The fundamental requirement for a coal preparation plant is to transform low value run-of-mine (ROM) material into high value marketable products. The significant aspect relative to the plant is that any gain in efficiency flows almost entirely to the "bottom line" for the operation. The incremental quality concept has gained wide acceptance as the best method to optimize the overall efficiency of the various cleaning circuits. Simply stated, the concept requires that all the cleaning circuits operate as near as possible to the same incremental quality. To ensure optimal efficiency, a plant that receives ROM feed from multiple sources must develop a strategy to operate at the same incremental quality, which yields wide ranges in product qualities from the individual ROM coals. In order to provide products that meet contract specifications, clean coal stockpiles can be utilized to accept coals with various qualities, such as "premium," "low," and "filler" qualities, with shipments formulated from the stockpiles to meet product specifications. A more favorable alternative is raw coal blending to produce the specified clean coal qualities. This study will review the incremental quality concept and present case studies in applying the concept to meet product specifications. / Master of Science

The PCI technology is well established for reducing the consumption of economic and environmentally expensive coke in blast furnace iron-making. Often, coal blends show unexpected combustion performance which cannot be explained on the basis of individual coal properties particularly coal rank and volatile matter. Several coals were combusted in this study under controlled conditions in a drop tube furnace. Fixed bed reactor, XRD, SEM and BET analyses were used to understand the mechanism of combustion of coal blends. Burnout of the coal blends did not change linearly with volatile matter of blends. The study demonstrated that combustion behaviour of coal blends was influenced by several properties of individual coals and cannot be estimated by using any single coal parameter. Carbon structure of coal as well as the interaction of volatile matter of individual coals was found to have a strong influence on the burnout of coal blends. Pet-cokes were generally found to burn with a greater difficulty. Carbon structure of pet-cokes was found to have a significant effect on the burnout such that coal blends with highly ordered pet-coke indicated lower burnout. The study shows that up to 10% of pet coke did not change the burnout of PCI blends significantly. As far as combustion is concerned, the drop tube furnace test provides a reasonable distinction of the effect of coal properties for PCI application.

The operational scheduling at coal handling facilities is of the utmost importance to ensure that the coal consuming processes are supplied with a constant feed of good quality coal. Although the Sasol Coal Handling Facility (CHF) were not designed to perform coal blending during the coal handling process, CHF has to blend the different sources to ensure that the quality of the feed supplied is of a stable nature. As a result, the operation of the plant has become an extremely complex process. Consequently, human intelligence is no longer sufficient to perform coal handling scheduling and therefore a scheduling model is required to ensure optimal plant operation and optimal downstream process performance. After various attempts to solve the scheduling model optimally, i.e. with exact solution methods, it was found that it is not possible to accurately model the complexities of CHF in such a way that the currently available exact solvers can solve it in an acceptable operational time. Various alternative solution approaches are compared, in terms of solution quality and execution speed, using a simplified version of the CHF scheduling problem. This investigation indicates that the Simulated Annealing (SA) metaheuristic is the most efficient solution method to provide approximate solutions. The metaheuristic solution approach allows one to model the typical sequential thoughts of a control room operator and sequential operating procedures. Thus far, these sequential rules could not be modelled in the simultaneous equation environment required for exact solution methods. An SA metaheuristic is developed to solve the practical scheduling model. A novel SA approach is applied where, instead of the actual solution being used for neighbourhood solution representation, the neighbours are indirectly represented by the rules used to generate neighbourhood solutions. It is also found that the initial temperature should not be a fixed value, but should be a multiple of the objective function value of the initial solution. An inverse arctan-based cooling schedule function outperforms traditional cooling schedules as it provides the required diversification and intensification behaviour of the SA. The scheduling model solves within 45 seconds and provides good, practically executable results. The metaheuristic approach to scheduling is therefore successful as the plant complexities and intricate operational philosophies can be accurately modelled using the sequential nature of programming languages and provides good approximate optimal solutions in a short solution time. Tests done with live CHF data indicate that the metaheuristic solution outperforms the current scheduling methodologies applied in the business. The implementation of the scheduler will lead to a more stable factory feed, which will increase production yields and therefore increase company profits. By reducing the amount of coal re-handling (in terms of throw-outs and load-backs at mine bunkers), the scheduler will reduce the coal handling facility’s annual operating cost by approximately R4.6 million (ZAR). Furthermore, the approaches discussed in this document can be applied to any continuous product scheduling environment. Additional information available on a CD stored at Level 3 of the Merensky Library. / Dissertation (MEng (Industrial Engineering))--University of Pretoria, 2011. / Industrial and Systems Engineering / unrestricted