Linking your Process FMEA and Control Plan for Higher Performance: 3 Things to Consider
One of the more frequently asked questions received in Plexus and AIAG FMEA training sessions is, "Why isn't my Process FMEA and Control Plan performing as expected?" The answer to this will vary from organization to organization, however, there are some basic principles to think about when developing your FMEA and moving to your Control Plan to ensure your controls actually address the risks identified in the FMEA. In order to effectively link your FMEA and Control Plans for better performance and more robust controls, here are three things you should consider before you get started:
1. Every line in the FMEA should match to a Control Plan item
Each line item in the FMEA should have a corresponding line item in the Control Plan. Think of it like a conversation; if you say that there is a risk in your FMEA, but you don't have a corresponding control, you're only having half of the conversation. Often times an organization's Control Plan isn't effective because the risk identified in the FMEA is never carried over and addressed by the controls set in the control plan. This seems like a simple enough concept. Yet, a surprising number of organizations fail to achieve this when developing FMEAs and Control Plans. Will it take you time to address each risk in the FMEA? Yes. Will it pay off when it comes to overall performance? Absolutely, yes.
2. Consider your sampling frequency
The second thing you'll want to do is take a look at your sampling frequency. Make sure that the sampling frequency in your Control Plan is representative of the risk identified in the FMEA. For example, maybe you have an operator dependant type of process where there are three shifts and break coverage during each, but your sampling occurs at the beginning of the day and at the end of the day. Six operators have touched that part, and your sampling plan is not robust enough to mitigate the risk. This is something often overlooked, but it can make a big difference when the frequency is appropriately adjusted for the risk.
3. Look at your sample size
The smaller the change or shift in dimensions of the product, the more samples you'll need to take. Let's say that in your manufacturing process a tool breaks and it causes a massive shift in the dimension. You may not need many sample pieces to detect the shift . Now let's say the tool wears slowly, causing small shifts in the dimension. You'll need a much larger sample size to see a small shift.