Date of Thesis



This thesis presents the development of a Modified Aggregate Feature Commonality Index (MAFCI) for analyzing information on medical labels, building on the Aggregate Feature Commonality Index (AFCI) created by Shooter and Cohen. The purpose of the MAFCI is to measure the commonality of a set of manufacturers' labels with minimal influence from non-essential features. Both the AFCI and the MAFCI are applied to prescription drug labels commonly used at the Geisinger Medical Center at Danville, PA. The difference between the MAFCI and AFCI is in the dissimilar weights placed on essential features in the calculations for MAFCI versus equal weights placed on all features for the AFCI. The MAFCI is the result of a conjoint analysis and Failure Modes and Effects Analysis (FMEA) with abundant input from medical professionals at the Geisinger Medical Center. Conjoint analysis is used to determine the weighing of features by visually presenting specially designed sample labels in survey format to professionals at Geisinger. The results of the survey are then analyzed to yield weights for specific features. The FMEA is then used support the results of the conjoint analysis. Differences between the AFCI and MAFCI are then presented, showing more correlation between the MAFCI and the commonality of the specific features identified.


Feature Commonality Index, FACI, FLCI, Conjoint, Modified aggregate

Access Type

Masters Thesis

Degree Type

Master of Science in Mechanical Engineering


Mechanical Engineering

First Advisor

Steven Shooter