An Architecture for Intelligent Multichip Module Reliability Analysis

Abstract

This report describes the development of a computer-based modeling and analysis system called the Intelligent Multichip Module (MCM) Analyzer (IMCMA). IMCMA is a blackboard-based software tool that automatically performs finite-element and knowledge-based analysis of MCM designs to rapidly assess their reliability. In IMCMA, modeling effort and expert-operator requirements have been reduced through: (1) use of high-level representation of devices as the interface between the designer and the analysis tools; (2) capturing the expertise of experienced design analysts in an intelligent assistant for use by less experienced designers. Nine knowledge sources (KSs) were completed that take a high-level device specification through model generation and simplification, finite-element generation, and thermal analysis. These KSs include stand-alone FORTRAN finite-element generation codes that have been integrated into IMCMA by using the generic blackboard framework, GBB. This initial IMCMA prototype quickly produces a thermal analysis when given a high-level MCM design description. Reliability, Thermal analysis, Design, Finite element analysis, FFA, Modeling, Multichip module, MCM, Blackboard, Artificial intelligence.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1994
Accession Number
ADA281574

Entities

People

  • Daniel D. Corkill

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Computer Science
  • Computers
  • Contracts
  • Engineering
  • Engineers
  • Failure Mode And Effect Analysis
  • Finite Element Analysis
  • Graphics
  • Heat Energy
  • Lisp Programming Language
  • Materials
  • Prototypes
  • Reliability
  • Static Loads
  • Thermal Analysis
  • Three Dimensional

Fields of Study

  • Engineering

Readers

  • Artificial Intelligence
  • Computational Fluid Dynamics (CFD)
  • Computer Engineering

Technology Areas

  • AI & ML