The best way to improve production yields and efficiency is to gain full visibility into the manufacturing process.
Enhanced visibility allows you to fix potential issues, find ways to optimize, and implement processes that streamline every aspect of the manufacturing process. Despite this, increasing demand in most industries means manufacturing is too complicated to be perfect, and even the largest enterprises must plan for the occasional defective unit.
For these reasons, companies must understand how many items are going through their production cycles with defects. Faulty products obviously imply wasted materials and labor, but knowing the exact incidence of these issues will help you thoroughly plan out how you can improve your production processes to minimize future defects.
That’s where the industry metric known as “first pass yield” (FPY) comes into play. This article will discuss the first pass yield meaning, the calculation involved, what meanings and intel you can gather from it, and some next steps your business can take to improve upon it.
First pass yield is a key performance indicator that demonstrates the quality and efficiency of a manufacturing process. This manufacturing intelligence figure specifically tells you the proportion of finished units that pass inspection during product testing.
The higher the FPY, the more consistent and reliable your process. Managers usually measure first pass yield for a certain period or output, such as an order or batch.
The first pass yield calculation is defined as the number of “good” units divided by the total number of products going into the production process. The figure is typically presented as a percentage.
For example, say that a batch of 100 laptops come out of the factory. If 96 of them pass testing with no defects, then the FPY is 96%. The remaining 4 must either be thrown out or recycled, both of which result in wasted resources for the company.
If you want to calculate FPY for multiple production cycles, calculate the FPY for each individual process and multiply them all together. The more processes you have, the higher the chance you will receive more defective units.
The manufacturing yield formula must be understood in context. There are more steps involved in the calculation of the figure, the limitations of it, and what you can do with it.
You need the right data to input into the formula, so proper data collection strategies are necessary for an accurate reading. Get verifiable data by using collection tactics that are reproducible across the organization. The more reliable this information, the more accurate the FPY will be.
Remember that FPY changes drastically based on several factors, including labor, the cost of raw materials, the initial investment, and processing costs.
One question you must ask is: how exactly do I identify defective units? There are many unknown anomalies in manufacturing. In addition, it’s not uncommon for front-line workers to fix manufacturing problems immediately on the factory floor so that they don’t show up in your FPY calculation.
First pass yield demands a solid method for measuring and tracking defective units to be accurate.
A major part of a first pass yield analysis is finding ways to raise it. The metric measures your success and tracks your progress in optimizing the production cycle. Building a plan is therefore the best course of action for taking advantage of first pass yield.
Once you have your current FPY, decide on a target for the future and calculate how much you can save each production cycle by optimizing your processes. This information is vital to getting enough staff members and upper management on board.
There’s no use in having a formula if you don’t take action on it. What can you do to capitalize on manufacturing metrics?
Boosting first pass yield is a long process that requires extensive collaboration with the rest of the organization. Bring up how much you will save by boosting FPY by a certain amount to keep everyone engaged with the process.
It’s no secret that companies are looking to optimize every stage of the manufacturing process. Whether that’s through the first yield process or later on down the line, manufacturing intelligence is one of the best ways to accomplish this.
Are you interested in seeing how predictive analytics can further optimize and improve the efficiency of your manufacturing process? Book a discovery call today to see how Vanti Analytics has helped other top manufacturers boost production, faulty unit detection, and more.