A Methodology For Applying Expert Systems To Process Plan Execution

Mark C. Maletz

doi:10.1117/12.940606

11 May 1987 A Methodology For Applying Expert Systems To Process Plan Execution

Mark C. Maletz

Proceedings Volume 0786, Applications of Artificial Intelligence V; (1987) https://doi.org/10.1117/12.940606
Event: 1987 Technical Symposium Southeast on Optics, Electro-Optics, and Sensors, 1987, Orlando, FL, United States

Abstract

This paper describes a methodology for applying expert systems to the task of executing process plans as a control mechanism for the factory floor. This methodology includes an architecture for representing both declarative and procedural knowledge. Declarative knowledge describes the state of the factory floor and the process plan operations that can be performed on parts on the factory floor (e.g., machining and assembly operations). Declarative knowledge is represented using both facts and schemata. Procedural knowledge identifies when and how process plan operations are to be executed. Procedural knowledge is represented using data-driven rules with an asynchronous event handling capability. Rules that determine when process plan operations can be performed embody largely domain-independent scheduling knowledge. Rules that determine how to execute process plan operations require domain-dependent knowledge about particular operations. Both of these types of rules also require information about the current state of the factory floor. A context graph mechanism is included in the methodology to represent temporal precedence constraints among process plan operations (i.e., the structure of a context graph indicates process plan operation precedences). Contexts are also used to represent a part configuration relative to a process plan operation. A prototype expert system based on the methodology presented in this paper has been developed using the Automated Reasoning Tool (ART).

Citation Download Citation

Mark C. Maletz "A Methodology For Applying Expert Systems To Process Plan Execution", Proc. SPIE 0786, Applications of Artificial Intelligence V, (11 May 1987); https://doi.org/10.1117/12.940606

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Artificial intelligence

Control systems

Prototyping

Computer programming

Databases

Network security

Process modeling

Show All Keywords

Keywords/Phrases

Search In:

Publication Years