Massive Data Sets: Proceedings of a Workshop

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3 Data Overview

Data taken during manufacturing is available from a variety of sources. Some of the data are collected as a normal part of the statistical process control effort. Some of the data are collected as a normal part of the electrical screening tests that ensure product quality. At AMD we currently collect and summarize approximately 2 gigabytes of such data per day. In order to discover better ways of controlling key process steps, a number of companies are now automatically collecting some data using process state sensors.

Even in the development stage, the data volume from these sensors is huge. It is now possible to collect over 1 megabyte of sensor data per wafer in a plasma etch step alone. Given that there are typically 10 or more such steps in a manufacturing process, when one considers that an average wafer fabrication site produces several thousand wafers per week, the potential data volume for analysis is huge.

Some of the reasons we wish to collect manufacturing data and perform the analyses include: process and product characterization process optimization yield optimization process control design for manufacturing

The question might be raised as to how these needs are different from the same needs in a more typical manufacturing environment? The first and foremost reason is that data are available from a large number of process operations—and much of that data can be collected automatically. The second reason is that the manufacturing process involves a large number of steps, some of which are essentially single wafer steps and others of which are batch processing steps of various batch sizes.

In addition, much of the summary data collected at this time are highly correlated due to the nature of the underlying physics and chemistry of the processing operations. In addition there is an established practice of taking multiple measures of the same electrical characteristics using test cells of varying sizes and properties. So, many of the apparently "independent" observations aren't actually independent.

There are other sources of data that are less related to direct manufacturing that may be used with the manufacturing data. These sources of data involve the output of process simulators and die design simulators. It is becoming more standard throughout the semiconductor industry to link these simulators together in chains to get a better picture of the expected performance characteristics of processes and semiconductor devices. these expectations may then be compared to actual manufacturing experience.

Manufacturing process data are typically collected in 4 different stages, each of which provides a characteristic type of data for analysis. These data types are: die fabrication data wafer electrical data sort electrical data final test data

4 Die Fabrication Data

Die fabrication data are typically in-process SPC data at this time. Although SPC data and its uses in the manufacturing environment are fairly well understood, there has been some interest expressed both within AMD and in other companies about further leveraging the

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