MN5617: System Modelling and Simulation Assessment

Learning Outcomes

By completing this assignment, students will be able to:

1. Critically evaluate and implement principles of systems approach and analysis.

2. Describe, critically evaluate, and appropriately apply manufacturing concepts to real-world industrial systems in order to design, plan, and solve problems arising in day-to-day management.

3. Develop skills for modelling, simulating, and critically analysing performance of deterministic and stochastic systems.

4. Acquire the ability to recognise the elements and rules governing supply chains/logistics and reverse logistics for better management and engineering of these systems.

5. Apply key tools and techniques for planning and critically evaluating the design of enterprise systems.

6. Model interactions and negotiations between components of enterprise systems.

7. Demonstrate integrated modelling of key processes within manufacturing systems.

8. Use simulation and optimisation techniques to identify improvements for enterprise integration.

9. Prepare written reports in a professional and structured manner.

10. Critically evaluate a range of complex scenarios and make informed decisions.

11. Exercise a high level of initiative and personal responsibility.

Assignment Theme

Each year, the assignment for the Systems Modelling and Simulation module explores a new theme.

• Previous Themes : Healthcare, banking services, manufacturing, and logistics.

• This Year’s Theme : Airport Operations Management

This variety demonstrates how the core principles of the subject can be applied to different fields with similar performance indicators.

Assignment Scenario

Aircraft Arrivals

• Arrivals follow an Exponential distribution with mean (λ) = 15 minutes.

• Upon arrival, planes wait for clearance from the control tower.

• Landing runway must be available and clear; otherwise, planes circle until permitted to land.

Runways

• Two runways in operation :

  • One dedicated to landings.

  • One dedicated to take-offs.

• Landing and clearing process: Triangular distribution TRIA(15, 15, 20) minutes .

Taxi and Unloading Times

• Taxi time (runway → terminal gates): Exponential distribution, λ = 10 minutes .

• Passenger and luggage unloading delay: Exponential distribution, λ = 15 minutes .

Terminal Distribution and Capacity

• From total arrivals:

  • Terminal 1 : 30%

  • Terminal 2 : 20%

  • Terminal 3 : 25%

  • Terminal 4 : 25%

• Each terminal capacity: 5 identical gates .

Departures

• Departures follow an Exponential distribution, λ = 17 minutes .

• Departure ratios same as arrivals (T1: 30%, T2: 20%, T3: 25%, T4: 25%).

• Loading time for departures: Exponential distribution, λ = 10 minutes .

• Taxi to runway: Exponential distribution, λ = 10 minutes .

• Departure process (runway allocation, preparation, take-off): Triangular distribution TRIA(5, 10, 15) minutes .

Runway Maintenance

• Inspections every 5.5 hours .

• Both runways closed during inspections.

• Inspection duration: Normal distribution (μ = 10 minutes, σ = 3 minutes) .

• Maintenance aligns with operational safety requirements.

Simplifications

• Passenger check-ins and similar processes ignored (due to Arena software limitations).

Assignment Tasks – Part A

1. Simulation Model

   • Develop a simulation model (with animations) of the airport operation system focusing on runway use.

   • Simulate for 24 hours and replicate 10 times (without initiating system).

2. Runway Utilisation

   • Calculate the percentage of time runways are idle or busy .

3. Daily Utilisation

   • Analyse utilisation of each runway and each terminal .

4. WIP Plots

   • Display Work-in-Progress (WIP) for:

     • Arriving planes

     • Departing planes

     • Total WIP

   • Plot over 24 hours (for each simulation run).

   • Do not initialise statistics between runs.

5. Noise Pollution Analysis

   • Sound exposure per aircraft: Triangular distribution (50, 60, 100 dB) .

   • Plot number of aircraft above 85 dB threshold over 24 hours.

6. Emergency Landings

   • Model 5% of departing aircraft requiring emergency landing (priority in queue).

   • Record total number of such aircraft.

7. Report Writing

   • Document the modelling approach.

   • Explain modelling of control tower clearance and other processes.

8. Simulation Results Discussion

   • Discuss results with respect to:

     • Runway & terminal utilisation

     • WIP

     • Noise pollution

     • Waiting times & queues (air and ground)

   • Include validation & verification for confidence levels.

9. Improvement Suggestions

   • Propose system improvements for:

     • Runway & terminal utilisation

     • WIP reduction

     • Noise reduction

     • Queue/waiting time optimisation

   • Simulate and compare results.

10. Increased Traffic Scenario

    • Airport management aims to double aircraft arrivals & departures .

    • Suggest operational strategies to handle traffic while minimising emissions.

    • Create simulation models, compare, and discuss results.

Assignment Tasks – Part B: Feasibility Study for a Third Runway

1. Runway Proposal Simulation

• Simulate integration of a third dual-purpose runway .

• Evaluate impact on:

  • Runway utilisation

  • Queue times

  • Overall efficiency

2. Cost and Feasibility Analysis

Conduct financial analysis using arbitrary figures:

• Construction costs & long-term maintenance .

• Environmental assessments (noise, emissions, sustainability).

• Cost management strategies to minimise financial & environmental impacts.

3. Research Component

• Investigate similar airport expansion projects.

• Focus on balancing cost, sustainability, and operational efficiency .

4. Report Requirements

• Financial plan with accurate cost projections & ROI estimates .

• Environmental impact assessment & mitigation strategies.

• Recommendations based on simulation results & research insights.

Run Conditions

• Warm-up period : 1 hour

• Replication length : 24 hours

• Number of replications : 10

• System initialisation : Required between replications

• Statistics initialisation : Not required

Hint :

• Create arrivals and departures separately.

• Dispose arriving aircraft after unloading.

• Dispose departing aircraft after take-off.

Submission Requirements

• Submit:

  • Report

  • Arena models (*.doe)

  • Output file (*.out)

• Attach printout of Arena’s final Summary Report as appendix.

Important Notes :

• Follow University submission guidelines.

• Files must be in correct format; PDF for report (not scanned).

• Zipping allowed only if permitted by University system.

• Missing required files = Fail .

Administrative Details

• Submission deadline : 11:59 am (UK Time), Thursday, 28th August 2025

• Submission method : Via WISEflow platform

• Late submission : As per University policy

• Marking criteria : Attached (Annex I)

• Provisional grade release : 25th September 2025

Assessment and Marking

• Marks allocated for:

  • Intuitive modelling approach

  • Simulation design and animation

  • Presentation and interpretation of results

  • Suggestions for system improvement with validation and verification

• Ensure compliance with academic integrity policies.

Assessment Approach

The academic mentor guided the student through the assessment using a structured, step-by-step approach.

Step 1: Understanding the Learning Outcomes & Assignment Scenario

The mentor began by clarifying the core learning outcomes, emphasizing the practical application of systems analysis, simulation, and enterprise systems management. We then broke down the assignment scenario, carefully interpreting each distribution and parameter, such as the Exponential distribution for arrivals and departures, and the Triangular distribution for landing/take-off times. This foundational step ensured the student fully grasped the complexities of the system before attempting to model it.

Step 2: Simulation Model Development (Part A)

The mentor and student collaboratively developed the Arena simulation model.

• Process Flow Mapping: First, we sketched out the process flow, separating arrivals from departures. This visual representation helped translate the scenario's text into a logical sequence of events.

• Arrivals Process: We created a CREATE module for arriving aircraft, followed by a SEIZE module to simulate the control tower allocating the landing runway. After the runway was released, the aircraft proceeded through DELAY modules representing taxi and unloading times.

• Departures Process: Similarly, a CREATE module was used for departures, followed by SEIZE and DELAY modules for loading, taxiing, and the take-off runway process.

• Maintenance & WIP: We modeled runway maintenance as a separate, time-based event that seizes both runways. We also set up Work-in-Progress (WIP) plots by defining QUEUE modules to track the number of aircraft waiting in the air (for landing clearance) and on the ground (for take-off).

• Special Conditions: We addressed specific requirements like the noise pollution analysis by adding a DECIDE module to check if an aircraft's noise level exceeded the 85 dB threshold. We also modeled the 5% emergency landings using a DECIDE module to divert a small percentage of departing aircraft back into the arrival queue with higher priority.

Step 3: Simulation Execution & Data Analysis

Once the model was built, we focused on running the simulation and interpreting the results.

• Run Conditions: The mentor ensured the student correctly configured the simulation run conditions: a 1-hour warm-up period, 24-hour replication length, and 10 replications. We paid special attention to the instruction to not initialize statistics between replications to get continuous data for the WIP plots.

• Result Interpretation: We analyzed the raw output to calculate runway and terminal utilization, which provided key insights into system bottlenecks. The WIP plots were used to visualize queue build-up and congestion over the 24-hour period.

Achieving the Final Outcome

The final outcome was a comprehensive submission that addressed all parts of the assessment criteria.

• The Report: The student drafted a professional report, a crucial learning outcome in itself. It started with a description of the modelling approach, detailing how the various distributions and processes were represented in Arena. We then presented and critically discussed the simulation results, using the utilization percentages and WIP plots to support our findings.

• Improvement Suggestions: Building on the analysis, we proposed practical improvement suggestions, such as optimizing gate allocation or introducing a third runway. This required running additional simulations to compare the "before" and "after" scenarios and validate the proposed changes, directly fulfilling a key learning objective.

• Feasibility Study (Part B): The student conducted the feasibility study for a third runway, using the new simulation results to evaluate its impact on efficiency. This part also involved a research component into real-world airport expansion projects and a financial analysis with arbitrary cost figures, demonstrating the student's ability to integrate technical simulation with broader business and environmental considerations. This section directly met the learning outcomes related to critical evaluation and informed decision-making.

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