likelihood of unexpected failures.
Check out some of the main strategies:
Maintenance Planning: Developing a comprehensive maintenance plan that includes regular predictive maintenance schedules is key to starting the process of following up the indicators needed to maintain a healthy asset plant.
Failure Analysis: As mentioned above, performing detailed failure analysis to identify root causes and implement corrections to prevent recurrences is essential when it comes to increasing availability.
Predictive maintenance: Predictive maintenance is a strategy that ensures asset monitoring based on the systematic application of analysis techniques. It uses centralized supervision or sampling and aims to reduce preventive maintenance to a minimum. It is generally applied with the aim of predicting and avoiding failures in machinery and equipment.
It is based on continuous monitoring and data analysis to work ahead and identify problems in advance, avoiding potential unplanned downtime. Predictive maintenance uses techniques based on monitoring the condition of assets, bringing benefits for efficient and assertive maintenance management.
Remote Monitoring: The use of remote monitoring systems to follow up asset performance from distant locations and take preventive action based on real-time data.
Asset Management: Use asset management systems to monitor the condition, maintenance and history of each asset, helping to make informed decisions.