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Title: Acquisition and sharing of innovative manufacturing knowledge for preliminary design
Author: Mountney, Sara
ISNI:       0000 0004 2679 2974
Awarding Body: Cranfield University
Current Institution: Cranfield University
Date of Award: 2009
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This study investigates the identification, acquisition and sharing of innovative manufacturing knowledge for the preliminary design of complex mechanical components. Such components need to satisfy multiple, often conflicting design and performance requirements. Some degree of innovation may be required, involving the development of new manufacturing processes. The innovative nature of this manufacturing knowledge makes it difficult to define, codify and share, especially during preliminary design, where this can present significant risks in the design process. Current methods of knowledge sharing do not account for the immature nature of innovative manufacturing knowledge and the combined explicit and tacit elements needed to express it. A flexible interpretive research study with inductive and hypothesis testing elements was undertaken to explore this novel knowledge management problem. During the inductive phase, two data collection activities were undertaken to investigate the manufacturing knowledge required for the preliminary design of gas turbine engines. Using a data driven approach, the main findings which emerged were: the need to include an assessment of the maturity of the design process; the need to use a range of tacit and explicit knowledge to effectively share this and the need to manage knowledge across different domain boundaries. A conceptual framework of the findings was used to develop a hypothesis of knowledge requirements for preliminary design. For the hypothesis testing phase, a systematic methodology to identify, acquire and share innovative manufacturing knowledge for preliminary design was developed from the knowledge requirements. This approach allowed both explicit and tacit knowledge sharing. An evaluation of the methodology took place using three different industrial cases, each with a different component / manufacturing process. The evaluations demonstrated that using the range of knowledge types for transferring knowledge was effective for the specific cases studied and confirmed the hypothesis developed.
Supervisor: Gao, James ; Roy, Rajkumar Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available