Title page for ETD etd-03172010-020042

Type of Document Master's Thesis
Author Grau, Peter F.
URN etd-03172010-020042
Title Analysis of high density interconnect alternatives in multichip module packaging using the analytic hierarchy process
Degree Master of Science
Department Systems Engineering
Advisory Committee
Advisor Name Title
Sullivan, William G. Committee Chair
Blanchard, Benjamin S. Jr. Committee Member
Fabrycky, Wolter J. Committee Member
  • Multichip modules (Microelectronics)
Date of Defense 1993-10-05
Availability restricted

Packaging of high density integrated circuits offers many challenges in the electronics industry today. Advanced requirements for high performance computing are starting to take advantage of multichip modules that are smaller in size and weight, use less energy, and cost less than prior technologies. This project and report provides a summary of the processes of multichip module packaging and describes some of the companies and their technologies currently involved in the industry today. An advanced computer system is proposed that would require a high density multichlp module. Functional requirements and performance specifications are identified for the system.

Many design decisions are required to determine the best integrated circuit package for the system, with trade-off analysis being key in the selection process. One comparative analysis worthy of study is the evaluation of high density interconnection alternatives. Two technologies of multichip module designs are compared using the Analytic Hierarchy Process. Main attributes of the alternatives are chosen that are key to thp design and have significant differences. The attributes are defined in detail and weighted based on their importance to the model. Performance data is also used in the comparisons of alternatives.

A spreadsheet program was developed to quickly enter the weighted values and performance data, perform the matrix calculations, and determine the final rankings of the alternatives. Sensitivity analysis was then applied to determine what effect a change in the value of a particular attribute had on the outcome of the rankings. Results of the sensitivity analysis for key attributes are graphically plotted.

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