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Journal ArticleDOI

The evolution, challenges, and future of knowledge representation in product design systems

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TLDR
The goal of this paper is to review both the understanding of the field and the support tools that exist for the purpose, and identify the trends and possible directions research can evolve in the future.
Abstract
Product design is a highly involved, often ill-defined, complex and iterative process, and the needs and specifications of the required artifact get more refined only as the design process moves toward its goal. An effective computer support tool that helps the designer make better-informed decisions requires efficient knowledge representation schemes. In today's world, there is a virtual explosion in the amount of raw data available to the designer, and knowledge representation is critical in order to sift through this data and make sense of it. In addition, the need to stay competitive has shrunk product development time through the use of simultaneous and collaborative design processes, which depend on effective transfer of knowledge between teams. Finally, the awareness that decisions made early in the design process have a higher impact in terms of energy, cost, and sustainability, has resulted in the need to project knowledge typically required in the later stages of design to the earlier stages. Research in design rationale systems, product families, systems engineering, and ontology engineering has sought to capture knowledge from earlier product design decisions, from the breakdown of product functions and associated physical features, and from customer requirements and feedback reports. VR (Virtual reality) systems and multidisciplinary modeling have enabled the simulation of scenarios in the manufacture, assembly, and use of the product. This has helped capture vital knowledge from these stages of the product life and use it in design validation and testing. While there have been considerable and significant developments in knowledge capture and representation in product design, it is useful to sometimes review our position in the area, study the evolution of research in product design, and from past and current trends, try and foresee future developments. The goal of this paper is thus to review both our understanding of the field and the support tools that exist for the purpose, and identify the trends and possible directions research can evolve in the future.

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Book

The knowledge-creating company

TL;DR: Nonaka and Takeuchi as discussed by the authors argue that there are two types of knowledge: explicit knowledge, contained in manuals and procedures, and tacit knowledge, learned only by experience, and communicated only indirectly, through metaphor and analogy.

Design Prototypes: A Knowledge Representation Schema for Design

John S. Gero
TL;DR: A knowledge representation schema for design called design prototypes is introduced and described to provide a suitable framework to distinguish routine, innovative, and creative design.
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Customization design method for complex product systems based on a meta-model:

TL;DR: A rapid customization design prototype system has been developed and applied to the design of a high-speed train’s bogie to illustrate how to construct a product meta-model and how to conduct configuration design on different layers and variant design for generating new products.
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A comprehensive survey of augmented reality assembly research

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Exploring product design quality control and assurance under both traditional and crowdsourcing-based design environments

TL;DR: This article focuses on product design stages to investigate what key factors affect product design quality and how it can be controlled and assured, and separately survey key factors affecting product designquality in traditional and crowdsourcing-based design environments.
References
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Book

The Knowledge Creating Company

TL;DR: The Japanese companies, masters of manufacturing, have also been leaders in the creation, management, and use of knowledge-especially the tacit and often subjective insights, intuitions, and ideas of employees as discussed by the authors.
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Dilemmas in a general theory of planning

TL;DR: The search for scientific bases for confronting problems of social policy is bound to fail, becuase of the nature of these problems as discussed by the authors, whereas science has developed to deal with tame problems.
Book

The Sciences of the Artificial

TL;DR: A new edition of Simon's classic work on artificial intelligence as mentioned in this paper adds a chapter that sorts out the current themes and tools for analyzing complexity and complex systems, taking into account important advances in cognitive psychology and the science of design while confirming and extending Simon's basic thesis that a physical symbol system has the necessary and sufficient means for intelligent action.
Journal ArticleDOI

Toward principles for the design of ontologies used for knowledge sharing

TL;DR: The role of ontology in supporting knowledge sharing activities is described, and a set of criteria to guide the development of ontologies for these purposes are presented, and it is shown how these criteria are applied in case studies from the design ofOntologies for engineering mathematics and bibliographic data.
Journal ArticleDOI

The Sciences of the Artificial