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|Title: ||A methodology for best practice knowledge management|
|Authors: ||Dani, Shilpa S.|
Harding, Jennifer A.
|Keywords: ||Product development|
|Issue Date: ||2006|
|Publisher: ||Professional Engineering Publishing / © IMechE|
|Citation: ||DANI, S.S. ... et al, 2006. A methodology for best practice knowledge management. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 220 (10), pp. 1717-1728|
|Abstract: ||Capturing and reusing knowledge of best practices has been identified as one of the requirements for next-generation product development. Knowledge identification is therefore already being done to some degree in many organizations, through instruction manuals or ‘how to’ guidelines. However, this is only a first step, as to fully exploit valuable knowledge, best practices must be identified and shared. A detailed review of previous research in best practice knowledge management shows that the method of modelling best practice knowledge and the resulting model structure are critically important for the successful reuse of best practice knowledge. Yet, to date, only limited research has been focused on these aspects. This paper therefore presents research into a methodology to determine ways for better communication, sharing, and reuse of best/good practice knowledge. The proposed methodology has been divided into two parts: firstly, the identification of best practices for product development, and secondly, the structuring of best practice knowledge for effective sharing and reuse. This methodology encourages the adoption of best practices by providing knowledge about both process and implementation elements. This makes the explicit knowledge easier to find and reuse. Once a best practice is found to suit current requirements and circumstances, an expert who has identified and used the best practice can also be contacted to gain additional knowledge/information. This helps to address the challenges posed by ‘tacit’ knowledge, which cannot easily be shared within the knowledge base.|
|Description: ||This is an article from the journal, Proceedings of the IMechE, Part B: Journal of Engineering Manufacture [© IMechE]. It is also available at: http://journals.pepublishing.com/content/119784/?p=710e956435344e5bb554ce59223c763c&pi=0|
|Appears in Collections:||Published Articles (Mechanical, Electrical and Manufacturing Engineering)|
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