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Advances in Nano Research
  Volume 12, Number 4, April 2022 , pages 375-386
DOI: https://doi.org/10.12989/anr.2022.12.4.375
 


Artificial neural fuzzy system and monitoring the process via IoT for optimization synthesis of nano-size polymeric chains
Shihao Hou, Luyu Qiao and Lumin Xing

 
Abstract
    Synthesis of acrylate-based dispersion resins involves many parameters including temperature, ingredients concentrations, and rate of adding ingredients. Proper controlling of these parameters results in a uniform nano-size chain of polymer on one side and elimination of hazardous residual monomer on the other side. In this study, we aim to screen the process parameters via Internet of Things (IoT) to ensure that, first, the nano-size polymeric chains are in an acceptable range to acquire high adhesion property and second, the remaining hazardous substance concentration is under the minimum value for safety of public and personnel health. In this regard, a set of experiments is conducted to observe the influences of the process parameters on the size and dispersity of polymer chain and residual monomer concentration. The obtained dataset is further used to train an Adaptive Neural network Fuzzy Inference System (ANFIS) to achieve a model that predicts these two output parameters based on the input parameters. Finally, the ANFIS will return values to the automation system for further decisions on parameter adjustment or halting the process to preserve the health of the personnel and final product consumers as well.
 
Key Words
    hazardous material; healthcare; internet of things (IoT); optimization; process monitoring
 
Address
Shihao Hou and Luyu Qiao: School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, China 250220

Lumin Xing: The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, 250014, China/ City University of Macau, Macau, 999078, China
 

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