Each industrial park has its own story and is composed of different types of machines and equipment, with mechanical failures being “common” occurrences. It can be said that machines not only give signs but also warn, if sensorized, when they are about to fail.
This type of occurrence generates numerous delays in the industrial park, including unplanned expenses on spare parts, labor, and sometimes even production stoppages.
Machine failures occur for various reasons, some of which may be more difficult to detect, highlighting the importance of continuous monitoring of assets.
The loss of usefulness of machines and equipment originates from three main sources:
- Obsolescence;
- Degradation or wear of component surfaces;
- Accidents.
Component wear is by far the leading cause of machine and equipment unavailability and also a source of increasing vibrations.
In this text, we will discuss in detail the most common failures caused by vibration. Keep reading.
POTENTIAL CAUSES OF MACHINE FAILURES
Increased vibration and excessive heating are signs that something is wrong. In the case of atypical vibrations, the main sources are defective bearings and gears, electrical and mechanical failures in motors, problems caused by misalignments, imbalances, or unstable bases, bent or deformed shafts, pulley or belt failures, mechanical looseness, aerodynamic or hydraulic issues, and so on.
In addition to abnormal vibration and heating, other indicators of failures include water and oil leaks, corroded pipes, abnormal odors, and sounds.
Lack of lubrication or improper lubrication, and failure to quarantine when recommended, can also cause failures. Improper operation or handling of machinery can result in damage to internal parts and subsequent failures.
Furthermore, lack of maintenance or improper maintenance can lead to accidents or even the breakdown of machinery, causing injuries to the operator.
IDENTIFYING FAULTS IN YOUR INDUSTRY
Identifying faults begins with a trained team. In addition to selecting qualified candidates, team training is a process that never ends. To get the best out of the machine operators and maintenance team, a continuous learning process must be established.
There is no one-size-fits-all formula, but it involves retaining knowledge, that is, the learning absorbed and shared within the organization. Detailed descriptions of processes, whether machine operation or maintenance, should be easily accessible and kept up to date.
With the hustle and bustle of daily life, is it possible to find time to think?
Encouraging the capacity for fault analysis for maintenance personnel should be a priority. Prioritizing the analysis of the most relevant problems and systematizing this procedure will generate benefits for employees with diverse roles and experience.
Root cause analysis is a problem-solving method that involves investigating an incident, failure, or potential problem. However, a criterion or trigger is needed to activate the root cause analysis technique. This trigger will vary over time and from industry to industry.
The root cause analysis method can be used when:
- An unexpected event happened causing worker’s injury or death;
- A situation of unacceptable risk or repeated failure occurs;
- Machine downtime for a specified period and the cost associated with it. For example, downtime exceeding two hours.
SOLVING FAULTS IN YOUR INDUSTRY
Identifying the root cause of the problem is not enough; the solution must be planned, executed, and monitored to verify the effectiveness of the intervention. Just as potential faults have varied causes, their detection is possible through routine inspections or may require the use of specific techniques.
Industries establish their approach to maintenance, which typically includes corrective maintenance, i.e., allowing it to break down to repair it, and preventive maintenance, which involves scheduled maintenance over time, usually recommended by equipment manufacturers rather than initiated by the administrator.
The increased competitiveness of the industry as a whole has been demanding more advanced steps in terms of maintenance, with the main goal of reducing costs, increasing machine availability, and improving the reliability of delivery deadlines and product quality.
This is where predictive maintenance or reliability-centered maintenance of machines and equipment comes in. Some of the predictive maintenance techniques, as well as the responsibilities of reliability engineering, can be found in this link.
There is a reason for adopting the best maintenance strategy for each type of equipment. And it is directly related to the use of resources, such as spare parts and labor allocation, as well as considerations about the risks that failures in critical equipment pose to the organization, due to production stoppages, risks of accidents involving employees or the environment.
How to Optimize Fault Diagnosis in Assets?
The truth is, inefficient maintenance strategies can occur in industrial operations. Consequently, equipment failures become recurring events. Here are two important points:
Identify the root cause of the problem:
Record the occurrence and then check the equipment’s inspection history. Additionally, review the checklist or daily pre-use inspection, and see if there were any reported symptoms or anomalies.
Next, review the asset’s usage procedures. Also, reassess the maintenance plan and propose changes if necessary, such as implementing a blocking action.
Avoid intuitive actions and pay attention to details!
Improve your diagnostic processes:
Organize the information and data obtained in the previous step to get to the root of the problem. In this stage, look for tools that can help you facilitate the analysis of this data.
Once the fault has been observed, analyzed, and diagnosed, create an action plan to prevent the recurrence of the failure. Also, establish a deadline to verify the effectiveness of the actions taken.
After completing the analysis, share the results of this investigation with the team to prevent the problem from recurring.
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BREAK THE PARADIGM WITH SPECTRAL AND TEMPORAL ANALYSIS
When it comes to vibrations, each component of a machine or equipment vibrates differently during operation, generating a unique impression on the frequency spectrum.
Thus, spectral analysis is one of the predictive maintenance techniques used to determine the condition of the machinery under evaluation because it can identify abnormalities in component vibration.
These abnormalities can, in addition to indicating failures in early or advanced stages, pinpoint the location of affected components, indicate the cause or source of the problem, and suggest trends that may indicate how soon the identified problem will become critical.
In general, conducting spectral analysis, obtained through FFT (Fast Fourier Transform) or Fast Fourier Transform, requires the analysis of specialists.
Read about Spectral analysis: how to apply it to analyze vibration in industrial assets. (dynamox.net)
It is a well-known fact that these specialists are expensive, and their time is limited to perform spectrum collections. Therefore, often these collections are done by sampling, which does not necessarily provide a realistic picture of the condition of a particular industrial park.
Continuous Time Monitoring
In addition to spectral analysis, continuous time monitoring of vibration (and temperature) by devices with acceleration (and temperature) sensors is also useful.
This monitoring generates time series indicating the trend of the condition of that component over hours or days, suggesting to the maintenance team further analysis with the performance of spectral analysis and intervention, if pertinent.
Following the logic of the maintenance strategy adopted for each machinery or equipment based on its criticality, due to its simplicity and low cost, Industry 4.0 technologies allow monitoring of several points in the same equipment continuously, recording time series, and performing spectral analysis whenever demanded at that monitored point.
This is the value proposition of Dynamox’s solution: a Bluetooth data logger with acceleration and temperature sensors, a wireless device with a battery life of three years that performs spectral analysis and allows data interpretation in the comfort of a room away from the factory floor. Contact us to know more!
Also read Dynamox’s sensors identify failures in a conveyor belt pulley side frame