For the past five years, I’ve been working in a semiconductor clean room. I’m interested in the connections between manufacturing and computer science. One that stands out to me is the importance of concurrency control throughout the fab (factory).<\/p>\n\n\n\n
The fab has a multitude of interconnected monitors, machines (aka “tools”), servers, and computer programs. Multiple employees may interact with a tool or lot remotely at the same time. To prevent errors in processing, it is important to keep the sequence of events synchronized.<\/p>\n\n\n\n
In my OSU classes, I have used thread management libraries in Python and C++ for concurrency control. When a sensitive transaction takes place, one thread will lock the data store (Amarasinghe, et al). Other threads cannot access the data until the first thread has released it (Amarasinghe, et al).<\/p>\n\n\n\n
Some programs in the fab use something like optimistic concurrency, where updates are allowed, but fail on save if someone else made a change in the meantime (Vickers). If a technician puts a lot on hold while an operator is in the middle of logging lot data, the software will show an error and prevent data submission.<\/p>\n\n\n\n
However, some programs do not have concurrency checks in place. For instance, separate software is used to evaluate data and track lots. After data entry, an operator might need to wait a few seconds before updating the lot status in the tracking software. The data software doesn’t always evaluate the data and flag the lot immediately.<\/p>\n\n\n\n
My fab needs some improvements in concurrency control. For instance, locking lots or tools from operators while waiting for data to be uploaded and evaluated.<\/p>\n\n\n\n
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Works Cited<\/strong>
Amarasinghe, S., et al. “Reading 23: Locks and Synchronization” Software Construction<\/em>. MIT, Fall 2015, web.mit.edu\/6.005\/www\/fa15\/classes\/23-locks\/#reading_23_locks_and_synchronizatio<\/a>n. Accessed 11 Jan 2024.
This work is licensed under CC BY-SA 4.0.<\/p>\n\n\n\n