The configuration of design and manufacture knowledge models from a heavyweight ontological foundation

Abstract

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.

Extending product lifecycle management for manufacturing knowledge sharing

“…Prior work [6,7,15] has demonstrated that an ontology of well-defined core concepts can serve as a foundation for the sufficiently flexible development of domain-specific concepts, such as those pertinent to feature-based design and manufacturing planning viewpoints. Thus, the IMKS approach allows the derivation of specialised knowledge bases as repositories for designers and planners alike, without the need to commit to a fixed master model.…”

“…Thus, the IMKS approach allows the derivation of specialised knowledge bases as repositories for designers and planners alike, without the need to commit to a fixed master model. In that sense, the heavyweight ontology dimension of this work builds on top of the current perceived advantages of applying formal ontologies within a PLM context to aid the process of semantic interoperability and knowledge exchanges [3,6,7,16,17].…”

“…Various contributions have demonstrated that the semantic value of the captured knowledge is dependent on the expressiveness of the ontology language used [4,5,6]. In production engineering, heavyweight (i.e., expressive) ontologies are favoured [3,6,7] as they are accompanied with logic-based reasoning mechanisms which carefully prescribe the semantics, behaviour and conditions present within information structures. Expressive ontologies thus impart the ability to configure knowledge models for improved decision making [7].…”

“…In production engineering, heavyweight (i.e., expressive) ontologies are favoured [3,6,7] as they are accompanied with logic-based reasoning mechanisms which carefully prescribe the semantics, behaviour and conditions present within information structures. Expressive ontologies thus impart the ability to configure knowledge models for improved decision making [7]. This paper investigates the Interoperable Manufacturing Knowledge Systems (IMKS) approach.…”

A Framework for Structural Modelling of an Rfid-Enabled Intelligent Distributed Manufacturing Control System

“…A typical manufacturing facility has a centralised database containing the product data model (PDM), which holds information on the product [1], and the manufacturing data model (MDM), which holds information on the systems needed to manufacture the product [2]. Together, the PDM and MDM provide an optimal scheduling plan for all control subsystems [3], organised hierarchically (e.g., as factories, cells, and stations) through a central host computer.…”