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Massive Data Sets Proceedings of a Workshop (1996) / Chapter Skim
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Massive Data Sets in Semiconductor Manufacturing
Pages 69-76

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 69...
... typical processing sequence, there may be over 100 process operations performed before the raw material, crystalline silicon wafers up to 8 inches in diameter, is converted to wafers carrying up to several thousand unpackaged electronic circuits, called die, on them. There are perhaps a few dozen additional manufacturing operations related to packaging, in which the die are encapsulated in plastic or ceramic, that occur before the product is ready for sale.
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From page 70...
... 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.
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From page 71...
... Because many, if not most, of the process steps during semiconductor manufacture are under control of process controllers and are also capable of being fitted with sensors, the future data potential is enormous. For instance, for the etch step in a typical wafer fabrication site, it would not be unreasonable to expect approximately 35 GB of data per week to be collected at some point in the future.
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From page 72...
... Indeed, there have been numerous occasions in the industry where misprocessed product was identifiable at wafer electrical test. If this is the case in the more general setting, then it would be highly desirable to produce models relating in-process data to wafer electrical data for "normal" product so that corrections can be made to the process to achieve optimum performance for the process.
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From page 73...
... Since there can be considerable interaction between the package and the silicon die, some electrical tests are possible for the first time at this stage of manufacture. As with the sort electrical test data, we would like to relate these test results to the die fabrication process.
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From page 74...
... The ability to use a standard statistics package, perform simple tests of hypothesis, design and analyze standard fractional factorial experiments, and set up SPC programs does not represent the needs for the future. developing an understanding of which types of advanced modeling techniques provide leverage against which types of data for different analytical goals.
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From page 75...
... encouraging software vendors to provide analytical tools that can handle large quantities of data, either in the number of observations or in the number of variables, for identified high leverage techniques. This research is supported by ARPA/Rome Laboratory under contract #F30602-930100, and by the Dept.
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From page 76...
... A case study in planning for exploratory data analysis. In Advances in Intelligent Data Analysis, pages 1-5, 1995.
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Key Terms

  • electrical test
  • test data
  • semiconductor manufacturing
  • die fabrication
  • electrical tests

  • process operations
  • electrical data
  • sort electrical
  • fabrication data
  • spc data

  • response functions
  • manufacturing environment
  • process steps
  • wafer fabrication
  • fabrication process

  • sensor based
  • highly correlated
  • neural nets
  • data volume
  • individual process

  • based data
  • individual die
  • manufacturing industry
  • processing operations
  • exploratory data

  • fractional factorial
  • sensor response
  • massive data
  • silicon wafers
  • pid controller


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