Failures of any kind are not tolerated in today’s global economy. Identifying and eliminating - or reducing - them as early as possible saves money and time, besides improving the quality and reliability of a product.
Failure Modes and Effects Analysis (FMEA) is a methodology for analyzing potential reliability problems early in the development cycle where it is easier to take actions to overcome these issues.
This methodology is used to identify potential failure modes, determine their effect on the operation of the product, and identify actions to mitigate the failures. A crucial step is anticipating what might go wrong with a product.
There are several benefits of using FMEA, such as:
- Improves product/process reliability and quality;
- Increases customer satisfaction;
- Early identification and elimination of potential product/process failure modes;
- Emphasizes problem prevention;
- Minimizes late changes and associated cost.
The most known and used types of FMEA are the Design FMEA (DFMEA) and the Process FMEA (PFMEA). The DFMEA focuses on components and subsystems. On the other hand, the PFMEA focuses on manufacturing and assembly processes.
The basic steps to perform a FMEA are:
- Assemble the team;
- Establish the ground rules;
- Gather and review relevant information;
- Identify the item(s) or process(es) to be analyzed;
- Identify the function(s), failure(s), effect(s), cause(s) and control(s) for each item or process to be analyzed;
- Evaluate the risk associated with the issues identified by the analysis;
- Prioritize and assign corrective actions;
- Perform corrective actions and re-evaluate risk;
- Distribute, review and update the analysis, as appropriate.
The most common method to evaluate the risk is the Risk Priority Number (RPN), calculated multiplying the severity, occurrence and detection.
Severity (SEV) is a rating of the severity of each potential failure effect. Occurrence (OCC) is a rating of the likelihood of occurrence for each potential failure cause. Detection (DET) is a rating of the likelihood of detecting the failure cause.