Article from SYMBIOSIS July 2008
Enhancing safety and production with automation By Colin Farrelly and Jarrod Basson
CSC and the CRCMining recently conducted a joint studyon the application of advanced analytical techniques in the mining industry. The research looked at the challenges faced by the mining industry today, and how advanced analytics have been employed inother industries, such as aerospace, utilities, petroleum and manufacturing, to overcome similar challenges. Advanced analytics techniques can help overcome some of the fundamental operational andhuman resources challenges faced by the mining industry today by applying data techniques not previously applied in mining. While the implementation of data historians, MES (Manufacturing ExecutionSystems) and Plant Information Managements Systems provide the ability to capture and store more information about the mining and processing operations, paradoxically, the sheer volume of data available ismaking it difficult to use this information for making better decisions. Today, decisions are usually locally optimized but do not achieve optimum capability for the value chain. Although moreinformation is collected then ever before, it is difficult to link many sources of data together in the same place in real-time, for example plant history, maintenance, mine planning, logistics andengineering data. Consequently, complex analysis of data is time consuming and requires specialist skills and knowledge, and is often neglected in the decision-making process. In the future, analytics willclose the loop between analysing data and taking action. Analytics will become embedded in the business and routinely applied to improve decision making across the organisation, from senior management tooperations and maintenance workers, but will not require specialist skills or be as time consuming. As analytics becomes embedded in the business process, decisions are supported by data (not on...
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