Detail publikace

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

Originální název

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

Anglický název

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

Jazyk

en

Originální abstrakt

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. The 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, the manufacturer with the 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.

Anglický abstrakt

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. The 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, the manufacturer with the 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.

Plný text v Digitální knihovně

BibTex


@article{BUT159875,
  author="Darius {Andriukaitis} and Andrius {Laucka} and Algimantas {Valinevicius} and Mindaugas {Zilys} and Vytautas {Markevicius} and Dangirutis {Navikas} and Roman {Šotner} and Jiří {Petržela} and Jan {Jeřábek} and Norbert {Herencsár} and Dardan {Klimenta}",
  title="Research of the Operator's Advisory System Based on Fuzzy Logic for Pelletizing Equipment",
  annote="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. The 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, the manufacturer with the 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.",
  address="MDPI",
  chapter="159875",
  doi="10.3390/sym11111396",
  howpublished="online",
  institution="MDPI",
  number="11",
  volume="11",
  year="2019",
  month="november",
  pages="1--17",
  publisher="MDPI",
  type="journal article in Web of Science"
}