1. ¹RMIT University, Melbourne, Victoria, Australia
2. ²Swinburne University of Technology, Hawthorn, Australia

Correspondence: MG Nicholls, Graduate School of Business, RMIT University, GPO Box 2476V, Melbourne, Victoria 3001, Australia. E-mail: miles.nicholls@rmit.edu.au

Based on an idea contained in a paper delivered to the Decision Sciences Institute's 36th Annual Meeting at San Francisco, USA, 19–22 November 2005.

Received 1 January 2006; Accepted 1 July 2006; Published online 8 November 2006.

Abstract

This paper considers the difficulties associated with a production process that contains a sub-process that is not fully understood and for which data for many parameters are only able to be approximately obtained. The aluminium smelting industry epitomizes such a situation. Here, the critical sub-process that exemplifies these difficulties is the actual heart of the smelter, the electrolytic processing of alumina. This sub-process of aluminium production is at best 'fuzzy' and relies on the smelter operators to use their experience and tacit knowledge on a day-to-day basis, that is, the sub-process involves 'alchemy'. In this paper, this is referred to as the tacit knowledge problem. The impact of such sub-processes on production is significant and the development of a methodology that will lead to a reduced reliance on uncertain alchemy associated with them, highly beneficial. The role of Communities of Practice in finding a solution to the tacit knowledge problem is discussed together with its integration into a mixed-mode model for the determination of best practice production for the smelter.