• Skip to main content
  • Skip to primary sidebar
AAAI

AAAI

Association for the Advancement of Artificial Intelligence

    • AAAI

      AAAI

      Association for the Advancement of Artificial Intelligence

  • About AAAIAbout AAAI
    • AAAI Officers and Committees
    • AAAI Staff
    • Bylaws of AAAI
    • AAAI Awards
      • Fellows Program
      • Classic Paper Award
      • Dissertation Award
      • Distinguished Service Award
      • Allen Newell Award
      • Outstanding Paper Award
      • Award for Artificial Intelligence for the Benefit of Humanity
      • Feigenbaum Prize
      • Patrick Henry Winston Outstanding Educator Award
      • Engelmore Award
      • AAAI ISEF Awards
      • Senior Member Status
      • Conference Awards
    • AAAI Resources
    • AAAI Mailing Lists
    • Past AAAI Presidential Addresses
    • Presidential Panel on Long-Term AI Futures
    • Past AAAI Policy Reports
      • A Report to ARPA on Twenty-First Century Intelligent Systems
      • The Role of Intelligent Systems in the National Information Infrastructure
    • AAAI Logos
    • News
  • aaai-icon_ethics-diversity-line-yellowEthics & Diversity
  • Conference talk bubbleConferences & Symposia
    • AAAI Conference
    • AIES AAAI/ACM
    • AIIDE
    • IAAI
    • ICWSM
    • HCOMP
    • Spring Symposia
    • Summer Symposia
    • Fall Symposia
    • Code of Conduct for Conferences and Events
  • PublicationsPublications
    • AAAI Press
    • AI Magazine
    • Conference Proceedings
    • AAAI Publication Policies & Guidelines
    • Request to Reproduce Copyrighted Materials
  • aaai-icon_ai-magazine-line-yellowAI Magazine
    • Issues and Articles
    • Author Guidelines
    • Editorial Focus
  • MembershipMembership
    • Member Login
    • Developing Country List
    • AAAI Chapter Program

  • Career CenterCareer Center
  • aaai-icon_ai-topics-line-yellowAITopics
  • aaai-icon_contact-line-yellowContact

Home / Proceedings / Papers from the 1994 AAAI Spring Symposium /

Detecting and Resolving Errors in Manufacturing Systems

Contents

  • Manufacturing Control System Principles Supporting Error Recovery

    Peter Loborg and Anders Tome

    PDF
  • Robust Strategies for Diagnosing Manufacturing Defects

    Nancy Reed

    PDF
  • A Learning-Based Diagnostics Approach for Manufacturing Systems

    James Graham

    PDF
  • Model-Based Diagnostics for the Supervisory Control of Manufacturing Systems

    R. A. Williams, B. Benhabib, and K. C. Smith

    PDF
  • Adaptive Planning: An Approach that Views Errors As Assumption Failures

    Damian Lyons and A. J. Hendricks

    PDF
  • Attention Focusing and Anomaly Detection in Systems Monitoring

    Richard Doyle

    PDF
  • Sensor-based Monitoring for Real-Time Quality Control in Manufacturing

    Soundar R. T. Kumara, Sagar V. Kamarthi, Satishmohan Bukkapatnam, and Jinwhan Lee

    PDF
  • System Reliability and Risk Assessment: A Quantitative Extension of IDEF Methodologies

    Andrew Kusiak and Nick Larson

    PDF
  • The Effect of the Product Cost Factor on Error Handling in Industrial Robotics

    Nigel Hardy and Mark Lee

    PDF
  • A Practical Methodology for Generating Diagnosis and Recovery Applications in Large-Scale Plants

    Samir Padalkar, Gabor Karsai, Janos Sztipanovits, and Frank DeCaria

    PDF
  • Fault Monitoring in Manufacturing Systems Using Concurrent Discrete-Event Observations

    Larry Holloway and Sujeet Chand

    PDF
  • Error Recovery in Automation–An Overview

    Peter Loborg

    PDF
  • The Supervisory Control of Automated Manufacturing Systems: A Discrete Event Systems Approach

    Bertil A. Brandin

    PDF
  • A Method for Implementing AI-based Control in a Manufacturing Workcell Using a Biological Model

    Robert Borchelt

    PDF
  • Monitoring the Execution of Sensory Robot Programs

    Vincenzo Caglioti, Massimo Danieli, and Domenico Sorrenti

    PDF
  • Intelligent Error Recovery in Flexible Production Systems

    Emmanuel D. Adarnides, Ekaterin C. Yamalidou, and Dominique Bonvin

    PDF
  • Comparing a Neural-Fuzzy Scheme with a Probabilistic Neural Network for Applications to Monitoring and Diagnostics in Manufacturing Systems

    Kai Goebel, Bill Wood, Alice Agogino, and Punit Jain

    PDF
  • Integrated Control and Diagnostics in Discrete Event Dynamic Systems with Hierarchical Time-Extended Petri Nets

    S. Ramaswamy and Kimon P. Valavanis

    PDF
  • Integrating Failure Recovery with Planner Debugging

    Adele Howe

    PDF
  • Two Years On-line: A Dynamic Scheduler for a Hot Steel Mill

    Virginio Chiodini

    PDF
  • Communication Protocols and Failure Semantics in a Material-Driven Intelligent Manufacturing System

    Anders Adlemo and Sven-Ame Andreasson

    PDF
  • Detecting and Predicting Errors in Manufacturing Applications

    David Goldstein

    PDF
  • Reliability Analysis: System Models

    Jeffrey Bamen

    PDF
  • Active Rescheduling for Goal Maintenance in Dynamic Manufacturing Systems

    Ame F. Claassen, Ruby D. Lathon, Daniel M. Rochowiak, and Leslie D. Interrante

    PDF
  • Dynamic Sensor Policies

    Kun Krebsbach and Maria Gini

    PDF

Primary Sidebar