Discrete event simulation is a powerful technique used to model and analyze systems that involve discrete, sequential events. I have covered discrete-event simulation extensively in various SCDA blog posts. In this article I point out five classical examples of discrete-event simulation in a broad range of industries. I will furthermore point out concrete application examples and the financial benefits yielded by them.

Simulation applications for manufacturing systems

Discrete event simulation is commonly used in manufacturing to optimize production processes. It can model the flow of materials, the operation of machines, and the scheduling of tasks to improve efficiency, reduce bottlenecks, and minimize downtime.

Example: An automobile manufacturing plant uses discrete event simulation to optimize its production line. The simulation models the assembly process, including the movement of parts, the operation of robots and machines, and the scheduling of tasks. By adjusting parameters and experimenting with different scenarios in the simulation, the plant can identify ways to increase production efficiency, reduce assembly line downtime, and improve the overall manufacturing process.

Here are some financial benefits that a simulation study of manufacturing system design and operation can yield:

• Downtime reductions: Simulation can help identify and mitigate bottlenecks and inefficiencies in the production line, reducing downtime and increasing overall equipment effectiveness (OEE).
• Operational cost reduction: By optimizing resource allocation and scheduling, manufacturers can reduce labor and energy costs.
• Improved productivty of capital and labor deployed: Increased throughput and reduced production time can lead to higher production volumes and, consequently, higher revenue.

Transport system simulations

Simulation is used to model traffic flow, airport operations, and public transportation systems. It helps planners and engineers make informed decisions about infrastructure design, traffic management, and scheduling.

Example: A city’s transportation department employs discrete event simulation to evaluate traffic management strategies. The simulation models the flow of vehicles through major intersections and roadways. By altering traffic signal timings, lane configurations, or introducing new traffic management policies, the city can assess the impact on traffic congestion, travel times, and overall road network performance.

Here are some points that explain the financial interest behind ordering and conducting simulation studies for transport systems:

• Reduced traffic congestion: Simulation can lead to optimized traffic signal timings and lane configurations, reducing congestion. This can result in lower fuel consumption, less wear and tear on vehicles, and reduced air pollution.
• Improved public perception: Efficient transportation systems can enhance a city’s reputation, potentially attracting more businesses and residents.
• Cost savings: Efficient traffic management can lead to lower infrastructure maintenance costs and potentially reduce the need for expensive road expansion projects.

Discrete-event simulation in healthcare

Hospitals and healthcare facilities use discrete event simulation to optimize patient flow, staff scheduling, and resource allocation. This can lead to improved patient care, reduced waiting times, and better utilization of resources.

Example: A hospital uses discrete event simulation to optimize its emergency department (ED) operations. The simulation models patient arrivals, triage processes, treatment queues, and resource allocation. Hospital administrators can experiment with different staffing levels, patient flow protocols, and resource allocation strategies to reduce patient waiting times, enhance the quality of care, and allocate staff more efficiently during peak hours.

A simulation study in healthcare may very well yield some or several of the following exemplary financial benefits and gains:

• Enhanced patient care: Shorter wait times and efficient patient flow can lead to higher patient satisfaction and potentially attract more patients.
• Improved resource utilization: Better allocation of staff and resources can reduce labor costs while maintaining or improving the quality of care.
• Reduced overhead: By streamlining operations and reducing waste, hospitals can lower operating costs and improve their financial health.

Simulation applications in supply chain management

Discrete event simulation is employed to model supply chain processes, including inventory management, order fulfillment, and logistics. It allows organizations to analyze various scenarios and make informed decisions about inventory levels, distribution strategies, and order processing.

Example: A retail company employs discrete event simulation to optimize its distribution center operations. The simulation models the receiving of goods, order processing, inventory management, and shipping processes. By adjusting parameters like order fulfillment policies, inventory levels, and workforce schedules, the company can identify cost-effective strategies for minimizing inventory carrying costs while meeting customer demand.

A simulation study related to supply chain management may be conducted due to the following financial beneifts:

• Reduced inventory costs: Simulation can help optimize inventory levels and reduce carrying costs, leading to significant savings.
• Faster order fulfillment: Improved order processing and logistics can result in faster order delivery and higher customer satisfaction.
• Lower operating costs: Streamlined supply chain operations can reduce labor and transportation costs.

Telecommunications network simulations

Telecom companies use simulation to study the performance of network systems, such as call centers, data centers, and routing algorithms. It helps in optimizing network design, capacity planning, and fault tolerance.

Example: A telecommunications company uses discrete event simulation to assess the performance of its call center operations. The simulation models incoming call volumes, call routing algorithms, agent availability, and call handling times. By experimenting with different staffing levels, routing strategies, and call prioritization rules in the simulation, the company can improve customer service, reduce call wait times, and optimize staffing levels to handle fluctuating call volumes effectively.

Here are some of the financial benefits of simulation studies of telecommunications networks:

• Improved customer satisfaction: Faster call response times and better service can lead to increased customer loyalty and reduced churn.
• Optimal staffing levels: Simulation can help avoid overstaffing during periods of low call volumes, reducing labor costs, while ensuring sufficient staff during peak times.
• Enhanced service quality: Simulation can identify areas for network optimization, potentially reducing service disruptions and costly maintenance.

Concluding remarks on popular simulation applications

In this article I have pointed out popular industrial discrete-event simulation applications. Such examples can be found in e.g. telecommunications networks, supply chain management, healthcare, transport systems, and production planning and control. I have published many other exemplary applications and related articles in the past. Here are some of them – you might be interestd in giving them a read:

• Link: 53% ROI: Barge transport simulation study
• Link: Backlog simulation of FIFO production
• Link: AGV simulation of part routings in AnyLogic
• Link: Job shop SimPy Python simulation
• Link: Poultry meat supply chain simulation

Linnart Felkl

Data scientist focusing on simulation, optimization and modeling in R, SQL, VBA and Python