Theoretical Optimization of Compressive Crushing
Licentiate thesis, 2009
Surrounded by products made from crushed rock materials in all corners of society, most people do not spend much time thinking about when, where, or how these are produced. In fact, most people take the supply and availability of products made from crushed rock materials for granted. One is only reminded of the raw material crushed rock when passing by construction work, or during winter when streets and roads are slippery. Nevertheless, crushed rock material or products made from it can be found in roads, railways, constructions, and all things made from metal.
Crushed rock materials can roughly be divided into aggregates and ores. These products are supplied by the aggregate and mining industry. However, along with the growing world population, increased urbanization, and improved standard of living, this industry is today faced with the challenge of meeting a rapidly rising product demand. In addition, industry is also confronted with additional demands of energy savings as well as considerations for sustainability and environment. For the rock processing industry, this means that efforts must be put towards improving the performance and efficiency of existing crushers and crushing processes. This requires a deeper fundamental understanding about the crushing process itself. The objective of this research is and has, therefore, been to develop the existing knowledge about compressive crushing and to eventually give advice for crusher design.
In the present research work, four technically interesting rock materials (i.e. gneiss, diabase, marble, and quartzite) were studied. Their compressive breakage behaviors were characterized using piston-die equipment and were subsequently modeled to enable theoretical optimizations. More specifically, genetic evolutionary algorithms were applied in order to study how the different rock materials should be crushed compressively given different optimization objectives expressed by so called fitness functions. Aspects such as product yield, energy consumption, and crushing pressure were considered.
Results indicate that the tested materials should, under the studied circumstances, be crushed with fewer and/or smaller compressions than what is believed to be applied in existing crushers. It is thus suggested that modern cone crushers do not work optimally in any of the studied aspects for any of the studied materials. In fact, it is believed that considerable improvements can be made for a crushing unit in terms of product yield. Significant gains considering capacity, energy consumption, and product yield are also indicated by crushing plant simulations. Future work should therefore include extended studies of existing crushers (i.e. with regards to their performance and dynamics) and implementation of research results in terms of conceptual crusher design. The objective of such implementation should be to improve the performance and efficiency of existing crushing equipment as well as to inspire for the next generation of compression crushers.
Genetic Evolutionary Algorithms