Getting More out of your Product Engineering Team
Posted By: yieldWerx on September 2, 2016
Semiconductor wafer manufacturing is a long and complex process comprising of several process steps. Normally it takes somewhere between five weeks to several months to manufacture a fully functional IC that can be shipped to the customers. During the manufacturing phase, each process node generates parametric and process data to help monitor and evaluate operational efficiency and health of the wafer being processed.
The collection, storage and analysis of the data becomes challenging for most of the systems as several hundreds of electrical, mechanical and other underlying parameters are being measured for each individual chip. The statistical analysis becomes even more difficult if we take into consideration the huge data sizes containing thousands of ICs being fabricated on a few lots and thousands of lots per product.
The Product Engineering Team has to spend a considerable amount of time just to collect, store and clean the data that can be used for statistical modelling and analysis. This shifts their focus from high value activities to a low value activity such as collecting raw data from multiple sources including the process data from Manufacturing Execution System (MES). It is imperative to document and monitor the process and parametric data at every node as some yield loss might happen at any step as the wafer progresses from one step to another. The job becomes critical for the product engineers as they have to perform various statistical and yield analysis to pinpoint the root cause of defects that are impacting the yield and interfering with the production schedule. If the engineering team is spending time on data collection, cleaning and analysis, they will miss out on other key activities like incorporating customer feedback in the product and making adjustments to the design and production cycle, transitioning of product from sampling stage to high volume production stage and lastly ensuring cost-effective and timely production of the products.
Product yield is no doubt an important KPI of product engineering team but how to make sure that they have enough time to focus on other high value activities too?
A complete end-to-end yield management solution (YMS) like yieldWerx let the product engineers focus on high value activities and perform the data cleansing and management functions automatically in the background. The tool can be connected directly to the MES and data can be loaded to its cloud servers either in real time or scheduled for specific time intervals. The YMS then automatically maps the raw data to its corresponding wafer, lot, facility and develops the associated genealogy and stores it in a central database for analysis. The product engineer can then perform required analysis and generate reports with the help of simple clicks and the intuitive user interface of yieldWerx. One of our customers, QuickLogic has reported saving up to 90% of their product engineering time because of elimination of noise from their data sets, allowing engineers to perform analysis quickly and improving their productivity. The engineers are now able to analyze characterization data in as little as 30 minutes and prepare a dashboard of reports for enterprise-wide quick decision making because of powerful data management capabilities of yieldWerx.
If you are interested in how you can get more out of your product engineering team without compromising on quality and yield, contact us today and schedule a demo. Our sales and technical team will get in touch with you to highlight the increased productivity that your team can achieve by deploying yieldWerx.