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The FabTime Cycle Time Management newsletter is a forum for introducing and discussing best practices in wafer fab cycle time management.
In our main article this month, we have a special year-end write-up of industry resources on cycle time management for wafer fabs. We were inspired to put this together by various inquiries from subscribers about where to get started in learning about fab cycle time, and what to do to start a cycle time improvement project. People asked us about papers, conferences, software products, links, tutorials, and the like. Naturally, many of the resources that we have to suggest come from FabTime’s own website, since we have been working in this area for seven years. But, in our travels, we’ve also come across other useful industry references, books, conferences, and sources for papers, and we wanted to share some of those with you. We hope that you find this article useful. We welcome your feedback and additional suggestions.
In this issue, we have a FabTime software tip of the month concerning use of a new priority-based alert. We also have two subscriber discussion questions one about integrated metrology, and one about staffing models. We’re pleased to introduce both topics, because subscriber discussion has been rather sparse lately, and we hope that some of you will choose to contribute. We also have a response to last month’s article about “7 Things You Should Know about Wafer Fab Cycle Time.”
In our main article this month was discuss seven things that we believe people need to understand in order to improve wafer fab cycle times. We focus on high-level items, areas through which fab management can have a significant influence. These include utilization, tool redundancy, equipment downtime, product mix, staffing levels, access to performance data, and selection of metrics. There are many other factors that influence cycle time in wafer fabs, too, of course (batching, setups, hot lots, and holds, just to name a few). But we think that the areas highlighted in this article are worthy of your time and attention. We welcome your feedback.
In this issue we also have a FabTime-related announcement, complete with a glowing endorsement from one of our newer customers. We also have one last conference announcement for the year. Our software user tip of the month concerns hiding chart legends on your FabTime home page. We have one subscriber response to last month’s article about lot release policies. We’re hoping that subscriber discussion levels will ramp back up in the future.
In our main article this month we discuss several ways that operating practices in fabs contribute to arrival variability, and hence to cycle times. These include releasing lots into the fab in large batches, forcing full batches on lightly utilized batch tools, and using carts for manual transportation of lots between steps. Each of these practices directly increases fab cycle time. We recommend relatively low-cost changes that, if implemented, can help to smooth the flow of WIP through the fab, and make cycle times lower and more predictable.
In this issue we have two announcements related to industry conferences. Our FabTime software user tip of the month is about how to look at shipped lot cycle times for individual lots in more detail. We have no subscriber discussion in this issue, but we do welcome your questions or comments for future newsletters.
In our main article this month we provide some ammunition to the many people who have asked us for help in estimating financial benefits from cycle time improvement efforts. The dollar benefits from cycle time improvement are not as easy to estimate as those from utilization improvement. However, there are several clear benefits that stem from variability reduction and cycle time improvement. If we can reduce variability in the fab, we have the option of squeezing the existing capacity buffer, and getting some extra throughput out of the same toolset. Alternatively, if we reduce variability in the fab, we can reduce cycle time. Cycle time reduction is tied to several other benefits: improved line yield, decreased WIP carrying cost, decreased cost of engineering change notices, decreased risk of obsolete inventory, and increased revenue from time to market pricing premiums. In this article, we review the first two of these benefits in detail, with numerical examples, and include highlights of the other three.
In this month’s issue we have a response from newsletter subscriber MS Ham to last month’s question about making dispatching decisions that account for downstream batch efficiency. Our development team has also been busy, and our FabTime software user tip of the month concerns a new method for configuring flexible goals.
In our relatively short main article this month, we discuss a fundamental conflict in wafer fabs: the pressure to simultaneously increase tool utilization, while decreasing cycle time. As regular readers of this newsletter know, utilization is one of the main drivers of cycle time at the tool level. As utilization increases, cycle time increases non-linearly, becoming very large for tools with the highest utilization values. Despite this fact, fabs are under cost pressure to increase utilization, so that they can get more throughput out of the same toolset. In this article, we discuss two ways to resolve this conflict.
In this month’s issue we have an announcement about my being named to the Supplier Advisory Board for the Fab Owners Association. The FOA is a corporation of semiconductor fab owners and associates who meet to discuss common manufacturing issues, and to combine strengths and resources. I recommend that you look into it, if you are an independent device manufacturer. We also have announcements for two upcoming industry conferences.
This month’s FabTime software user tip of the month describes how to use our new Forecast Outs Lot List chart. In our subscriber discussion forum we have a response from a subscriber about an attempt to implement Kanban cards in a wafer fab (in response to last month’s article about lean manufacturing). We also have a new subscriber question about making active dispatching decisions to improve downstream batch efficiency. We welcome your feedback regarding these topics, or your other manufacturing-related questions.
In our main article this month, we revisit a topic that we last touched in the very first year of publication of the newsletter: lean manufacturing and wafer fabs. Lean manufacturing is a philosophy focused on reducing waste and developing a more flexible and efficient manufacturing process. This philosophy has application to many types of manufacturing environments, including wafer fabs. However, many of the lean manufacturing implementation techniques currently in use were developed for automotive manufacturing, and are problematic when applied to wafer fabs. This does not mean that the underlying principles of lean manufacturing can’t be applied to wafer fabs - merely that we have to look at the underlying techniques, and focus on more relevant industry-specific implementation methods.
In this month’s issue, we have an announcement regarding the IEEE Robotics & Automation Society’s Technical Committee on Semiconductor Manufacturing Automation. They have a useful new website available. Our software user tip of the month is about setting alerts for individual lots at specific operations, highlighting two new alerts requested by a FabTime customer. In our subscriber discussion forum, we have a response to last month’s main article about cycle time variability. We’re also pleased to welcome 11 new companies and universities to the subscriber list.
This month we have an announcement about new members of the Fab Owners Association, of which FabTime is an associate member. Our FabTime software user tip of the month is about generating a lot comments report (to display all of the MES comments for a particular lot). We have subscriber discussion related to last month's question about process cycle efficiency, and about cycle time variability.
The subscriber discussion questions about cycle time variability, in conjunction with a discussion that we’ve been having with one of our customers, inspired us to write this month’s main article about cycle time variability (or the distribution of cycle times). We first briefly discuss benefits of and methods for tightening the distribution of shipped lot cycle times. We then review a couple of metrics for tracking variability within the fab, with emphasis on understanding the impact of this variability on overall cycle time distribution. We next describe several methods for tracking and reporting shipped lot cycle time distribution, including a new metric similar to the A20/A80 availability metric, which we have called CT20/CT80. We believe that this metric can help fabs to better understand, and hence to improve, the distribution of lot cycle times.
In our main article this month, we summarize our current recommended set of metrics for managing and improving cycle time in a wafer fab. Metrics are an indication of management priorities. Fabs that are cycle time focused need metrics that drive cycle time improvement. Such metrics should highlight current opportunities for improvement, and, if followed, should lead to improvements in shipped lot cycle time. In this article, we discuss several metrics that we believe are helpful for cycle time improvement. We have categorized these metrics as open lot, closed lot, shift-level, and tool-level, and have briefly defined each one.
This month we have an announcement about the newsletter receiving its 2000th subscriber. We also have an announcement regarding future newsletter topics. Our FabTime user tip of the month describes the use of the new “stripe” control to apply a target band across a chart. We also have subscriber discussion regarding the continuing topic of M-Ratio (maintenance ratio), by James Ignizio, and about a cross-fab metric called Process Cycle Efficiency.
In our main article this month we return to the ever-popular topic of operators. Specifically, we discuss some of the ways that operators can introduce variability into the fab and suggest metrics to capture and reduce this effect. It’s a relatively short article, in honor of our shortest month (and because of the extensive subscriber discussion in this issue).
This month we have two FabTime announcements, one about our new associate membership in the Fab Owners Association, and another concerning our enhanced lot dispatching module. We also have a call for papers for a special session on semiconductor manufacturing at the upcoming IEEE Conference on Automation Science and Engineering. Our FabTime software user tip of the month is about displaying zero-value objects on the move and WIP pareto charts. This month we have quite a bit of subscriber discussion, with multiple responses to last month's article about running development lots in a production fab. We also have multiple responses to James Ignizio’s description of M-Ratio from last month’s subscriber discussion forum.
In our main article this month, we discuss the cycle time impact of running development wafers in a production fab. For many fabs, running development wafers in a production fab is a necessary part of doing business. However, the development wafers can have a negative impact on production lot cycle times. In this article, we discuss several reasons why development lots may contribute to higher production lot cycle times. We also trace each of these factors back to their effect on the three fundamental drivers of fab cycle time: utilization, variability, and number of tools per tool group.
This month we have announcements about a new software development cost estimation tool from WWK, and a FabTime News and Updates website/blog that we are beta testing. Our software user tip of the month describes how to add a custom title to any FabTime chart. This month’s subscriber discussion forum brings feedback from James Ignizio regarding last month’s article on operational recommendations for fab cycle time improvement, as well as a new subscriber question about understanding the relationship between staffing levels and equipment utilization.
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