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Industrial-scale ethyl benzene production optimization using Aspen Plus and MATLAB. Features static optimization (47.6% TAC reduction), dynamic control systems, and comprehensive economic analysis. Demonstrates process systems engineering with material/energy balances, controller tuning, and disturbance analysis.

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Ethyl Benzene Production Optimization: Statics & Dynamics

Project Overview

This project presents a comprehensive simulation study on Ethyl Benzene (EB) production optimization using Aspen Plus software. The work encompasses static optimization for minimum Total Annualized Cost (TAC) and dynamic process control analysis for an industrial-scale ethyl benzene production plant.

Student: Aadityaamlan Panda
Roll Number: 220007
Course: CHE352 - Simulation Lab


🎯 Project Objectives

  1. Static Optimization: Minimize Total Annualized Cost (TAC) through systematic sensitivity analysis
  2. Dynamic Control: Implement and tune process control systems for stable operation
  3. Process Analysis: Evaluate material and energy balances across the production facility
  4. Economic Evaluation: Calculate capital costs, operating costs, and payback periods

🏭 Process Description

The ethyl benzene production process consists of:

Main Equipment:

  • 2 CSTR Reactors (200 Β΅mΒ³ each) - Alkylation reaction
  • 3 Distillation Columns - Product separation and purification
  • Heat Integration System - Energy optimization

Key Streams:

  • Feed Stream: Ethylene (95 mol%) + Ethane (5 mol%) - 105.26 kmol/h
  • Benzene Makeup: Fresh benzene feed for reaction
  • Product Stream: High-purity ethyl benzene (99.9+ mol%)
  • Recycle Streams: Benzene recovery and unreacted materials

πŸ“Š Static Optimization Results

Sensitivity Analysis Sequence:

1. Entrainer Rate Optimization

  • Optimal Benzene Recycle Rate: 193.507 kmol/h
  • Fresh Benzene Makeup: 100.207 kmol/h
  • Energy Consumption: 3690.219 kW

2. Distillate Rate Optimization (Column 2)

  • Benzene Purity in Recycle: 0.989 mol fraction
  • Energy Reduction: 3689.311 kW

3. Reboiler Duty Optimization (Column 2)

  • Benzene Impurity in C2 Bottoms: 6.86 Γ— 10⁻⁡
  • Significant Energy Reduction: 3484.453 kW

4. Distillate Ratio Optimization (Column 3)

  • EB Impurity in Recycle: 0.0012214
  • Final Optimized Energy: 3483.458 kW

Material Balance Summary:

Stream Flow Rate (kmol/h) Key Components
Feed 105.26 Ethylene (95%), Ethane (5%)
Benzene Makeup 100.207 Pure Benzene
Product (C3 Distillate) 99.9106 Ethyl Benzene (99.9%)
C1 Distillate 5.56054 Light Components

Energy Balance:

Equipment Duty (kW) Utility
C1 Reboiler 636.028 High Pressure Steam
C2 Reboiler 1011.8 Medium Pressure Steam
C3 Reboiler 1835.631 High Pressure Steam
Total Heating 3483.459 -
Total Cooling -3804.491 Cooling Water

πŸ’° Economic Analysis

Capital Cost Breakdown:

Component Cost (Γ—10⁢ $)
Column C1 0.2586
Column C2 1.9992
Column C3 4.4117
Total Capital Cost (TCC) 6.6696

Operating Costs:

  • Yearly Operating Cost (YOC): $1.0686 Γ— 10⁢
  • Payback Period (PBP): 3 years
  • Total Annualized Cost (TAC): $3.2918 Γ— 10⁢

πŸ”§ Advanced Optimization using fmincon

Optimization Variables:

  • br_p: Benzene mole purity in recycle stream (0.9883)
  • deb_p: Ethyl benzene impurity in C3 bottoms (0.0216)
  • br_fr: Benzene flow rate in recycle (209.9439 kmol/h)

Optimization Results:

Iteration Initial Guess Final TAC ($)
1 [0.96, 0.02, 190] 1,747,200
2 [0.96, 0.0222, 189.99] 1,739,200
3 [0.97, 0.0222, 189.99] 1,732,100
4 [0.98, 0.0222, 189.99] 1,727,700
5 [0.991, 0.0222, 189] 1,724,500
6 (Final) [0.991, 0.0222, 189] 1,723,900

Final Optimized TAC: $1,723,900 (47.6% reduction from static cost analysis)


πŸŽ›οΈ Dynamic Process Control

Control Strategy Implementation:

Pressure Control (Ziegler-Nichols Tuning):

Controller Gain (Kc) Integral Time (Ο„I)
C1_CondPC 90.6326 1 min
C2_CondPC 73.4499 1 min
C3_CondPC 60.0014 1 min

Temperature Control (Tyreus-Luyben Tuning):

Controller Gain (Kc) Integral Time (Ο„I)
CSTR1_TC 14.5057 9.24 min
CSTR2_TC 105.3682 11.88 min
C1_TopTC 0.1133 11.88 min
C1_BotTC 3.9789 7.92 min
C2_BotTC 11.156 6.6 min
C3_BotTC 83.53 3.96 min

Disturbance Analysis:

Test Cases Evaluated:

  • Β±10% Fresh ethylene flowrate changes
  • Β±4% Fresh ethylene composition changes

Key Performance Indicators:

  • Ethyl Benzene Purity: Maintained at 99.9+ mol% despite disturbances
  • Temperature Control: Stable reactor and column temperatures
  • Flow Control: Effective manipulation of recycle streams

Control Performance:

  • Settling Time: < 40 hours for most disturbances
  • Overshoot: Minimal for temperature and composition variables
  • Steady-State Error: < 0.1% for critical process variables

πŸ”¬ Technical Specifications

Column Design Parameters:

Column Trays Diameter (m) Reboiler Type Condenser Type
C1 11 0.6695 Partial Partial
C2 24 1.2173 Partial Total
C3 29 1.3081 Partial Total

Operating Conditions:

  • CSTR Temperature: 150Β°C (controlled)
  • Pressure: Atmospheric operation
  • Heat Integration: Steam levels (HP/MP/LP) and cooling water

πŸ’» Software & Methodology

Simulation Environment:

  • Aspen Plus: Process simulation and optimization
  • MATLAB: fmincon optimization algorithm implementation
  • Dynamic Simulation: Controller tuning and disturbance analysis

Optimization Techniques:

  1. Sequential Sensitivity Analysis: Systematic parameter variation
  2. Constrained Optimization: fmincon with multiple variables
  3. Controller Tuning: Ziegler-Nichols and Tyreus-Luyben methods

πŸ“ˆ Key Achievements

βœ… 47.6% TAC Reduction: From $3.29M to $1.72M annually
βœ… Robust Control System: Stable operation under Β±10% disturbances
βœ… High Product Purity: 99.9+ mol% ethyl benzene maintained
βœ… Energy Integration: Optimized heat exchange network
βœ… Economic Viability: 3-year payback period achieved


This project demonstrates comprehensive process systems engineering, combining steady-state optimization, dynamic control, and economic analysis for industrial ethyl benzene production.

About

Industrial-scale ethyl benzene production optimization using Aspen Plus and MATLAB. Features static optimization (47.6% TAC reduction), dynamic control systems, and comprehensive economic analysis. Demonstrates process systems engineering with material/energy balances, controller tuning, and disturbance analysis.

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