Parametric Optimization of Medical Plastic Wastes Conversion into Transportation Fuel using Mamdani Fuzzy Inference Systems (FIS)

Abstract

Rapid growth of medical plastic wastes required attention for its scientific disposal along with conversion into value added products. Pyrolysis method is found suitable process for such conversion of such wastes into liquid oil. The experiment was carried out with the medical plastic wastes collected from local medicals and treated in a batch reactor taking appropriate range of temperature change and use of Calcium bentonite (CB) and Zeolite-A (ZA) as catalysts. The yield of liquid oil, gas and char produced from the process are collected in scale. The yield of liquid fuel in this process was influenced by factors such as temperature, catalyst concentration and acidity of catalyst. It was observed that yield of liquid fuel in this process were significantly dependent on temperature, nature of catalyst and catalyst concentration. The maximum yield of oil reported at 500 C and even increased by adding 20% by weight of CB as catalyst and 10% by weight of Z-A. In this study, Mamdani Fuzzy inference System (FIS) is used in order to measure the performance of the process and can be analyzed with more objectives, oriented through mathematical modelling and simulation. Mamdani Fuzzy inference was also introduced to identify the significant factors affecting the response and helps to determine the best possible factor level of combination. Finally, a regression model for liquid fuel from catalytic degradation of medical plastic wastes has been developed and mapped as a function of process parameters.