Research of the Operator's Advisory System Based on Fuzzy Logic for Pelletizing Equipment

Fertilizer manufacturing in the chemical industry is closely related with agricultural production. More than a half of raw materials for food products are grown by fertilizing plants. The demand of fertilizers has been constantly increasing along the growth of human population. Fertilizer manufacturers face millions of losses each year due to poor quality products. One of the most common reasons is wrong decisions in control of manufacturing processes. Operator’s experience has the highest influence on this. This paper analyzes the pellet measurement data, collected at the fertilizer plant by using indirect measurements. The results of these measurements are used to construct the model of equipment status control, based on the fuzzy logic. The proposed solution allows to respond to changes in production parameters in a 7–10 times faster manner. On average, a manufacturer with production volumes of up to 80 tonnes/hour could have lost about 8400 tonnes/year of high-quality production. The publication seeks symmetry between human and system decision making.

[1]  Krzysztof Okarma,et al.  Objective 3D Printed Surface Quality Assessment Based on Entropy of Depth Maps , 2019, Entropy.

[2]  Kim H. Esbensen,et al.  Acoustic chemometrics - monitoring of chemical production processes , 2007 .

[3]  Nihat Dipova,et al.  DETERMINING THE GRAIN SIZE DISTRIBUTION OF GRANULAR SOILS USING IMAGE ANALYSIS , 2017 .

[4]  Nick J. Miles,et al.  An improved estimation of size distribution from particle profile measurements , 2006 .

[5]  Muvvala Sudhakar,et al.  Advances in Granulation Technology , 2016 .

[6]  Nejat Rahmanian,et al.  University of Huddersfield Repository Finishing Process: , 2022 .

[7]  Nick J. Miles,et al.  Improving particle size measurement using multi-flash imaging , 2009 .

[8]  Ahmet Ozan Gezerman,et al.  A New Approach to Cooling and Prilling during Fertilizer Manufacture , 2011 .

[9]  N. Pappa,et al.  Image Analysis for Particle Size Distribution , 2014 .

[10]  Petrak Dieter,et al.  In-line particle sizing for real-time process control by fibre-optical spatial filtering technique (SFT) , 2011 .

[11]  ハイネ マーティン,et al.  Apparatus for determining the particle size , 2010 .

[12]  Andrew W. Hamilton,et al.  Image analysis framework with focus evaluation for in situ characterisation of particle size and shape attributes , 2018, Chemical Engineering Science.

[13]  Andrius Laucka,et al.  Research of the Equipment Self-Calibration Methods for Different Shape Fertilizers Particles Distribution by Size Using Image Processing Measurement Method , 2019, Symmetry.

[14]  Jurgita Antucheviciene,et al.  Civil Engineering and Symmetry , 2019, Symmetry.

[15]  Richard Wisniewski.  Spray Drying Technology Review , 2015 .

[16]  Nejat Rahmanian,et al.  SIMULATION OF UREA PRILLING PROCESS: AN INDUSTRIAL CASE STUDY , 2013 .

[17]  Ian Larson,et al.  Importance of particle size and shape on the tensile strength distribution and de-agglomeration of cohesive powders , 2013 .

[18]  Yakup Kutlu,et al.  A Real-Time Parallel Image Processing Approach on Regular PCs with Multi-Core CPUs , 2017 .

[19]  W. K. Zahra,et al.  Study on Heat and Mass Transfer During Urea Prilling Process , 2012 .

[20]  Vincenzo Piuri,et al.  3-D Granulometry Using Image Processing , 2019, IEEE Transactions on Industrial Informatics.

[21]  Lei Tian,et al.  Measuring particle size distribution using LED-illumination , 2010 .

[22]  Saad N. Saleh,et al.  Reduction of Dust Emission by Monodisperse System Technology for Ammonium Nitrate Manufacturing , 2017 .

[23]  Evangelos Tsotsas,et al.  Multiscale Approaches to Processes That Combine Drying with Particle Formation , 2015 .

[24]  Colin Hare,et al.  Auto-granulation of Fine Cohesive Powder by Mechanical Vibration , 2015 .

[25]  Pedro Castro,et al.  GRAIN-SIZE MEASUREMENTS OF FLUVIAL GRAVEL BARS USING OBJECT-BASED IMAGE ANALYSIS , 2018 .

[26]  Algimantas Valinevicius,et al.  Research of the Equipment Calibration Methods for Fertilizers Particles Distribution by Size Using Image Processing Measurement Method , 2018, 2018 23rd International Conference on Methods & Models in Automation & Robotics (MMAR).

[27]  Krzysztof Okarma,et al.  Current Trends and Advances in Image Quality Assessment , 2019, Elektronika ir Elektrotechnika.

[28]  Edward J. Garboczi,et al.  Measurement of particle size distribution and specific surface area for crushed concrete aggregate fines , 2017 .

[29]  Nejat Rahmanian,et al.  CFD Simulation of Droplet Formation under Various Parameters in Prilling Process , 2014 .

[30]  P. R. Sharma,et al.  Ultrasound promoted efficient and green protocol for the expeditious synthesis of 1, 4 disubstituted 1, 2, 3-triazoles using Cu(II) doped clay as catalyst , 2013 .

[31]  Victor V. Kozlov,et al.  Round Jets in a Cross Shear Flow , 2012 .

[32]  Krzysztof Okarma,et al.  Prediction of the Optical Character Recognition Accuracy based on the Combined Assessment of Image Binarization Results , 2015 .

[33]  V. Piuri,et al.  D Granulometry Using Image Processing , 2018 .

[34]  Yuan Wu,et al.  An Innovated Tower-fluidized Bed Prilling Process , 2007 .

[35]  伍沅,et al.  An Innovated Tower-fluidized Bed Prilling Process , 2007 .

[36]  M. Massinaei,et al.  Estimation of particle size distribution on an industrial conveyor belt using image analysis and neural networks , 2014 .