Mechanical Alloying is a manufacturing process that produces alloys by cold welding of powders. Usually, a vial containing both the powder and steel balls is agitated. Due to impact between the balls and balls and the vial, the powder is mechanically deformed, crushed, and mixed at nano-scales. In this thesis, a numerical model is developed to simulate the dynamics of the vial and the grinding balls of the SPEX 8000 ball milling device, a standardized equipment in both industrial and academic investigations of ball milling. The numerical model is based on the Event Driven Method, typically used to model granular flows. The method implemented is more efficient than the discrete element method used previously to study ball milling dynamics. The numerical tool obtained is useful for scale-up and optimization of mechanical alloying of various materials. An optimization study is presented for the SPEX 8000.

Mechanical Alloying is a manufacturing process that produces alloys by cold welding of powders. Usually, a vial containing both the powder and steel balls is agitated. Due to impact between the balls and balls and the vial, the powder is mechanically deformed, crushed, and mixed at nano-scales. In this thesis, a numerical model is developed to simulate the dynamics of the vial and the grinding balls of the SPEX 8000 ball milling device, a standardized equipment in both industrial and academic investigations of ball milling. The numerical model is based on the Event Driven Method, typically used to model granular flows. The method implemented is more efficient than the discrete element method used previously to study ball milling dynamics. The numerical tool obtained is useful for scale-up and optimization of mechanical alloying of various materials. An optimization study is presented for the SPEX 8000.

Mechanical Alloying is a manufacturing process that produces alloys by cold welding of powders. Usually, a vial containing both the powder and steel balls is agitated. Due to impact between the balls and balls and the vial, the powder is mechanically deformed, crushed, and mixed at nano-scales. In this thesis, a numerical model is developed to simulate the dynamics of the vial and the grinding balls of the SPEX 8000 ball milling device, a standardized equipment in both industrial and academic investigations of ball milling. The numerical model is based on the Event Driven Method, typically used to model granular flows. The method implemented is more efficient than the discrete element method used previously to study ball milling dynamics. The numerical tool obtained is useful for scale-up and optimization of mechanical alloying of various materials. An optimization study is presented for the SPEX 8000.

Mechanical Alloying is a manufacturing process that produces alloys by cold welding of powders. Usually, a vial containing both the powder and steel balls is agitated. Due to impact between the balls and balls and the vial, the powder is mechanically deformed, crushed, and mixed at nano-scales. In this thesis, a numerical model is developed to simulate the dynamics of the vial and the grinding balls of the SPEX 8000 ball milling device, a standardized equipment in both industrial and academic investigations of ball milling. The numerical model is based on the Event Driven Method, typically used to model granular flows. The method implemented is more efficient than the discrete element method used previously to study ball milling dynamics. The numerical tool obtained is useful for scale-up and optimization of mechanical alloying of various materials. An optimization study is presented for the SPEX 8000.

The key objective of this research is to develop a generic simulation modelling methodology that can be used to model stochastic continuous systems effectively. The generic methodology renders simulation models that exhibit the following characteristics: short development and maintenance times, user-friendliness, short simulation runtimes, compact size, robustness, accuracy and a single software application. The research was initiated by the shortcomings of a simulation modelling method that is detailed in a Magister dissertation. A system description of a continuous process plant (referred to as the Synthetic Fuel plant) is developed. The decision support role of simulation modelling is considered and the shortcomings of the original method are analysed. The key objective, importance and limitations of the research are also discussed. The characteristics of stochastic continuous systems are identified and a generic methodology that accommodates these characteristics is conceptualised and developed. It consists of the following eight methods and techniques: the variables technique, the iteration time interval evaluation method, the event-driven evaluation method, the Entity-represent-module method, the Fraction-comparison method, the iterative-loop technique, the time “bottleneck” identification technique and the production lost “bottleneck” identification technique. Five high-level simulation model building blocks are developed. The generic methodology is demonstrated and validated by the development and use of two simulation models. The five high-level building blocks are used to construct identical simulation models of the Synthetic Fuel plant in two different simulation software packages, namely: Arena and Simul8. An iteration time interval and minimum sufficient sample sizes are determined and the simulation models are verified, validated, enhanced and compared. The simulation models are used to evaluate two alternative scenarios. The results of the scenarios are compared and conclusions are presented. The factors that motivated the research, the process that was followed and the generic methodology are summarised. The original method and the generic methodology are compared and the strengths and weaknesses of the generic methodology are discussed. The contribution to knowledge is explained and future developments are proposed. The possible range of application and different usage perspectives are presented. To conclude, the lessons learnt and reinforced are considered. / Thesis (PhD (Industrial Engineering))--University of Pretoria, 2004. / Industrial and Systems Engineering / unrestricted