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Data, information and knowledge have become an important commodity for manufacturing organizations in recent years. The effective capture and reuse of these 'commodities' can assist world-class organizations in maintaining competitive advantage. In the field of manufacturing technology selection, there is a vast amount of experienced information and knowledge sources supporting each phase of the process. These include documentation, technology catalogues, applied technologies and case studies, as well as a range of informal and formal information developed through discussions and meetings.The effective utilization and application of these information and knowledge commodities can assist organizations in next generation decision-making to ensure they select and invest wisely in optimized systems. This paper presents background literature of knowledge acquisition in manufacturing. The data, information and knowledge generated within the technology selection process are then studied. A conceptual framework to improve expertise transfer is presented for manufacturing technology decision support. The model identifies the link in a manufacturing organization to combine and improve the overall approach to manufacturing technology investment by collating relevant experience.

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