An introduction to mineral processing, hydrometallurgy, pyrometallurgy, and electro-metallurgy, and to adaptive metallurgy. Terminology, principles, processes, flow diagrams and overview of local and foreign metallurgical industries.
The course is designed for undergraduate engineering students with emphasis on problem-solving related to societal that engineers and scientists area called upon to solve. It introduces different methods of data collection and the suitability of using a particular methods for a given situation. It includes coverage and discussion of the relationship of probability to statistics, providing students with tools they need to understand how “chance” plays a role in statistical analysis. Probability distributions of random variables and their uses, are also considered, along with a discussion of linear functions of random variables within the context of their application to data analysis and inference. The course also include estimation techniques for unknown parameters, and hypothesis testing used in making inferences from sample to population, inference for regressions parameters and build models for estimating means and predicting future values of key variables under study Finally, statistically based experimental design techniques and analysis of data are discussed with the aid of relevant statistical software.
Criteria for the selection of underground mining method including coal mining. Techniques, unit operations and mine systems involved in the different underground mining methods. Development planning, engineering layout and extraction. Underground haulage systems, draw and grade control.