Welcome to Volume 23, Number 2 of the FabTime Cycle Time Management Newsletter. In this relatively brief issue, we have some highlights from Jennifer’s LinkedIn posts, a FabTime software tip of the month about using our new on-chart drill-down capability, and subscriber discussion about defining the components of cycle time and measuring fab linearity.
Our main article this month was inspired by a new subscriber to the newsletter. We always ask people who fill out subscription requests on our website “What is the most urgent cycle time issue occurring in your fab?” This subscriber wrote: “Ramping up starts and maintaining cycle time.” We realized that although we’ve written in the past about what to do to during an industry downturn, we had never written an article about what to do to protect cycle time during a strong upturn. We decided to remedy that omission. We share tips for squeezing additional capacity out of an existing tool set, deciding where to add capacity, and spending money in other areas beyond tools, all with an eye to keeping cycle times under control. We welcome your feedback, as always.
Welcome to Volume 23, Number 1 of the FabTime Cycle Time Management Newsletter. We hope that the new year is treating you all well. In this issue we have a question assessing potential interest in a multi-company session of our cycle time management course, an announcement about the FOA Collaborative Forum (in person as of this writing), and some highlights from Jennifer’s LinkedIn. We have a FabTime software tip about the use of our new search bar. We have subscriber discussion about various topics, including a recommendation for a new blog on Factory Physics that we believe subscribers to this newsletter will enjoy.
We’ve talked many times in this newsletter about using queueing model-based operating curves to illustrate the impact of various factors on wafer fab cycle time. In our main article this month, we discuss the idea of populating these operating curves with data from real fabs. Reasons to do this include estimating the impact on cycle time from changes in utilization or other parameters and identifying places in the fab where the cycle time is worse than might be expected given the known characteristics of a tool group. We discuss techniques and pitfalls of collecting data for this effort. We show a detailed example from our demonstration server and then highlight possible uses of the operating curves. As always, we welcome your feedback.
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