Meifa Huang

Automatically generating assembly tolerance types with an ontology-based approach

In most cases, designers have to manually specify both assembly tolerance types and values when they design a mechanical product. Different designers will possibly specify different assembly tolerance types and values for the same nominal geometry. Furthermore, assembly tolerance specification design of a complex product is a highly collaborative process, in which semantic interoperability issues significantly arise. These situations will cause the uncertainty in assembly tolerance specification design and finally affect the quality of the product. In order to reduce the uncertainty and to support the semantic interoperability in assembly tolerance specification design, an ontology-based approach for automatically generating assembly tolerance types is proposed. First of all, an extended assembly tolerance representation model is constructed by introducing a spatial relation layer. The constructed model is hierarchically organized and consists of part layer, assembly feature surface layer, and spatial relation layer. All these layers are defined with Web Ontology Language (OWL) assertions. Next, a meta-ontology for assembly tolerance representations is constructed. With this meta-ontology, the domain-specific assembly tolerance representation knowledge can be derived by reusing or inheriting the classes or properties. Based on this, assembly tolerance representation knowledge is formalized using OWL. As a result, assembly tolerance representation knowledge has well-defined semantics due to the logic-based semantics of OWL, making it possible to automatically detect inconsistencies of assembly tolerance representation knowledge bases. The mapping relations between spatial relations and assembly tolerance types are represented in Semantic Web Rule Language (SWRL). Furthermore, actual generation processes of assembly tolerance types are carried out using Java Expert System Shell (JESS) by mapping OWL-based structure knowledge and SWRL-based constraint knowledge into JESS facts and JESS rules, respectively. Based on this, an approach for automatically generating assembly tolerance types is proposed. Finally, the effectiveness of the proposed approach is demonstrated by a practical example.

Enriching the semantics of variational geometric constraint data with ontology

Lack of explicit semantics in the product data to be exchanged among product development systems is a major problem for existing product data exchange standards. To solve this problem, the semantics of product data should be enriched to form a basis for exchanging them. This paper proposes an ontology-based approach to enrich the semantics of variational geometric constraint data, one of the most important kinds of product data in product development systems. In this approach, an ontology for variational geometric constraint specifications is constructed by formalizing the specifications in the variational geometric constraint network theory in Web Ontology Language 2 Description Logic (OWL 2 DL) and Semantic Web Rule Language (SWRL). This ontology has rigorous computer-interpretable semantics due to the mathematic logic-based semantics of OWL 2 DL and SWRL. It is capable of providing a semantic enrichment model for the variational geometric constraint data extracted from CAD systems. The ontology is implemented with the use of the OWL 2 DL/SWRL ontology based technologies. As the benefits of the implemented ontology, consistency checking, knowledge reasoning and semantic queries can be automatically performed. These benefits will lay a basis for further exchanging the explicit semantics of variational geometric constraint data among heterogeneous product development systems. The semantics of product data cannot be automatically exchanged by existing standards.An ontology is constructed by formalizing VGC specifications in OWL and SWRL.The ontology is instantiated by the VGC data extracted from CAD systems.The ontology can well express the explicit semantics of the VGC data.Consistency checking, knowledge reasoning and semantic queries can be performed.

An assembly tolerance representation model based on spatial relations for generating assembly tolerance types

The main advantage of polychromatic sets-based assembly tolerance representation model is that the number of feature types to be processed is larger. However, the number of recommended assembly tolerance types generated by the model is somewhat large for the same feature surfaces. Furthermore, the model cannot be directly applied to further assembly tolerance analysis and synthesis due to the fact that the information of degrees of freedom cannot be processed in polychromatic sets. To further reduce the number of recommended assembly tolerance types and to lay foundation for further assembly tolerance analysis and synthesis, a spatial relation layer is introduced into the polychromatic sets-based model and an assembly tolerance representation model based on spatial relations for generating assembly tolerance types is proposed. The proposed model is hierarchically organized and consists of part layer, assembly feature surface layer, spatial relation layer and assembly tolerance type layer. Each layer is defined with an adjacency matrix, respectively. By the mapping from spatial relations to assembly tolerance types, the number of recommended assembly tolerance types generated by the mapping from feature surfaces to assembly tolerance types is able to be further reduced. In addition, the information of degrees of freedom can be attached in the elements of adjacency matrices when recommended assembly tolerance types are generated by spatial relations so that the proposed model can be directly applied to further assembly tolerance analysis and synthesis. The effectiveness of the proposed model is demonstrated by an approach for generating assembly tolerance types and a practical example.

Constructing a meta-model for assembly tolerance types with a description logic based approach

There is a critical requirement for semantic interoperability among heterogeneous computer-aided tolerancing (CAT) systems with the sustainable growing demand of collaborative product design. But current data exchange standard for exchanging tolerance information among these systems can only exchange syntaxes and cannot exchange semantics. Semantic interoperability among heterogeneous CAT systems is difficult to be implemented only with this standard. To address this problem, some meta-models of tolerance information supporting semantic interoperability and an interoperability platform based on these meta-models should be constructed and developed, respectively. This paper mainly focuses on the construction of a meta-model for assembly tolerance types with a description logic ALC(D) based approach. Description logics, a family of knowledge representation languages for authoring ontologies, are well-known for having rigorous logic-based semantics which supports semantic interoperability. ALC(D) can provide a formal method to describe the research objects and the relations among them. In this formal method, constraint relations among parts, assembly feature surfaces and geometrical features are defined with some ALC(D) assertional axioms, and the meta-model of assembly tolerance types is constructed through describing the spatial relations between geometrical features with some ALC(D) terminological axioms. Besides, ALC(D) can also provide a highly efficient reasoning algorithm to automatically detect the inconsistency of the knowledge base, a finite set of assertional and terminological axioms. With this reasoning algorithm, assembly tolerance types for each pair of geometrical features are generated automatically through detecting the inconsistencies of the knowledge base. An application example is provided to illustrate the process of generating assembly tolerance types.

Estimation of the measurement uncertainty based on quasi Monte-Carlo method in optical measurement

Because measurement uncertainty is an important parameter to evaluate the reliability of measurement results, it is essential to present reliable methods to evaluate the measurement uncertainty especially in precise optical measurement. Though Monte-Carlo (MC) method has been applied to estimate the measurement uncertainty in recent years, this method, however, has some shortcomings such as low convergence and unstable results. Therefore its application is limited. To evaluate the measurement uncertainty in a fast and robust way, Quasi Monte-Carlo (QMC) method is adopted in this paper. In the estimating process, more homogeneous random numbers (quasi random numbers) are generated based on Haltons sequence, and then these random numbers are transformed into the desired distribution random numbers. An experiment of cylinder measurement is given. The results show that the Quasi Monte-Carlo method has higher convergence rate and more stable evaluation results than that of Monte-Carlo method. Therefore, the quasi Monte-Carlo method can be applied efficiently to evaluate the measurement uncertainty.

Towards an ontology-supported case-based reasoning approach for computer-aided tolerance specification

Abstract In this paper, an ontology-supported case-based reasoning approach for computer-aided tolerance specification is proposed. This approach firstly considers the past tolerance specification problems and their schemes as previous cases and the new tolerance specification problems as target cases and uses an ontology to represent previous and target cases. Then certain ontology-based similarity measure is used to assess the similarity between the toleranced features of target and previous cases, the similarity between the part features of target and previous cases, and the similarity between the topological relations of target and previous cases. Based on these similarities, an ontology-based similarity measure for computing the similarity between target and previous cases is designed, and an algorithm for establishing such similarity measure with high accuracy and retrieving similar previous cases for a target case with this similarity measure is presented. This algorithm shows how to linearly combine the similarity of toleranced features, the similarity of part features, and the similarity of topological relations to assess the similarity between target and previous cases to implement retrieval of previous cases under the prerequisite of ensuring the highest accuracy of the similarity measure. The paper also reports a prototype implementation of the proposed approach, provides an example to illustrate how the approach works, and evaluates the approach via theoretical and experimental comparisons.

A Representation Model of Geometrical Tolerances Based on First Order Logic

Tolerance representation models are used to specify tolerance types and explain semantics of tolerances for nominal geometry parts. To well explain semantics of geometrical tolerances, a representation model of geometrical tolerances based on First Order Logic (FOL) is presented in this paper. We first investigate the classifications of feature variations and give the FOL representations of them based on these classifications. Next, based on the above representations, we present a FOL representation model of geometrical tolerances. Furthermore, we demonstrate the effectiveness of the representation model by specifying geometrical tolerance types in an example.