Keywords

Artificial intelligence, Expert systems, Materials handling, Automation in Warehouses, Automated storage and retrieval systems (AS/RS), Blackboard expert system architecture, Rule-based warehousing control, Simulation-based performance evaluation, Operational efficiency improvement

Abstract

This report discusses the major functions, decisions, and strategies of automated storage and retrieval systems (AR/RS). The report surveys the essential features of expert systems and discusses how they can be applied in automated warehousing environments. A blackboard expert system architecture was examined and found to be a flexible and responsive control system for automated warehousing applications. A simple AR/RS expert system was constructed using an expert system software package. A warehousing simulation was performed which compared the expert system’s performance to a typical AR/RS control system. The expert system produced increased efficiency of operation because of the intelligent rules programmed into the system.

Notes

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Graduation Date

1986

Semester

Spring

Advisor

Biegel, John E.

Degree

Master of Science (M.S.)

College

College of Engineering

Department

Industrial Engineering and Management Systems

Format

PDF

Pages

38 pages

Language

English

Rights

Public Domain

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

Identifier

DP0020308

Subjects

Expert systems (Computer science)--Industrial applications; Information storage and retrieval systems--Warehouses; Information storage and retrieval systems--Automation; Expert systems (Computer science)--Design; Information storage and retrieval systems--Computer simulation

Accessibility Status

Searchable text

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