Print Email Facebook Twitter Intelligent assembly time analysis, using a digital knowledge based approach Title Intelligent assembly time analysis, using a digital knowledge based approach Author Jin, Y. Curran, R. Butterfield, J. Burke, R. Welch, B. Faculty Aerospace Engineering Department Aerospace Management and Operations Date 2009-12-31 Abstract The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for intelligent time analysis of aircraft assembly processes within a digital manufacturing framework. A knowledge system is developed so that the design knowledge can be intelligently retrieved for implementing assembly time analysis automatically. A time estimation method based on MOST, is reviewed and employed. Knowledge capture, transfer and storage within the digital manufacturing environment are extensively discussed. Configured plantypes, GUIs and functional modules are designed and developed for the automated time analysis. An exemplar study using an aircraft panel assembly from a regional jet is also presented. Although the method currently focuses on aircraft assembly, it can also be well utilized in other industry sectors, such as transportation, automobile and shipbuilding. The main contribution of the work is to present a methodology that facilitates the integration of time analysis with design and manufacturing using a digital manufacturing platform solution. To reference this document use: http://resolver.tudelft.nl/uuid:cd461eb9-f76e-47f0-b7a2-ffd755568d1d Publisher AIAA ISSN 1542-9423 Source Journal of aerospace computing, information and communication, 6(8)2009 Part of collection Institutional Repository Document type journal article Rights (c) 2009 Jin, Y.;Curran, R.;Butterfiel;d, J.;Burke, R.;Welch, B. Files PDF 232544.pdf 760.3 KB Close viewer /islandora/object/uuid:cd461eb9-f76e-47f0-b7a2-ffd755568d1d/datastream/OBJ/view