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Problems related to knowledge sharing in design and manufacture, for supporting automated decision-making procedures, are associated with the inability to communicate the full meaning of concepts and their intent within and across system boundaries. To remedy these issues, it is important that the explicit structuring of semantics, i.e. meaning in computation form, is first performed and that these semantics become sharable across systems. This paper proposes a Common Logic-based ontological foundation as a basis for capturing the meaning of core feature-oriented design and manufacture concepts. This foundation serves as a semantic ground over which design and manufacture knowledge models can be configured in an integrity-driven way. The implications involved in the specification of the ontological foundation are discussed alongside the types of mechanisms that allow knowledge models to be configured. A test case scenario is then analysed in order to further support and verify the researched approach.

1 In a seminal work published in 1952, "The chemical basis of morphogenesis"-considered as the true start point of the modern theoretical biology-, A. M. Turing established the core of what today we call "natural computation" in biological systems, intended as self-organizing dynamic systems. In this contribution we show that the "intentionality", i.e., the "relation-to-object" characterizing biological morphogenesis and cognitive intelligence, as far as it is formalized in the appropriate ontological interpretation of the modal calculus (formal ontology), can suggest a solution of the reference problem that formal semantics is in principle unable to offer, because of Gödel and Tarski theorems. Such a solution , that is halfway between the "descriptive" (Frege) and the "causal" (Kripke) theory of reference, can be implemented only in a particular class of self-organizing dynamic systems, i.e., the dis-sipative chaotic systems characterizing the "semantic information processing" in biological and neural systems.

Production--centric international standards are intended to serve as an important route towards information sharing across manufacturing decision support systems. As a consequence of textual--based definitions of concepts acknowledged within these standards, their inability to fully interoperate becomes an issue especially since a multitude of standards are required to cover the needs of extensive domains such as manufacturing industries. To help reinforce the current understanding to support the consolidation of production--centric standards for improved information sharing, this article explores the specification of well--defined core concepts which can be used as a basis for capturing tailored semantic definitions. The potentials of two heavyweight ontological approaches, notably Common Logic (CL) and the Web Ontology Language (OWL) as candidates for the task, are also exposed. An important finding regarding these two methods is that while an OWL--based approach shows capabilities towards applications which may require flexible hierarchies of concepts, a CL--based method represents a favoured contender for scoped and facts--driven manufacturing applications.