Featured Customer Success Story

Dual Robot Photolithography Cluster Tool Throughput Improvement

Client: Texas Instruments

Texas Instruments Cluster Tool Throughput Increase Click here to see a customer interview video

Click here to read the complete customer story in Adobe PDF format. Adobe PDF

Situation:

Texas Instruments is a leading supplier of high-performance analog ICs specializing in power management, amplifier, data conversion, and high-speed interface products. With future demand forecasts on the rise, they needed to understand the maximum throughput they could expect from their constraint – the photolithography cluster tool. If constraint throughput could be increased by 10%, they could avoid purchasing another cluster tool at the cost of $4 million.

Semiconductor wafer fabrication facilities are highly complex queuing networks with process flows consisting of hundreds of steps utilizing a wide array of sophisticated manufacturing equipment. Each piece of equipment itself typically includes multiple process steps. For such equipment types, flexible simulation models can allow evaluation of configuration and process scenarios to more accurately determine throughput. After having previous success with ProModel technology, they used it again to model the photolithography cluster tool.

Objective:

Determine the maximum throughput from the Dual Robot Photolithography Cluster Tool constraint, in order to meet increased future demand without purchasing new equipment or expanding the facility.

Results:

A comparison of wafer level times between model and tool led to the following:

  • Discovered the tool was missing the latest coat/develop track software update causing a wafer flow disruption between lots resulting in a partial break in cascade driving both a ph reduction as well as a cycle time increase due to wafer delays.
  • A schedule was established to ensure roll-out of the latest software upgrade to gain the associated throughput and cycle time improvements.

Implementing the software update improved throughput enough to avoid purchasing a new cluster tool thus avoiding a $4 million capital expense

To continue reading please click the PDF link below.

Click here to read the complete customer story in Adobe PDF format. Adobe PDF

 

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