Mechanical assemblies are systems composed of modules that are either subassemblies or parts. Traditionally an assembly information model contains information regarding parts, their relationships, and its form. But it is important that the model also represent the function and behavior. This report describes the development of an Ontological Assembly Model in the broader context of Product Lifecycle Management (PLM).
The Standard for the Exchange of Product model data (STEP) [1] contains product information mainly related to geometry. The modeling language used to develop this standard, EXPRESS, does not have logical formalism that will enable rigorous semantics. In this paper we present an OWL-DL (Web Ontology Language -Description Logic) [2] version of STEP (OntoSTEP) that will allow logic reasoning and inference mechanisms and thus enhancing semantic interoperability. The development of OntoSTEP requires the conversion of EXPRESS schema to OWL-DL, and the classification of EXPRESS instances to OWL individuals. Currently we have considered AP203 [3] -the most widely used Application Protocol (AP) for the exchange of Computer-Aided Design (CAD) files -and STEP Part 21 [4] CAD files -CAD files conformant to the data exchange format defined in Part 21 -for schema level conversion and instance level classification respectively. We will describe a web application to demonstrate OntoSTEP. We are currently extending OntoSTEP to include information such as function, behavior, and assembly requirements.
The languages and logical formalisms developed by information scientists and logicians concentrate on the theory of languages and logical theorem proving. These languages, when used by domain experts to represent their domain of discourse, most often have issues related to the level of expressiveness and need specific extensions. In this paper, we first analyze the requirements for the development of structured knowledge representation models for manufacturing products. We then explore how these requirements can be satisfied through the levels of logical formalisms and expressivity of a structured knowledge representation model. We report our analysis of description logic (DL) and domain-specific rules with respect to the requirements by giving an example of a product ontology developed with ontology web language-description logic (OWL) and augmented with semantic web rule language (SWRL) rules. Clearly, increasing the expressivity of a product ontology also improves that of domain-specific rules, but there exits the usual tradeoff between the expressivity of languages and the complexity of their reasoning tasks. We present a case study of an electromechanical product to validate the analysis and further show how the OWL-DL reasoner together with the rule engine can enable reasoning about the product ontology. We finally discuss the open issues such as capabilities and limitations related to the usage of DL, OWL, and SWRL for product modeling.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.