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Disassembly, a process of separating the end of life (EOL) product into discrete components for re-utilizing their associated residual values, is an important enabler for the sustainable manufacturing. This work focuses on the modeling of the disassembly planning related information and develops a disassembly information model (DIM) based on an extensive investigation of various informational aspects in the domain of disassembly planning. The developed DIM, which represents an appropriate systematization and classification of the products, processes, uncertainties, and degradations related information, follows a layered modeling methodology in which DIM is subdivided into layers with the intent to separate general knowledge into different levels of abstractions and reach a balance between information reusability and information usability. Two prototype disassembly planning related applications have been incorporated to validate the usability and reusability of the developed DIM. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) offers significant opportunities for product innovation in many fields provided that designers are able to recognize the potential values of AM in a given product development process. However, this may be challenging for design teams without substantial experience with the technology. Design inspiration based on past successful applications of AM may facilitate application of AM even in relatively inexperienced teams. While designs for additive manufacturing (DFAM) methods have experimented with reuse of past knowledge, they may not be sufficient to fully realize AM's innovative potential. In many instances, relevant knowledge may be hard to find, lack context, or simply unavailable. This design information is also typically divorced from the underlying logic of a products' business case. In this paper, we present a knowledge based method for AM design ideation as well as the development of a suite of modular, highly formal ontologies to capture information about innovative uses of AM. This underlying information model, the innovative capabilities of additive manufacturing (ICAM) ontology, aims to facilitate innovative use of AM by connecting a repository of a business and technical knowledge relating to past AM products with a collection of knowledge bases detailing the capabilities of various AM processes and machines. Two case studies are used to explore how this linked knowledge can be queried in the context of a new design problem to identify highly relevant examples of existing products that leveraged AM capabilities to solve similar design problems. [ABSTRACT FROM AUTHOR]

Information exchange and sharing become a necessity for digital factory but they have been more challenging as the industry is computerized more. This is mainly because the capabilities of computerized systems have grown significantly in a very rapid pace in their own information structure, and they require to retrieve various data from different computer systems. ISO 10303-STEP has been developed to provide a neutral format for exchanging product data. However, implementation of STEP has several issues, including the following two: (1) the complete STEP file should be processed even for querying a small set of data, and (2) information required for realizing any functional activity (e.g., any analysis on any part of a product) is not explicitly identified. Hence, in this study, functionality-based conformance classes (FCCs) are developed to organize the current conformance classes (CCs) (which are the classes required to be implemented fully in order to be conformant to any particular STEP standard) for supporting different functional activities. Following the concept of data exchange specification (DEX)/template, several templates that are repeatedly used small information groups are introduced in order to create manageable sets of data constructs. In this study, the FCCs for 1D tolerance analysis are developed by enriching the available STEP information models with GD&T. The use of extended STEP models is illustrated with a case study. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an ontology for systems engineering, by means of a set of information models based on a modelling methodology derived from and a simplification of the ISO 15926 part 2 data model. During the engineering phase of several capital facility projects, the methodology has shown to be much more readable by and helpful in the communication between engineers than the mentioned data model. The ontology represents an interpretation of the Systems Engineering processes as described in ISO 15288 (System Life Cycle Processes) by the author based on years of experience with this standard. Based on the information models and the set of relationships defined herein one can, in combination with a reference data library, specify, build or configure an information system or data exchange mechanism in order to support Systems Engineering processes or set up a specific product knowledge model. Implementation can be done by using a centralized information management system or a distributed one, based on data exchange between involved parties. Both implementations have been validated within pilot projects respectively based on the software tool Relatics and based on a RDF application using triple stores. [Copyright &y& Elsevier]

Over the last decade, there has been a significant increase in attention to the overall accountability of higher education in Australia, and this is expected to continue. Increased accountability has led to the need for more explicitly documented curricula. The curricula from ten health-related disciplines developed over the last five years in Australia were the basis of this study. Curriculum information modeling is an approach that allows for the dynamic nature of curricula since elements and their linkages can be moved about and reconnected into meaningful patterns. In addition, the models give disciplines and institutions the ability to effectively monitor curricula and draw comparisons in a more unified manner. Curriculum information models are an efficient innovation in the design and management of curricula in higher education and particularly in the health care disciplines. They rest on the principles of reusable elements and linkages independent of content that were first used in the design, construction, and maintenance of buildings. The translation of this approach to the higher education sector provides a higher level of interoperabil-ity of resources and a clearer pathway for content design within a curriculum. [ABSTRACT FROM AUTHOR]

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