Fuzzy Method for in Control Acetaldehyde Generation in Resin Pet in the Process of Packaging Pre-Forms of Plastic Injection

Carlos Alberto Monteiro, Emanuel Negrão Macêdo, Manoel Henrique Reis Nascimento, Carlos Alberto Oliveira de Freitas, Jorge de Almeida Brito Junior

Packaging, Fuzzy Logic, Inference Rules, Computational Intelligence, PET, Acetaldehyde.

In order to control the drying temperature of the PET resin in the silo of the plastic injection molding machine, during the plastic injection process in the industries producing preforms for the manufacture of beverage bottles, care is taken in the ideal temperature regulation for the better performance in controlling the generation of Acetaldehyde (AA), which alters the taste of carbonated or non-carbonated drinks, providing a citrus nuance to the palate and questioning the quality of the packaged products The objective of this work is to develop a tool based on Fuzzy logic to support the control of the drying temperature of PET resin, allowing specialists to make the ideal temperature control decisions necessary to control the generation of Acetaldehyde (AA). For the development of the proposed Fuzzy inference model, we used the Matlab Fuzzy toolbox tool, where the input variables, the fuzzyfication rules and the output variable were implemented based on the data collected from the preform injection process. From the inference model, we obtained a more precise management of the variables that influence the generation of AA, estimating a reduction of $ 240,044.00 in annual costs in the production of preforms.

10.22161/ijaers.5.8.29