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Global megatrends such as scarcity of natural resources and urbanization have been the drivers for a mining sector upswing. Therefore, the mining sector in Finland, with attractive ore geology, has recently experienced rapid growth and new mines have been opened. At the same time, society's expectations have increased, resulting in a public debate on mining companies' environmental and social responsibility. Companies have the same positioning choices relative to their competitors, but environmental issues are a new area of interest in order to stand out strategically. In this study of companies with mining operations in Finland, strategic environmental management practices are examined based on companies' own public information. This article takes a closer look at whether their public reporting projects an image of strategic environmental management. The results show that environmental and social considerations are essential elements in companies' commitments and strengthen their business strategy. This study also shows a gap between strategic commitments and their implementation, based on the company reports.

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Artificial intelligence (AI) includes excellent tools for the control and supervision of industrial processes. Several thousand industrial applications have been reported worldwide. Recently, the designers of the AI systems have begun to hybridize the intelligent techniques, expert systems, fuzzy logic and neural networks, to enhance the capability of the AI systems. Expert systems have proved to be ideal candidates especially for the control of mineral processes. An expert system based on on-line classification of the ore type has been developed. Self-organizing maps (SOM) are used for pattern recognition of the type of feed. The system has been tested in two concentrators, the Outokumpu Finnmines Oy, Hitura Mine and Outokumpu Chrome Oy, Kemi Mine. The methodology for the development of the ore type based expert system is presented and the preliminary results obtained in the above plants are described.

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