One of the most important manufacturing KPIs that helps you benchmark your processes is First Pass Yield (FPY). First Pass Yield can help you determine how effective your production lines are and find areas for improvement so you can lower costs.
In this article, we’ll explore what First Pass Yield is, how to calculate it, and how manufacturing Industrial IoT services can help optimize this useful metric.
What Is First Pass Yield?
First Pass Yield (FPY) is a quality metric used to determine the number of products that pass through the manufacturing process without needing any rework or repair. In simpler terms, FPY tells you how many units were produced correctly on the first try.
This metric is important because it directly reflects the efficiency of your production process.
A high FPY means your manufacturing process is running smoothly with minimal waste.
A low FPY suggests there may be issues, such as defective materials or inefficient workflows, that you need to address.
FPY is often used in conjunction with other quality measures like Overall Equipment Effectiveness (OEE) and Defects Per Million Opportunities (DPMO). Together, these metrics give your team clear insights into what your business is doing well and where it can improve.
Why Is First Pass Yield So Important?
First Pass Yield is important for manufacturers because offers invaluable insights into the efficiency of your production lines. Improving FPY has the following benefits:
- Reduced production costs
- Fewer defects
- Less rework
- Increased efficiency
- Meet quality standards more consistently
- Happier customers
- Fewer returns and complaints
FPY also plays an important role in lean manufacturing principles, which help manufacturers reduce waste and clutter.
How to Calculate First Pass Yield
Here’s how to calculate First Pass Yield.
First Pass Yield formula = (Number of good units produced / Total number of units produced) x 100
For example, if you produced 1,000 units and 950 of them passed inspection on the first try, your FPY would be:
First Pass Yield = (950 / 1000) × 100 = 95%
This calculation helps manufacturers track the percentage of products that do not require any additional work or repair after the first production cycle. It is a straightforward way to measure the quality and efficiency of a production line.
Factors That Affect First Pass Yield
Several factors can affect FPY, both positively and negatively. When troubleshooting FPY, consider these questions:
- How Is Your Material Quality? Using substandard or inconsistent materials can lead to defects in the final product, reducing FPY.
- Are Your Machines Appropriately Calibrated? Poorly maintained or incorrectly calibrated machinery can cause product inconsistencies.
- Are Your Operators Skilled? Employees who lack proper training or experience may produce defective units, impacting the overall yield.
- What’s Your Process Design Like? An inefficient or overly complex process can result in errors that affect FPY.
How IIoT Platforms Can Improve First Pass Yield
In recent years, the integration of Industrial Internet of Things (IIoT) technologies has transformed the way manufacturers approach quality control. IIoT platforms provide real-time monitoring and data collection so manufacturers can quickly identify issues and make data-driven decisions to improve FPY.
In case you don’t already know, IIoT software collects data sent by IIoT devices and sensors strategically placed throughout your facility and equipment. IIoT devices measure metrics like speed, temperature, velocity, pressure, location, and more. This data is sent to your IoT platform which contains dashboards for easy reading.
While IoT platforms like ProphecyIoT help manufacturers automate and improve all areas of their factory, here’s how they can help improve First Pass Yield specifically.
1. Real-Time Monitoring
IIoT-enabled devices continuously monitor machines and production lines, providing instant feedback on performance. If a machine is operating outside of your specified parameters, alerts are sent to your team so they can fix problems before defects happen. It’s a proactive strategy that saves you rework in the long run.
2. Predictive Maintenance
One of the most significant benefits of IIoT is its ability to predict when machinery might fail or need maintenance, which we call predictive maintenance. IIoT systems use the data collected by sensors to predict when parts need to be replaced or when machines are likely to break down. When machines are running at their peak, you can expect less downtime and a higher FPY.
3. Quality Control Automation
IIoT systems can be integrated with automated quality control tools, such as vision systems and sensors, that inspect products during the production process. These tools can detect defects in real time, allowing manufacturers to quickly identify the root cause and make adjustments before more defective products are created.
4. Data-Driven Insights
IIoT platforms collect vast amounts of data from various points in the production process. By analyzing this data, manufacturers can uncover trends, inefficiencies, and patterns that might be affecting FPY.
For example, if one particular machine consistently produces lower-quality output, it may be a sign that it needs to be recalibrated or replaced.
Boost Your FPY with ProphecyIoT’s Solutions
You cannot ignore the importance of First Pass Yield in manufacturing. Improving FPY can lead to higher efficiency, lower costs, and better product quality. Learn to leverage IIoT technologies and gain greater visibility into your production processes, make data-driven decisions, and take proactive steps to raise your FPY.
Not sure where to start? Schedule a consultation with our IoT experts today.
