Intelligent condition-based maintenance of reactive ion etching process

N. I. Shaikh, Vittaldas V. Prabhu

Research output: Contribution to conferencePaper

Abstract

The semiconductor industry is facing increasing competition; motivating the need for condition-based maintenance in conjunction with process control. Condition-based maintenance can reduce the downtime of expensive equipment, production costs, and improve yield. Moreover, it can potentially reduce operation cost of semiconductor fabs by lowering the number of expensive spare parts that need to be in stock. This paper proposes an intelligent condition-based maintenance approach wherein the operating parameters for the process are selected while being constrained both by the process and maintenance requirements. Reactive ion etcher is selected as the target equipment: it is widely used and is a critical equipment in semiconductor industry. Based on real-time process and equipment condition data, artificial neural networks are used for assessing the current condition of the equipment and predicting the remaining time before the etcher needs to be shut down for maintenance. The proposed data driven approach is specially suited for the semiconductor industry, which relies heavily on statistical techniques for process control and optimization.

Original languageEnglish (US)
Pages927-932
Number of pages6
StatePublished - Dec 1 2003
EventSmart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference - St. Louis, MO., United States
Duration: Nov 2 2003Nov 5 2003

Other

OtherSmart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference
CountryUnited States
CitySt. Louis, MO.
Period11/2/0311/5/03

All Science Journal Classification (ASJC) codes

  • Software

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    Shaikh, N. I., & Prabhu, V. V. (2003). Intelligent condition-based maintenance of reactive ion etching process. 927-932. Paper presented at Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificial Life - Proceedings of the Artificial Neural Networks in Engineering Conference, St. Louis, MO., United States.