A structure-function-control paradigm for knowledge-based modeling and design of manufacturing workcells
Journal of Intelligent ManufacturingPublished 1 February 1992
Stefano Caselli, Constantinos Papaconstantinou, Keith L. Doty, Shamkant B. Navathe
Citations11
SJR quartileQ1
SJR score1.76
SNIP2.67
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TL;DR
A data model encompassing functional and control features, along with application domain structural knowledge, is developed that assists in explicitly representing the control aspects of engineering design within an object-oriented database and supports a task-level, functionality-driven, manufacturing workcell design.
Abstract
This paper discusses the integration of structural, functional and control knowledge in manufacturing workcell modeling, simulation and design. After an overview of applications of semantic and object-oriented data models in the manufacturing domain, issues relating to the control synthesis for manufacturing workcells are presented. In particular, a data model encompassing functional and control features, along with application domain structural knowledge, is developed. This model assists in explicitly representing the control aspects of engineering design within an object-oriented database and supports a task-level, functionality-driven, manufacturing workcell design. Since manufacturing workcells consist of a number of elements interacting in a complex manner, workcell control design is one of the most difficult steps in the workcell design procedure. Message passage, commonly used in object-oriented databases, provides no explicit modeling of the database behavior. Hence, it can not serve as a tool for the design of system control. On the other hand, Petrinets (PN) have proven successful in describing complex interaction among active agents. This paper will explore the incorporation of Petri nets as a basis for describing application control knowledge within a structure-function-control data model.
Keywords
EngineeringBusiness, Management and Accounting
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Elsevier eBooksKNOWLEDGE REPRESENTATION AND REASONING11This review draws heavily from work done with Ron Brachman. I also thank Jim des Rivières, Bart Selman, and John Tsotsos. for helping with an earlier version of the document. Financial support was received from the Natural Sciences and Engineering Research Council of Canada.
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