First Pass Yield (FPY) is a crucial measure of production efficiency that can greatly impact a company’s bottom line. A high FPY signifies effective management of time, resources, and labor, leading to fewer defective goods. Continue reading and learn how you can calculate first pass yield, and how you can improve your score.

Quick Reminder on FPY

First Pass Yield (FPY) serves as an essential yardstick for assessing a company’s manufacturing prowess. It represents the proportion of flawless product units a company produces, aiming for a high FPY score indicative of superior, error-free goods production. This achievement signifies efficient resource utilization and swift customer demand fulfillment, with the metric’s tracking revealing progress towards goals and efficiency enhancements over time.

A low FPY score can signal potential problems with a company’s manufacturing procedures, equipment, or raw materials, leading to wasted final products or reworked items. This scenario results in squandered time, labor, and resources. Conversely, a high FPY score suggests robust manufacturing processes, effective machinery, and adequate raw materials. The consistency of a company’s FPY score uncovers the dependability of its manufacturing systems, a crucial aspect in timely order fulfillment, fostering customer loyalty, revenue generation, and sustaining business operations.

Related:Explained: First Pass Yield and How Manufacturers Can Improve It

How to Calculate First Pass Yield in Detail

Gathering manufacturing data can help leaders make informed decisions. Calculating first pass yield is a straightforward way to gain valuable insights about production. Follow these steps:

Select a time period to measure first pass yield.Common options include a production cycle, day, week, month, quarter or year. A longer period like a quarter or year provides a larger data set, which can increase statistical accuracy and smooth out anomalies. However, also consider tracking first pass yield over shorter periods to quickly spot any changes. Factor in seasonal variations – for example, first pass yield may dip during busy periods if quality control is rushed.

Count the total units produced before the quality control phase.This represents all units that entered the production process, including defective ones. Use inventory management software to efficiently track units through production stages. Cloud-based systems allow access from anywhere. Automated tracking is faster and more accurate than manual methods.

Count the good units passing inspection that are approved for sale.These units meet company quality standards and legal regulations. Approval often occurs during a quality assurance process after production. Quality assurance involves inspections, testing and audits to verify standards are met before sale.

Insert the total units and good units into the first pass yield formula: Good Units / Total Units. Then multiply by 100 to convert to a percentage, which is easier to understand and convey. 

Consider calculating related metrics, like percentage of defects, units needing rework, units scrapped, and customer returns. Defect analysis helps identify improvement opportunities – for example, targeting equipment with high defect rates. Minimizing scraps and maximizing reuse through rework reduces material waste. Tracking returns helps address quality issues lowering customer satisfaction.

Calculate First Pass Yield Examples

We calculated for you some manufacturing-specific examples for first pass yield:

Example 1

Maria manages a factory that produces bicycle frames. She wants to measure the first pass yield for the past month’s production run. Here are the calculations:  

Total frames produced: 2,500  

Frames passing Quality Control (QC): 2,300  

First pass yield = (Frames passing QC / Total frames produced) x 100

First pass yield = (2,300 / 2,500) x 100  

First pass yield = 92%

This shows Maria that 92% of the bicycle frames produced were free of defects after the first production pass.

Example 2

John owns a small machining shop that makes automotive parts like pistons and valves. He wants to improve his process efficiency by increasing first pass yield. Here are his calculations for last quarter:

Total piston castings produced: 850 Castings passing inspection: 795

First pass yield = (795 / 850) x 100 First pass yield = 93.5%

John uses this data to target reducing casting defects. He adjusts the furnace temperature and improves mold quality. 

After 3 months, his first pass yield is:

Total piston castings produced: 880 

Castings passing inspection: 854

First pass yield = (854 / 880) x 100 First pass yield = 97%

By including the metrics for both periods, we can now see the increase in first pass yield from 93.5% originally to 97% after 3 months. The data shows that more piston castings passed inspection after John made furnace temperature and mold quality improvements.

Example 3

Jane works in quality control at a factory that makes capacitors. She calculates the weekly first pass yield:

Original Week:

Total capacitors tested: 1,200 Capacitors passing QC: 1,152

First pass yield = (1,152 / 1,200) x 100 First pass yield = 96%

One Month Later:

Total capacitors tested: 1,250 Capacitors passing QC: 1,237

First pass yield = (1,237 / 1,250) x 100 First pass yield = 99%

By including the metrics for both the original week and one month later, we can now see how the first pass yield increased from 96% to 99% after Jane shared the data with the production team and they made improvements.

5 Tips to Improve Your First Pass Yield Score

The key is moving from reactive to proactive quality management across equipment, processes, materials, employees to systematically improve first pass yield. For that reason, take a look at some tips focused to increase your first pass yield:

• Perform root cause analysis on defects to identify and address the sources. Look for common factors in defects like machine, material, method, staff skill gaps.
• Optimize preventative maintenance plans for critical equipment to minimize downtime and quality issues from machine wear. Track Mean Time Between Failures (MTBF), Mean Time To Repair (MTTR).
• Implement SPC statistical process control to catch process variations quickly before they create defects. Monitor key process parameters.
• Validate and optimize machine setups, workflows, and parameters for each product to minimize deviations. Standardize procedures.
• Upgrade older equipment and technology to take advantage of quality improvements and automation. Look for quick ROI.
• Partner with suppliers that certify materials to your specifications. Perform incoming inspections to verify quality.
• Institute rigorous quality training programs for employees focused on defect prevention and detection skills. Conduct periodic refresher training.
• Create quality checkpoints for in-process inspection at critical stages. First part inspection can verify setups.
• Digitize production data for real-time first pass yield tracking. Use dashboards to drive quality decisions.
• Implement quality circles and continuous improvement initiatives to engage staff in solving quality issues.

What You Should do Next

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