A semantically annotated multi-faceted ontology modeling for supporting product family design

Abstract

Product family design is one of the prevailing approaches for product realization in mass customization paradigm. With the ever-increasing product offerings in consumer market, a good product family modeling scheme is a basic requirement for further complex decision making where the incorporation of various design aspects, e.g. product function, marketing and manufacturing wise, for product family analysis are deemed important but challenging. Specifically, the issue of information management in product family design, that is related to an efficient and effective storage, sharing and timely retrieval of design information, has become more complicated. Product family modeling schema reported in the literature generally stress the component aspects of a product family and its analysis, with limited capability to model complex multiple inter-relationships and semantic annotations amongst physical components under various design facets. Due to this limitation, existing schemes are constrained to support intelligent PFD tasks, e.g. faceted component analysis based on vague, contextual design requirements like customer voices. In order to cope with these issues, ontology-based representation is identified as a promising solution especially in a semantically rich environment. Nevertheless, ontology development in design engineering demands a great deal of time commitment and human effort to digest complex design information. When a large variety of products are available, particularly in the consumer market, a more efficient method for building a product family ontology with the incorporation of multi-faceted semantic information is highly desirable. This thesis proposes a multi-faceted semantic tagging approach that is able to automatically suggest semantically related annotations based on design and manufacturing corpus. Technically, a semantic relatedness based ranking approach, FacetRank, is introduced in this thesis. Evaluation results using an annotated dataset indicate that FacetRank is capable of extracting salient terms from a collection of documents. Based on a faceted modeling approach, dictionary-like semantic descriptions can be generated for an input term where faceted semantic descriptors, e.g. faceted indicators and semantically similar key terms can be suggested. Using such an annotation approach, this thesis suggests a semi-automatic methodology of developing a semantically annotated multi-faceted product family ontology (MFPFO). The detailed steps of building such ontology are discussed with the feasibility of such a methodology exemplified using a family of laptop computers. Utilizing the aforementioned ontology, this thesis also presents a new perspective towards ontology-based product family design. Specifically, a faceted information search and retrieval framework based on a semantically annotated MFPFO is proposed. Faceted concept ranking (FCR) approach for ontology-based faceted component search is suggested to generate rank values for component search results corresponding to complex design requirements. From the component ranking results, a platform selection approach is proposed to evaluate the suitability of platform choices and platform change assessment under multi-faceted design considerations. Utilizing the search ranking results and new commonality metrics, optimal selection of components via a multi-objective design optimization is presented. A case study of three laptop computer design that involves four laptop computer families is demonstrated with promising outcomes. Finally, the advantages, issues and future works possible are also critically discussed in this thesis.