CASE-BASED REASONING SYSTEM FOR MIXING EQUIPMENT SELECTION

Case-based reasoning (CBR) is an alternative approach to rule-based and object-oriented systems. CBR is based on the retrieval and adaptation of the old solutions to the new problems. There are five steps in CBR: presentation of a new problem, retrieval of the most similar cases, adaptation of the most similar old solutions, validation of the current solution and updating of the system by adding the verified solution to the database of cases. The main advantages of CBR are the easy knowledge acquisition and simple explanatory system. Other important features are easy maintenance and learning capabilities. Determination of the most important features in mixing equipment selection and their importance is studied in this work. The main features discussed are liquid volume and theological parameters, content of particles and/or gas bubbles as well as the type of application and the aim of the process. The retrieval search has been organized by using flat memory and serial search. The following data are given as the output values of the system: impeller and entering type, scale of agitation, mixing power, number of impellers and geometry of tank. An example of CBR applications to the mixing equipment selection in wastewater industry is given.