How can simulation improve business performance?

• Is the terminal commercially viable?
• What’s the best design for berths and storage tanks?
• Will it operate safely under real-world conditions?

What we did

We created a detailed simulation that showed how the terminal would run, from ships arriving at the jetties to products being stored and dispatched. The model included:

• Ship movements: Arrival patterns based on shipping schedules and seasonal demand
• Berth operations: How three proposed jetties would handle different vessel sizes
• Tank storage: Product segregation and turnover rates
• Loading racks: Road tanker and rail car dispatch
• Connections: Pipelines linking to refineries and distribution networks

We also fed real-world data like historical vessel traffic, demand forecasts, equipment specs and even weather patterns that affect port operations.

Scenarios we tested

1. Base case: Two berths, existing storage
2. Reduced investment: Two berths, expanded storage
3. Future-proofed: Three berths, expanded storage

Each option was tested under different conditions — demand growth, vessel size mix, peak seasons, equipment downtime and environmental restrictions.

What we learned

• Capacity limits: The base design would hit full capacity in five years under medium growth — much sooner than expected.
• Hidden bottlenecks: Storage tanks, not berths, were the real choke point. Adjusting tank allocation reduced vessel delays.
• Safety risks: Emergency shutdown drills showed the original departure protocol could cause congestion during storms. A revised plan cut collision risk significantly.
• Financial wins: Optimising the design saved money by removing an unnecessary berth, improved utilisation and avoided costly expansions later.

The outcome

The port authority approved the project using the simulation-optimised design. The model didn’t stop there. It became a living tool for:

• Testing equipment changes in real time

• Validating contractor proposals

• Training future operators

Developing operating procedures before the terminal opens

Using a virtual model to test real-world conditions helped the port authority make informed decisions before spending millions. The study helped the team choose a design that works efficiently, stays safe during extreme weather and delivers strong financial returns — all without costly surprises later.

A state transport authority faced a big challenge with its freight rail network getting congested. More trains meant more delays at key junctions, schedule conflicts and inefficient use of passing loops. The authority needed a way to see the whole network clearly and test options before spending millions on upgrades.

What was the goal?

• Build a digital platform that could:
• Model the entire rail network
• Test different train schedules
• Identify bottlenecks
• Show how changes, like new infrastructure or policy tweaks, would affect performance

How we did it

• We created a virtual version of the rail network — a simulation that mirrored real operations. This model included:
• Tracks and junctions: Every passing loop, major junction and terminal
• Train details: Real movement data, train lengths, weights and loading patterns
• Operating rules: Priority systems for different freight types, seasonal surges and safety protocols
• Environmental factors: Flood-prone areas and heat-related speed restrictions

We also integrated real-world data like historical train schedules, maintenance windows and weather patterns.

What we tested

The platform allowed the authority to explore “what if” scenarios, such as:

• Infrastructure upgrades: Adding or extending passing loops, building a bypass or electrifying a corridor

• Operational changes: Adjusting priority rules, running fewer longer trains or moving to 24/7 operations
• Future demand: How the network would cope with five percent, ten percent or 15 percent freight growth over the next decade

What we learned

• Bottlenecks: Delays weren’t everywhere — they came from a few critical spots. For example:
  • A junction where coal trains crossed container services caused major delays.
  • A passing loop was too short for standard grain trains, forcing them to wait.
  • Yard capacity, not track space, was limiting throughput — fixing processes solved this without big spending.

• Smarter scheduling: By testing different timetables, the simulation found a schedule that:
  • Increased network capacity without new tracks
  • Cut transit times
  • Reduced fuel use

• Investment decisions: A costly urban bypass looked essential — until the simulation showed targeted upgrades and smarter operations could deliver similar benefits at a fraction of the cost.

The platform transformed how the transport authority makes decisions. Instead of relying on guesswork, they could see the entire network in action virtually and understand the impact of every choice before committing resources. This meant upgrades were prioritised for maximum benefit, schedules were optimised to improve on-time performance, and unnecessary spending was avoided. It also provided the evidence needed to meet strict safety regulations with confidence.

The simulation became part of everyday operations — a living tool used in weekly planning meetings, quarterly performance reviews and annual strategy sessions. It now underpins every major investment decision and even sets the stage for a future digital twin , enabling real-time monitoring and predictive maintenance. In short, the platform turned uncertainty into clarity and planning into precision.