A broader view of the economic design of the X-bar chart in the semiconductor industry

This paper starts from a notice made in the semiconductor industry: a process control system and especially control charts provide information that can be exploited for correlation analyses during process investigations. In this industry, key and costly investigations are made for improving yield and reducing scrap. Daily, engineering teams are working at manufacturing improvements. Without process data, their work could take much more time and lead to weak improvements. Nevertheless, design of process control systems and in particular control charts lacks from taking into account this remark as there is no sound application to infer an optimal control chart depending on business parameters like yield, scrap, customer audits, etc. Meetings between several engineering teams (process control, quality, process integration, industrial engineering and production) occur frequently to find an affordable quantity of controls for each operation. The literature point of view does not provide more recommendations to take into account the reuse of data into these costly investigations. The paper investigates this issue. For this first investigation, work has been focused on the design economics of control charts for a simplified process model. The paper translates this concept into the Lorenzen and Vance's (1986) model. It simulates the design economic of a control chart taking into account this new model and infers new optimal statistical process control (SPC) set points. An analysis of this new link is made in a context of yield improvement, providing reference for knowing optimal quantity and frequency of controls.

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