
FlexSim Simulation Software Course
Master FlexSim simulation software and gain the technical skills to model, analyse, and optimise real operational systems. From building your first discrete-event model to running advanced scenario experiments, this course covers everything professionals need to deliver credible simulation results. Whether you work in manufacturing, logistics, or healthcare, FlexSim expertise sets you apart.
What you will learn:
You will learn to navigate the FlexSim environment and construct structured simulation models using queues, processors, operators, and transporters. The course covers statistical distributions, input data fitting, and replication-based output analysis so that your results are statistically sound. You will use the Scenario Manager to compare design alternatives and apply sensitivity analysis to identify high-impact variables. Advanced topics include FlexScript coding, global tables, failure modelling, and 3D visualization. You will also explore supply chain, healthcare, and digital twin applications, and finish by completing a full simulation project from scoping through stakeholder presentation.
How you study in a practical way FlexSim Simulation Software Course
How you practise FlexSim Simulation Software Course
For companies looking to train their teams
With Dedika for businesses, the course includes exercises and examples tailored to your own business and the way your company needs.
Course content
8 Chapters • 36 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsIntroduction to FlexSim and Simulation Concepts
Introduction to FlexSim and Simulation Concepts
Lesson 1 • Fundamentals of Discrete-Event Simulation
Covers simulation types, event-driven logic, and real-world modelling principles. Establishes conceptual grounding needed for all FlexSim work.
Lesson 2 • Building and Running a First Model
Guides students through creating a minimal working model from scratch. Reinforces interface skills and introduces the run-and-observe cycle.
Lesson 3 • Navigating the FlexSim Interface
Introduces the FlexSim workspace, toolbars, and panel layout. Students gain confidence moving through the environment before building models.
Lesson 4 • FlexSim Object Library Overview
Surveys the standard object library including queues, processors, and resources. Connects object types to their real-world operational counterparts.
Chapter 2HideHide detailsSee detailsModel Building Essentials
Model Building Essentials
Lesson 1 • Processors and Service Logic
Explains processor setup including service time distributions and output routing. Connects processing logic to real workstation behaviour.
Lesson 2 • Queues and Buffers
Covers queue capacity, discipline rules, and buffer placement strategies. Students learn how queuing behaviour affects throughput and wait times.
Lesson 3 • Connecting and Routing Objects
Demonstrates port connections, routing logic, and conditional branching. Accurate routing ensures entities follow intended process paths.
Lesson 4 • Model Validation Techniques
Introduces methods for verifying that model behaviour matches intended logic. Validation prevents compounding errors in later analysis stages.
Lesson 5 • Sources and Sinks Configuration
Teaches arrival generation logic and entity disposal setup. Proper source and sink configuration controls the flow of entities through any model.
Chapter 3HideHide detailsSee detailsResources and Task Executers
Resources and Task Executers
Lesson 1 • Task Sequences and Dispatching
Teaches how task sequences control resource behaviour step by step. Dispatching rules determine which resource responds to which request.
Lesson 2 • Transporters and Conveyors
Explains transporter configuration for material movement and conveyor belt setup. Students model automated and manual transport systems accurately.
Lesson 3 • Resource Pools and Shared Resources
Demonstrates pooling multiple resources for shared use across process stations. Shared resource modelling reflects realistic labour and equipment allocation.
Lesson 4 • Operators and Labour Resources
Covers operator object setup, travel behaviour, and task assignment. Operators represent human labour that constrains throughput in many real systems.
Chapter 4HideHide detailsSee detailsStatistical Distributions and Input Data
Statistical Distributions and Input Data
Lesson 1 • Random Streams and Seed Control
Covers random number streams, seed assignment, and replication independence. Proper seed control ensures reproducible and statistically valid experiments.
Lesson 2 • Using the Distribution Fitter
Demonstrates FlexSim's built-in distribution fitting tool with real data sets. Fitting observed data to distributions improves model credibility.
Lesson 3 • Understanding Variability in Systems
Explains why deterministic models fail to capture real system behaviour. Variability in arrivals and service times drives the need for statistical inputs.
Lesson 4 • Common Distributions in FlexSim
Surveys exponential, normal, triangular, and uniform distributions and their uses. Students select appropriate distributions based on data characteristics.
Chapter 5HideHide detailsSee detailsData Collection and Performance Analysis
Data Collection and Performance Analysis
Lesson 1 • Built-In FlexSim Statistics
Surveys automatically collected metrics including throughput, utilisation, and wait time. Understanding default statistics accelerates initial performance assessment.
Lesson 2 • Warm-Up Period and Steady-State Analysis
Addresses transient bias and methods for identifying the warm-up period. Steady-state analysis ensures output data reflects true system performance.
Lesson 3 • Replication and Confidence Intervals
Covers running multiple replications and computing confidence intervals for output. Replication-based analysis quantifies uncertainty in simulation results.
Lesson 4 • Dashboards and Charts
Teaches dashboard creation with time plots, bar charts, and pie charts. Visual dashboards communicate model behaviour to technical and non-technical audiences.
Lesson 5 • Custom Performance Indicators
Explains how to define and track custom KPIs using labels and global tables. Custom indicators capture metrics not available in default statistics.
Chapter 6HideHide detailsSee detailsExperimentation and Scenario Analysis
Experimentation and Scenario Analysis
Lesson 1 • Comparing Alternatives Statistically
Applies paired comparison and ranking methods to evaluate scenario outputs. Statistical comparison prevents selecting inferior alternatives due to random variation.
Lesson 2 • Design of Experiments Principles
Covers factorial design, factor levels, and response variables for simulation experiments. Structured experimental design maximises insight from limited simulation runs.
Lesson 3 • Scenario Manager Fundamentals
Introduces the FlexSim Scenario Manager for defining and running multiple scenarios. Scenario management enables systematic comparison of design alternatives.
Lesson 4 • Sensitivity Analysis
Teaches one-at-a-time and range-based sensitivity testing of model parameters. Sensitivity analysis identifies which inputs most influence system performance.
Chapter 7HideHide detailsSee detailsAdvanced Modelling Techniques
Advanced Modelling Techniques
Lesson 1 • Introduction to FlexScript
Introduces FlexScript syntax, data types, and basic control structures. FlexScript enables custom logic beyond what graphical configuration alone can achieve.
Lesson 2 • Global Tables and Data Management
Explains global table creation, population, and lookup within model logic. Global tables centralise data management and support complex decision rules.
Lesson 3 • Labels and Entity Attributes
Teaches label assignment, reading, and use in routing and processing decisions. Labels attach custom attributes to entities, enabling differentiated handling.
Lesson 4 • Triggers and Event-Driven Logic
Covers on-entry, on-exit, and on-reset triggers for injecting custom behaviour. Triggers allow models to respond dynamically to entity and time events.
Lesson 5 • Failure and Repair Modelling
Models equipment failures using time-to-failure and time-to-repair distributions. Failure modelling captures the impact of downtime on system throughput.
Chapter 8HideHide detailsSee detailsReal-World Project Application
Real-World Project Application
Lesson 1 • Results Presentation and Recommendations
Teaches how to structure findings, visualise results, and deliver actionable recommendations. Effective presentation translates simulation insights into organisational decisions.
Lesson 2 • Project Scoping and Data Collection
Guides students through defining project objectives, system boundaries, and data needs. Clear scoping prevents scope creep and focuses modelling effort effectively.
Lesson 3 • Model Validation with Stakeholders
Covers face validity, historical data comparison, and stakeholder review sessions. Validation builds confidence that the model represents the real system.
Lesson 4 • Conceptual Model Development
Teaches process mapping and conceptual model documentation before building in FlexSim. A documented conceptual model reduces rework during construction.
Lesson 5 • Full Model Construction and Verification
Students build the complete model, applying all prior techniques and verifying logic. Verification confirms the model behaves as designed before validation.
Your valid completion certificate
This course is for you:
Industrial engineers: seeking to validate process designs before implementation.
Operations managers: wanting data-driven evidence to justify capacity investments.
Supply chain analysts: ready to move beyond spreadsheets into dynamic system modeling.
Healthcare administrators: aiming to reduce patient wait times through flow analysis.
Graduate students: building simulation competency for research or industry careers.
Career changers: transitioning into operations research or process improvement roles.
What our students say
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