Process Simulation, Modelling and Optimization for Chemical Plants Training Course

Course Introduction

Process simulation, modelling, and optimization have become indispensable tools in modern chemical engineering, enabling organizations to design safer, more efficient, and highly profitable manufacturing facilities. As chemical plants become increasingly integrated and complex, engineers must accurately predict process behavior, evaluate operating scenarios, optimize energy consumption, improve product quality, and reduce production costs before implementing physical modifications. This Process Simulation, Modelling and Optimization for Chemical Plants Training Course equips participants with advanced engineering knowledge and practical methodologies to develop reliable process models, conduct detailed simulations, and implement optimization strategies that improve operational excellence, sustainability, and long-term plant competitiveness.

Modern chemical plants require engineers capable of integrating thermodynamics, fluid flow, heat and mass transfer, reaction engineering, process control, equipment performance, utility systems, and economic evaluation into comprehensive simulation models. This course provides detailed coverage of steady-state and dynamic simulation, process modelling techniques, flowsheet development, model validation, sensitivity analysis, optimization algorithms, equipment performance analysis, and integrated plant-wide simulation. Participants will gain practical expertise in evaluating alternative operating conditions, minimizing process variability, optimizing resource utilization, and improving plant reliability through advanced engineering analysis.

Participants will strengthen their capabilities through practical workshops, industrial case studies, simulation exercises, engineering calculations, and optimization projects that replicate real-world chemical processing environments. The course emphasizes process flowsheet development, simulation model construction, calibration techniques, troubleshooting methodologies, process debottlenecking, utility optimization, production planning, operational flexibility, and continuous process improvement. Practical applications span petrochemical plants, refineries, fertilizer facilities, specialty chemical plants, pharmaceutical manufacturing, food processing, and industrial chemical production systems.

Emerging digital technologies are revolutionizing process engineering by combining simulation platforms with artificial intelligence, machine learning, digital twins, Industrial Internet of Things (IIoT), advanced process control, predictive analytics, cloud computing, big data analytics, and virtual commissioning. Participants will explore how intelligent simulation environments improve predictive maintenance, energy optimization, production forecasting, emissions reduction, operator training, process automation, and real-time operational decision-making while supporting Industry 4.0 and smart manufacturing initiatives.

The course also emphasizes sustainability, energy efficiency, process safety, carbon reduction, circular economy practices, environmental compliance, ESG integration, lifecycle engineering, operational resilience, and risk-based optimization. Participants will examine engineering strategies that reduce greenhouse gas emissions, improve heat recovery, optimize utility systems, minimize waste generation, enhance process flexibility, and strengthen plant resilience while maintaining world-class safety, reliability, and environmental performance.

Upon successful completion of this training course, participants will possess advanced competencies in process simulation, mathematical modelling, process optimization, digital engineering, plant-wide analysis, and engineering decision-making. They will be capable of developing accurate simulation models, optimizing production systems, improving process efficiency, reducing operating costs, supporting capital investment decisions, and implementing innovative engineering solutions that deliver measurable operational, environmental, and economic improvements across modern chemical processing facilities.

Duration

10 days

Who Should Attend

• Chemical Engineers

• Process Engineers

• Production Engineers

• Plant Design Engineers

• Process Simulation Engineers

• Operations Engineers

• Process Control Engineers

• Plant Managers

• Commissioning Engineers

• Project Engineers

• Energy Engineers

• Mechanical Engineers in process industries

• Process Improvement Specialists

• Manufacturing Engineers

• Refinery Engineers

• Petrochemical Engineers

• Technical Managers

• Research and Development Engineers

• Utility Engineers

• Professionals involved in chemical plant optimization

Course Objectives

• Develop comprehensive knowledge of process simulation methodologies, mathematical modelling techniques, and optimization strategies supporting high-performance chemical manufacturing systems.

• Understand steady-state and dynamic simulation principles, thermodynamic modeling, reaction engineering integration, and process equipment representation for accurate engineering analysis.

• Gain practical expertise in developing process flowsheets, constructing simulation models, validating engineering assumptions, and evaluating alternative plant operating scenarios.

• Learn advanced techniques for sensitivity analysis, optimization algorithms, process debottlenecking, utility optimization, production forecasting, and operational performance enhancement.

• Build competency in process model calibration, equipment performance analysis, plant-wide integration, operational troubleshooting, and continuous process improvement using engineering best practices.

• Master engineering methodologies for optimizing reactors, distillation systems, heat exchangers, utility networks, separation units, and integrated process facilities while improving efficiency.

• Strengthen capabilities in evaluating process economics, lifecycle performance, sustainability metrics, energy efficiency, emissions reduction, and engineering investment decision support.

• Develop practical understanding of artificial intelligence, digital twins, Industrial Internet of Things, advanced process control, predictive analytics, cloud-based engineering platforms, and smart manufacturing technologies.

• Apply advanced process modelling techniques to improve operational flexibility, product quality, plant reliability, safety performance, and resource utilization across chemical manufacturing facilities.

• Improve engineering decision-making through process simulation, statistical analysis, optimization studies, uncertainty evaluation, scenario analysis, and operational benchmarking methodologies.

• Explore emerging topics including autonomous process optimization, Industry 4.0 integration, hydrogen-ready process simulation, carbon capture modelling, and digital engineering innovations.

• Equip participants with practical skills to develop, optimize, validate, troubleshoot, and continuously improve chemical process simulation models while supporting operational excellence and sustainable industrial development.

Comprehensive Course Outline

Module 1: Fundamentals of Process Simulation and Modelling

• Principles of process simulation supporting advanced chemical plant engineering design

• Mathematical modelling techniques for integrated chemical process representation

• Simulation workflow from conceptual model development to operational validation

• International engineering standards supporting process modelling best practices

Module 2: Thermodynamics and Property Estimation

• Thermodynamic property packages supporting accurate chemical process simulation models

• Phase equilibrium calculations improving separation process engineering performance

• Equation of state selection for complex chemical processing applications

• Property estimation techniques supporting reliable engineering model predictions

Module 3: Process Flowsheet Development

• Building comprehensive process flowsheets for integrated manufacturing facilities

• Material and energy balance development using engineering simulation techniques

• Process configuration evaluation supporting operational optimization opportunities

• Engineering documentation supporting simulation model development and validation

Module 4: Reactor Modelling and Simulation

• Mathematical reactor models supporting reaction engineering performance optimization

• Kinetic parameter estimation improving simulation accuracy and engineering reliability

• Batch, continuous, and catalytic reactor simulation methodologies comprehensively explained

• Reactor optimization techniques maximizing conversion and product selectivity outcomes

Module 5: Separation Process Simulation

• Distillation modelling improving separation efficiency and energy utilization performance

• Membrane process simulation supporting advanced separation engineering applications

• Absorption and extraction model development for integrated chemical processing

• Hybrid separation technologies enhancing plant-wide process optimization capabilities

Module 6: Heat Transfer and Utility System Modelling

• Heat exchanger network simulation supporting integrated thermal energy optimization

• Utility system modelling improving steam, cooling, and refrigeration efficiency

• Pinch analysis integration within process simulation and optimization workflows

• Waste heat recovery simulation supporting sustainable industrial operations

Module 7: Dynamic Simulation Techniques

• Dynamic simulation principles supporting startup, shutdown, and transient process analysis

• Operational scenario evaluation improving plant flexibility and production resilience

• Process disturbance modelling supporting advanced operational troubleshooting capabilities

• Dynamic optimization techniques improving real-time production performance outcomes

Module 8: Process Equipment Performance Analysis

• Equipment performance modelling supporting operational reliability and efficiency improvements

• Pump, compressor, and valve simulation within integrated process models

• Hydraulic analysis supporting optimized process fluid transportation system design

• Equipment degradation modelling supporting predictive maintenance planning activities

Module 9: Process Optimization Methodologies

• Optimization algorithms supporting production efficiency and operating cost reduction

• Multi-objective optimization balancing productivity, safety, and sustainability objectives

• Constraint analysis improving plant operational flexibility and optimization results

• Economic optimization techniques supporting profitable process engineering decisions

Module 10: Plant-Wide Integration and Optimization

• Integrated plant simulation supporting facility-wide engineering performance improvements

• Utility network optimization reducing operational energy consumption significantly

• Production scheduling integration supporting optimized manufacturing system performance

• Debottlenecking studies increasing production capacity through engineering optimization

Module 11: Digital Engineering Technologies

• Artificial intelligence enhancing predictive process simulation and optimization capabilities

• Digital twins supporting virtual plant operation and engineering decision-making

• Industrial Internet of Things integrating real-time operational process information

• Cloud-based simulation platforms improving engineering collaboration and productivity

Module 12: Process Control Integration

• Advanced process control integration with simulation-based optimization methodologies

• Control strategy evaluation using dynamic process simulation environments

• Process monitoring techniques improving operational stability and product consistency

• Operator training simulators supporting safe plant operation and competency development

Module 13: Sustainability and Environmental Optimization

• Energy optimization strategies reducing environmental impacts and operating costs

• Carbon emission modelling supporting industrial decarbonization engineering initiatives

• Circular economy integration improving process resource efficiency and waste reduction

• Environmental compliance modelling supporting sustainable manufacturing operations

Module 14: Risk Analysis and Process Reliability

• Risk-based simulation supporting proactive engineering decision-making and safety management

• Reliability modelling improving process availability and operational continuity performance

• Failure scenario simulation supporting emergency preparedness and resilience planning

• Uncertainty analysis strengthening engineering confidence in optimization decisions

Module 15: Emerging Technologies and Industry Trends

• Autonomous process optimization using artificial intelligence and machine learning

• Hydrogen production and carbon capture process simulation methodologies explained

• Smart manufacturing integration supporting Industry 4.0 transformation initiatives

• Advanced predictive analytics improving future chemical plant operational excellence

Module 16: Practical Simulation Workshop and Industry Case Studies

• Comprehensive case studies demonstrating successful chemical process optimization projects

• Practical workshops constructing and validating integrated simulation models collaboratively

• Simulation exercises evaluating operational improvements and engineering alternatives effectively

• Best practices supporting world-class process simulation and plant optimization excellence

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.

Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment:

Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.