First Time Yield, or FTY (also called First Time Through or First Pass Yield), is a measure of the number of products that are made correctly the first time they come through the production line. A high FTY is achieved by ready identification of root causes of quality issues that are then quickly rectified at the source. Optimized manufacturing processes must then be controlled so that the high FTY is maintained. Every percentage point of improvement in FTY represents a substantial reduction in manufacturing costs.
In some industries, like automotive, FTY numbers are typically quite high, indicating well-developed, maintained, and measured processes across production lines. By contrast, other industries exhibit low FTY figures. Why? How can manufacturers improve on this?
Reasons for Low FTY
Manufacturers are settling for low FTY numbers because they lack visibility into their operations, are using costly and ineffective testing methods, and haven’t successfully automated quality monitoring of their processes.
Companies that don’t have visibility into their critical manufacturing processes don’t have insight into what quality issues exist within their operations and how to correct them. Those that employ wasteful post-manufacture testing modalities generate needless scrap, invite rework, and delay cycle times, all which limit First Time Yield and have a negative impact on product cost.
The Steps to Improvement
An in-process testing approach means that parts are being tested during rather than after manufacturing, making it easier to identify and correct any quality issues that are identified. Once the quality parameters of a process have been optimized, the monitoring and data-acquisition process can be automated.
Above, illustration of the five-step process for optimizing and maintaining FTY. The dashed blue line indicates the measured FTY, which may initially be artificially inflated by undetected failures resulting from an underperforming test strategy.
Here is a five-step approach to boosting FTY:
MAP the process: Visibility into the complete manufacturing process is essential. As a first step, the entire process should be mapped. Take note of the yields at each section or area in an assembly operation and evaluate the impact that those have on overall product quality.
DEFINE the test strategy: Once the process has been mapped, a monitoring and test strategy must be determined. This is where manufacturers have the opportunity to define a strategy that will reliably identify process abnormalities or defects at each critical process, while there’s still an opportunity to correct issues.
Depending on the industry, traditional quality control involves testing the product at the end of the line, with functional testing, destructive testing, or batch testing. These end-of-line tests tend to be bottlenecks on assembly lines and problems discovered can be costly to correct. Adding automated quality monitoring at each step in the production line reduces the number of defective parts and their cost.
In-process testing, or IPT, can significantly reduce the cost of maintaining quality, based on the premise that the sooner you find a problem part, the less it costs you in terms of materials, rework, lost cycle time, and other activities that contribute to the cost of production. IPT requires the addition of process monitors along the production line to verify that the processes are under control and to collect all process information related to each part.
With IPT, not only is every part verified, but the testing is objective and repeatable. A pass-fail decision is based on data gathered from sensors built into the process machine. One proven IPT methodology is Process Signature Verification, where the complete waveform of the manufacturing process is captured. Rather than a few specific data points, the full complement of data are available for analysis, to identify the cause of issues and to help address them.
DIAGNOSE the failure modes: Driving up FTY is achieved in large part by eliminating the root cause of defects. For example, if incoming materials do not meet necessary standards, the rejection rate rises, is immediately revealed by IPT, and the manufacturer has an early warning of the problem. Defects or deviations from the standard are identified during, rather than after, production and the affected line can immediately be halted and the cause of the problem identified. This saves money by saving time and decreasing the number of scrapped parts, resulting in higher FTY.
OPTIMIZE the process limits: A critical step in boosting FTY is the optimization of pass-fail criteria for testing. Parameters that are too tight result in excessive failures, while loose ones can reduce product quality. By performing a “what-if” yield analysis on a database of stored process signature waveforms that contains a population of both “good” and “bad” parts, manufacturers can eliminate the guesswork and long cycle times of a traditional trial-and-error approach. This method dramatically improves both the speed and accuracy of the optimization cycle but can only be successfully accomplished if you have the data.
MONITOR the process data: Finally, process data needs to be continually monitored to ensure that yields are maintained. This ongoing monitoring also supports continuous process improvement and identification of new failure modes.
Conclusion
In industries like automotive manufacturing, where there’s been widespread adoption of in-process testing and automated process monitoring has been integrated into production lines, FTY numbers are high. In order to improve production yields, manufacturers must have in-depth visibility into their manufacturing assembly processes. Having detailed information collected along each process and traceable to each part can be attributed to an enhanced ability to deal with faults quickly, reducing their impact on production cost, in terms of scrap and rework.
Many companies have found that IPT significantly improves throughput. The benefits of IPT and process monitoring automation pay dividends early on, and facilitate process improvements that boost FTY numbers and, ultimately, save manufacturers money.
Nathan Sheaff is founder and chief executive officer of Sciemetric Instruments. He developed Sciemetric’s innovative Process Signature Verification (PSV) technology, which is currently being used to detect and analyze defects in manufacturing processes across many sectors.