Fab scheduling is now so complex that it needs next-generation intelligent software

There are literally billions of possible ways to schedule all the work through a fab, so finding the best way is an immense challenge. This is a multidimensional problem that current heuristic scheduling software just cannot handle. A new approach to the complexities of scheduling, developed by Flexciton, is already making a significant impact in the semiconductor industry.

BY JAMIE POTTER, CO-FOUNDER AND CEO, FLEXCITON

Global megatrends such as autonomous cars, AI and high performance computing are driving technological advancements and the need for ever more sophisticated chips and smaller process nodes. As a result, the wafer fabrication process is becoming even more complicated, with certain types of products requiring wafers to go through thousands of process steps and taking several months to manufacture. In addition to the challenge of complexity, there is an expectation for wafer fabrication to become more sustainable and energy efficient while increasing productivity and keeping the cost per wafer low.

The level of complexity in the production process is only expected to increase and unless fabs adopt new methods to simplify and streamline management, the challenge will become overwhelming. Chip companies must improve their performance and output by addressing the sophistication of their products. The current common approach of fabs to deal with complexity involves breaking down a big problem into smaller, more manageable ones, with specific teams assigned to tackle each challenge. In principle, this approach seems the right one, however, in practice it has significant drawbacks. Different teams within the fab often have different priorities and KPIs, which leads them to work in isolation. As individual teams strive to maximise their own KPIs, conflicts can arise as the KPIs of one area may be in opposition to those of another, negatively affecting the overarching fab objectives.

For example, while process engineers prioritise yield, industrial engineers are focused on reducing cycle time and increasing throughput, and manufacturing operators seek to maximise the number of moves per day. As an illustration, the objective of maximising the yield can impede the increase in throughput. Conversely, altering the recipe to enhance yield can impact throughput and cycle times, particularly if the changes require optimization over time.

Using scheduling to conquer complexity
Let’s dive deeper into the issue of complexity and how it impacts the scheduling of wafer production in particular. The process involves various stages such as; metrology, photolithography, diffusion furnace, epitaxy and more, each with its own unique set of guidelines and tools. The most common approach to scheduling is utilising rules-based software that dictates the sequence in which wafers are processed.

However, the sheer number of rules per area can be overwhelming, and industrial engineers often resort to simplifications and shortcuts to manage and control each stage’s parameters. Again, these ‘shortcuts’ may lead to suboptimal decisions made by the scheduler, with a negative impact on performance. Another problem with this approach is that it requires a huge amount of manual input from skilled industrial engineers to write and maintain the rules in an attempt to keep pace with a fab’s dynamic nature. In a fully operational fab, things are constantly evolving, which requires constant human intervention to ensure that scheduling rules are proactively monitored and updated. This is necessary to accommodate any changes that may occur and to create new rules in situations when new tools, recipes, or product mix are added. As the complexity of chips increases, so does the complexity of their production, necessitating frequent updates and additions to the rule set.