Markov Chain Modelling of the Re-circulatory Fluidised Bed Granulation: Stochastic Processes

Stochastic models which can be based on Markov chain theory is a very valuable tool because of its simplicity and flexibility. The Markov theory has been applied in many fields such as telecommunication, astronomy, microbiology, risk analysis after Andrei Andreyevic Markov released his work in 1922. The characteristic property of a Markov process is that it retains no memory of where it has been in the past. That is only the current state of the process can influence where it goes next. This book focused on the Markov chain modelling of fluidised bed granulation. Granulation is a good example to describe a complex process. In the end it is a net growth process, but there are several sub-processes, which are also very complicated, have to be considered. For instance, particle motion, inter-particle collisions, particle-binder droplet collisions, kinetics of particle wetting, aggregation and breakage might be counted as the first sight.

Asst. Prof. Dr. Muammer Catak completed his Ph.D degree in Process Engineering at University College Cork, Ireland in 2010; his MSc. degree in Electrical Engineering at Blekinge Institute of Technology, Sweden in 2006, and his BSc. degree in Electrical and Electronics Engineering at Middle East Technical University,Turkey in 2004.