Paper
16 April 1993 Methodology for optimizing cost of ownership
Rito A. Martinez, Veronica A. Czitrom, Neal G. Pierce, G. Scot Srodes
Author Affiliations +
Proceedings Volume 1803, Advanced Techniques for Integrated Circuit Processing II; (1993) https://doi.org/10.1117/12.142932
Event: Microelectronic Processing '92, 1992, San Jose, CA, United States
Abstract
A design of experiments methodology was used to evaluate seven different types of gate stack cluster tool configurations and their associated economic performance. SEMATECH's Cost of Ownership, Cost/Resource, Generic Dual, and Batch Cluster Tool Models plus ManSim and RS/1 were used. Response surface methodology (RSM) was utilized to predict and optimize the tool's configuration and economic performance parameters against three independent factory strategies. These strategies were: minimize cost per chip, minimize process cycle time, and increase capital utilization and flexibility. As expected, the single wafer tool configurations produced the lowest process step cycle times. Results also indicate that for a single wafer processing tool (at a cost of $1.2 M) to be economically viable (in terms of COO) as an alterative to the conventional approach, process times (per wafer, per chamber) of less than five minutes must be achieved. The batch cluster tool configuration with one pre-clean, gate oxide and poly chamber each was the best method to increase capital utilization and flexibility. This methodology can be applied to any process tool evaluation and can prove useful in designing and improving the tools's performance in order to meet factory goals.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rito A. Martinez, Veronica A. Czitrom, Neal G. Pierce, and G. Scot Srodes "Methodology for optimizing cost of ownership", Proc. SPIE 1803, Advanced Techniques for Integrated Circuit Processing II, (16 April 1993); https://doi.org/10.1117/12.142932
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Cited by 8 scholarly publications.
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KEYWORDS
Semiconducting wafers

Oxides

Performance modeling

Data modeling

Solid modeling

Instrument modeling

Manufacturing

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