Sensitivity Analysis of Reactor and Distillation Column of Paraxylene Plant via Toluene Methylation Based on Simulation Process

Paraxylene is an important industrial compound, and its demand has been increasing in recent years. Paraxylene is made in several processes, one of which is toluene methylation. Furthermore, it is necessary to do a simulation to determine the optimal operating conditions in the formation and separation of paraxylene. The simulation was done using process simulation software. The first research design scheme was data validation. The results of the data validation obtained 3 – 4 % error indicated that the simulation was validated and can be used for the next step which is sensitivity analysis. The sensitivity analysis was performed to obtain the optimum reactor and column configuration. Based on the simulation of paraxylene production through toluene methylation process, the obtained purity was over 95%. The temperature and pressure of the reactor feed 600°C and 7 bar were obtained, the weight of the catalyst was 15,000 kg, the ratio of the catalyst feed to the toluene feed 37, and the ratio of the toluene feed to methanol 2. The optimal feed stage was obtained at the 18 stage, the number of stages was 27, the load a reboiler of 18,000 kW, and a reflux ratio of 2.

Authors

Institutions

Publication Details

Journal
Journal of Advanced Research in Fluid Mechanics and Thermal Sciences
Published
2025-04-20
DOI
https://doi.org/10.37934/arfmts.130.1.173184
Primary Topic
Industrial Technology and Control Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sensitivity Analysis of Reactor and Distillation Column of Paraxylene Plant via Toluene Methylation Based on Simulation Process

Sumaiya Zainal Abidin, Haniif Prasetiawan, Dewi Selvia Fardhyanti
Journal of Advanced Research in Fluid Mechanics and Thermal Sciences
Industrial Technology and Control Systems
article

Sensitivity Analysis of Reactor and Distillation Column of Paraxylene Plant via Toluene Methylation Based on Simulation Process

Sumaiya Zainal Abidin, Haniif Prasetiawan, Dewi Selvia Fardhyanti
article en

Abstract

Paraxylene is an important industrial compound, and its demand has been increasing in recent years. Paraxylene is made in several processes, one of which is toluene methylation. Furthermore, it is necessary to do a simulation to determine the optimal operating conditions in the formation and separation of paraxylene. The simulation was done using process simulation software. The first research design scheme was data validation. The results of the data validation obtained 3 – 4 % error indicated that the simulation was validated and can be used for the next step which is sensitivity analysis. The sensitivity analysis was performed to obtain the optimum reactor and column configuration. Based on the simulation of paraxylene production through toluene methylation process, the obtained purity was over 95%. The temperature and pressure of the reactor feed 600°C and 7 bar were obtained, the weight of the catalyst was 15,000 kg, the ratio of the catalyst feed to the toluene feed 37, and the ratio of the toluene feed to methanol 2. The optimal feed stage was obtained at the 18 stage, the number of stages was 27, the load a reboiler of 18,000 kW, and a reflux ratio of 2.

Journal of Advanced Research in Fluid Mechanics and Thermal SciencesVol. 130(1)
Universiti Malaysia Pahang Al-Sultan Abdullah (MY), State University of Semarang (ID)
Universitas Negeri Semarang
Openalex Percentile: Top 91%
Industrial Technology and Control Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.