Do you know how to correctly identify the failures of your company’s assets? If you are looking for solutions to help you analyze those failures, we are here to help.
First of all, it is necessary to understand the whole fault analysis process. This process consists of analyzing why a certain problem occurs, its degree of severity, and finding the root of that failure.
This analysis can be used in various ways and each analysis method will have a better functionality according to the situation that is applied.
Therefore, the professional who is managing this analysis process must know how to select these tools and must know how to combine them to reach a conclusion and propose a solution with greater efficiency at a lower cost.
So, we are going to discuss the top five fundamental tools and methods used in most failure analysis techniques.
1. Analysis: The 5 Whys
Unexpected failures often have various causes and rarely have the same reason. However, when a failure occurs, we always ask ourselves: “Why did this happen?”
The whys methodology consists of a series of questions that help to understand the root of the problem. The answer to the first question generates a second question, which will have its own answer and which will generate a third question. That is the main system of this methodology.
With the questions already formulated, it is possible to be oriented to know the root cause of the situation. The average number of questions to understand the possible start of the problem is 5 questions.
It is important that we continue to ask ourselves “why” questions until we find a plausible root cause for the failure in question. The questions can be helpful in any equipment availability calculation.
2. Analysis: Ishikawa Diagram (Fishbone)
The Ishikawa diagram method, also called the Fishbone diagram, is a graphical tool used to identify possible causes of the problem and which category of variations in the process represents the greatest source of variability in the output.
The methodology consists of a system for categorizing causes, either by function or by sequence in the process. In each category the potential causes are listed and tested for validity using evidence or another analytical tool.
In this way in the diagram we have a central spine and the ramifications of the causes that form something similar to the skeleton of a fish.
3. Analysis: Logical Fault Tree
The logical fault tree is nothing more than an organized and logical way of correlating faults and causes. This method allows discovering the physical, human and latent roots of a failure.
To use this tool we must start with a problem statement describing the incident – the functional failures. After categorizing and detailing the functional failures, a logical tree must be designed according to the events, correlating them with the failures.
The second stage is to list the failure modes. This process is repeated until the physical roots are reached. Additional interactions are necessary to reach the human and dormant roots.
4. Analysis: Pareto Chart
The Pareto diagram methodology is used to quantify and generate conflicts between the causes of an event and its determined effect. That is, from this diagram it is possible to see which are the causes that most impact the availability and reliability of the equipment.
The Pareto chart is a graphical representation of the process problems in the ranking order of what is most frequent to what is least frequent. This diagram illustrates the frequency between the types of failure or effect.
Using Pareto analysis, you can decide which event needs to be addressed with priority to be solved.
5. Analysis: AI Diagnosis
One of the current ways of analyzing equipment failures is through the constant monitoring of equipment and data processing. Many organizations use CMMS software to manage their maintenance tasks and gather data used in many types of failure analysis.
With a model based on the internet and artificial intelligence using platforms, it is possible to monitor basic and complex aspects of assets, thus having much more precise control and diagnosis of the causes and effects of failures.
In addition to creating a consistent history of information on equipment maintenance and condition, data analysis, when done well, manages to detect failures when they are in the initial phase, allowing the maintenance team to act before the failure occurs.
In other words, the analyzes are done when there is still the possibility of controlling the situation.
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