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This paper describes a cooperative endeavor between a state university and a federal agency to modernize design automation among rural manufacturers. It concerns efforts to infuse leading‐edge design technology into rural product development.

Boise State University established a rapid prototyping (RP) laboratory and conducted an information campaign targeting Idaho's design and manufacturing sector. About 12 rural companies participated in a program supported by a federal grant wherein they received solid modeling and RP services while developing a product.

Significant unfamiliarity about benefits of solid modeling and RP persists amongst Idaho's rural manufacturers. When exposed to the potential of these technologies, manufactures readily move to adopt them into their new product development processes. Those companies adapting design automation improved their capability to bring products to the marketplace more rapidly and with greater market success.

Other regions with similar dispersion of manufacturing can disseminate knowledge of advanced design automation technology and services through promotional approaches as described in this paper.

The paper focuses on a cooperative endeavor to infuse leading‐edge design technology into rural product development.

The purpose of this paper is to propose a solution for automating the task of matching business process models and search for correspondences with regard to the model semantics, thus improving the efficiency of such works.

A method is proposed based on combining several semantic technologies. The research follows a design-science-oriented approach in that a method together with its supporting artifacts has been engineered. It application allows for reusing legacy models and automatedly determining semantic similarity.

The method has been applied and the first findings suggest the effectiveness of the approach. The results of applying the method show its feasibility and significance. The suggested heuristic computing of semantic correspondences between semantically heterogeneous business process models is flexible and can support domain users.

Even though a solution can be offered that is directly usable, so far the full complexity of the natural language as given in model element labels is not yet completely resolvable. Here further research could contribute to the potential optimizations and refinement of automatic matching and linguistic procedures. However, an open research question could be solved.

The method presented is aimed at adding to the methods in the field of business process management and could extend the possibilities of automating support for business analysis.

The suggested combination of semantic technologies is innovative and addresses the aspect of semantic heterogeneity in a holistic, which is novel to the field.