P • A • R • T • 7
Predicting Piecepart Quality
Dan A. Watson, Ph.D.
Texas Instruments Incorporated
Dr. Watson is a statistician in the Silicon Technology Development Group (SiTD) at Texas Instruments.
He is responsible for providing statistical consulting and programming support to the researchers in
SiTD. His areas of expertise include design of experiments, data analysis and modeling, statistical
simulations, the Statistical Analysis System (SAS), and Visual Basic for Microsoft Excel. Prior to
coming to SiTD, Dr. Watson spent four years at the TI Learning Institute, heading the statistical training
program for the Defense and Electronics Group. In that capacity he taught courses in Design of Experi-
ments (DOE), Applied Statistics, Statistical Process Control (SPC), and Queuing Theory. Dr. Watson
has a bachelor of arts degree in physics and mathematics from Rice University in Houston, Texas, and a
masters and Ph.D. in statistics from the University of Kentucky in Lexington, Kentucky.
This chapter expands the ideas introduced in the paper, Statistical Yield Analysis of Geometrically
Toleranced Features, presented at the Second Annual Texas Instruments Process Capability Conference
(Nov. 1995). In that paper, we discussed methods to statistically analyze the manufacturing yield (in
defects per unit) of part features that are dimensioned using geometric dimensioning and tolerancing
(GD&T). That paper specifically discussed features that are located using positional tolerancing.
This chapter expands the prior statistical methods to include features that have multiple tolerancing
constraints. The statistical methods presented in this paper:
• Show how to calculate defects per unit (DPU) for part features that have form and orientation controls
in addition to location controls.
21-2 Chapter Twenty-one
• Account for material condition modifiers (maximum material condition (MMC), least material condi-
tion (LMC), and regardless of featur