How to use an FMECA or RCM Analysis to Determine What Spares to Stock
Determining which parts of stock can be a very overwhelming process. As such, many choose to blindly accept the OEM or Manufacturer’s recommendations. And why shouldn’t they? The OEM has many years of experience in building these types of assets and supplying spares, right?
One of the common issues with following the OEM recommended spare part lists, is that there are often there are parts that may not be used, too many of some parts and not enough of others. Why is this? The operating context of the asset is different between end users, and the OEM has to make recommendations to cover all end users (sound familiar like recommended PMs?).
Also, an OEM will typically still have a time-based PM program, in which components are replaced based on time, not a condition. So, when an end user of the asset leverages CBM or PdM, they may end up with excess parts as they are changed on condition, not time. So how can organizations determine which parts should be stocked? They should leverage the same tools that are used to establish a maintenance strategy.
How A FMECA Will Determine Which Spares To Stock
Performing an FMECA (or using another tool RCM, PM Optimization, FMEA) will provide some insights into understanding the potential failure modes, mechanisms, consequences of the failure and the risk mitigation strategy. These risk mitigation strategies may include time-based maintenance, CBM/PdM, redesign or Run to Failure (RTF). Each one of the strategies will drive different thinking to spares stocking.
By conducting the FMECA, an understanding of the failure mode and mechanism, i.e., the part wears out; the part fails randomly, the part fails on start-up, will be established. This will allow the analysis team to determine if the component being discussed, needs to be held on-site (infant mortality), or if it can be ordered on demand (definitive wear out, or random failure that can be detected). The team may also establish that a safety stock needs to be held (based on the severity of the consequences or lead time of the part) for emergencies and all other work has the parts ordered on demand.
If run to failure (RTF) was selected as the mitigation strategy, the consequence of the failure and the lead time of the part must be considered to determine if the part will be stocked.
Lastly, the team needs to review the full analysis of common components and determine if any components have different failure mechanisms. This may lead the time to consider a combination of stocking strategies, such as utilizing on-hand stock for any emergencies, but on-demand work has parts ordered specific to the work order.
How To Determine The Stocking Quantities Of Spares
Once the analysis has determined the stocking strategy for each component in the analysis, the min, max, safety stock and Economic Order Quantity, needs to be established.
To establish these values, the analysis team needs to review the full analysis and look for any common parts. This will allow the team to consider the big picture and understand the quantities and estimated usage of the parts. With an understanding of these quantities, common formulas can be used to determine the Min, Max, Safety Stock, and EOQ. These formulas can be found in the posts below;
The team may also have to consider other assets with the same parts. In this, the values determined will need to be added to the current values established. This will ensure that all assets have the right amount of spares are available. However, if the previous values were not determined through a scientific approach, be cautious about adding the values, as it may inflate the required stock.
Optimize the Spares Holding
After these spares to stock have been established, it will require periodic review and optimization. After a period such as one year or 2 years, usage data will be captured. Usage data combined with failure data will allow the analysis team to use Weibull Analysis to confirm the failure mechanisms and potentially change the stocking strategy.
Also, the usage values and lead times will allow the analysis team to optimize the Min, Max, Safety Stock and EOQ, based on real-world data. This is vital as the lead times, and usage values may fluctuate greatly. Using a statistical approach, the balance between the risk of stock-outs and having too much stock can be achieved.
Putting It All Into Action
Using an FMECA (or other process driven approach) is critical to the success of any reliability improvement program. It is also vital to establish the correct spares to stock. Without a process-driven approach, the spares being stocked are driven by gut feel and not data.
What is stopping you from using the FMECA to establish your required spares? If you need assistance in understanding and applying the FMECA and other reliability tools, please contact jkovacevic@eruditio.com for additional information.
I’m James Kovacevic
Principal Instructor at Eruditio
Where Education Meets Application
Follow @EruditioLLC
Follow @ReliableJames
Follow @HPReliability
