What is discrete event simulation (DES) and how does it work?
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What is discrete event simulation and how does it work?
Discrete event simulation (DES) enables risk-free experimentation and right-first-time decision making. It facilitates stakeholder buy-in, supports increased ROI and avoids unnecessary capital expenditure – across industries from manufacturing to healthcare.
But what exactly is it? Why is it an effective tool for overcoming challenges? And where does it deliver the most value?
In this article, we answer the most frequently asked questions about this important technique for designing, analysing and optimising complex operational processes:
What is discrete event simulation?
Discrete event simulation (DES) is a method for modelling the operation of a system or process as a discrete sequence of events. By enabling you to experiment with the process quickly – and in a risk-free environment – it allows you to:
- Find out how strategic or resource changes will impact a system or process
- Increase efficiency
- Test ideas
DES was developed at the advent of computing as a strategy to help understand queuing theory and improve automative and steel manufacturing. Our company was a product of that era – and our approach and software has been in constant evolution since. However, the underlying principles of event, states and time progression are still there.
How does discrete event simulation work?
In DES, a system or process is modelled as a sequence of consecutive events – for example, a customer arriving in a queue or a machine breaking down. Each event marks a change of state.States can include being busy, blocked by the next step or waiting for a resource. The events might be the end of a batch cycle, a vessel arriving into port or the start of bad weather.
Between events, it’s assumed there’s no change in the system, so the simulation can jump to the time of the next event. This is called next-event time progression. With next-event time progression, we can have arbitrarily small gaps between events – and understand what might happen if 2 events happen just before or just after each other, given variability in processing times.
The classic DES model sees customers queueing at a post office. It focuses on decisions around how many servers are required and whether it’s more efficient to have one long queue or a queue per server. However, some DES models also incorporate continuous elements (like the rate at which a machine processes parts) within a discrete event framework (modelling the arrival of those parts). This makes the simulation richer and more complex.
What are the benefits of using discrete event simulation to overcome key business challenges?
From boosting ROI to enabling confident decision making, DES delivers a multitude of benefits, including:
- Risk-free experimentation – Testing new designs, processes and facilities in a risk-free digital environment enables you to visualise their impact before you allocate real-world budget
- Right-first-time decision making – By enabling experimentation with multiple ‘what-if’ scenarios, DES helps you make business-critical decisions with clarity and confidence
- Facilitate stakeholder buy-in – Switch between 2D, 3D and abstract visualisation to maximise impact and deepen understanding of scenarios you’re facing, thereby improving communication across your organisation
- Increase return on investment – Validate business cases for investment by providing evidence on what will deliver the greatest ROI
- Balance resource and performance – Strike the right balance between staffing, response times, operating costs and service levels to improve outcomes and meet targets
- Manage change effectively – By identifying bottlenecks and revealing unintended consequences, DES helps you introduce change to complex processes and supply chains with confidence
Why choose discrete event simulation over other options?
By capturing the randomness and interdependencies inherent in real-world processes and workflows, DES enables detailed system modelling. This lets you solve complex challenges across processes involved in areas like manufacturing, logistics and service delivery – in a realistic way.
Compare that to static spreadsheet-based analysis. Spreadsheets struggle to deal with elements such as:
- Complex decision logic
- Resources required in multiple processes
Prioritisation - Dynamic variables such as cycle times, breakdowns or weather
For processes that don't exist yet, spreadsheet-based analysis can provide a baseline against similar operations – but this always involves assumptions and guesswork about the new process. Without a dynamic model, it’s hard to test these assumptions or experiment with multiple scenarios.
Time-sliced approaches – differential equation models, for example – are useful when it comes to large datasets. However, they struggle in processes where individual elements are important. Understanding these elements in a discrete way requires DES.
When you focus on spreadsheet analysis and statistics, or even when you use forecasting and predictive algorithms, there are many assumptions that things will be the same in the future as they were in the past. Simulation helps you understand the impact of changes to the norm and dynamic knock-on consequences. Of course, it becomes even more complex when you factor AI and machine learning into the mix.
Which sectors and applications are most suited to discrete event simulation?
Whether you’re looking to design a new facility, optimise the layout of an existing one, reduce waste or energy usage or make staffing more efficient, DES can help. And its value is by no means limited to optimising widget processing on a manufacturing line. It delivers benefits across sectors as diverse as nuclear decommissioning, offshore wind, ports, chocolate production and electronics!
For example, we’ve used it to optimise queuing at Madame Tussauds and set tee-off times at a leading golf course. Find a full list of the sectors we work with here.
Here are a few examples of key use cases to give you a flavour:
- Automotive – The shift to EV is disrupting the industry, but DES enables manufacturers and suppliers to adapt to change quickly to meet consumer demand (read how one leading manufacturer used DES to shape its AGV strategy)
- Contact centres – Call centres use DES to balance resource and reduce wait times (read how one mobile brand used DES to implement a new customer service delivery model)
- Supply chain and logistics – Providing clarity in the face of fluctuating demand, rising energy costs and resource scarcity, DES enables evidence-based decision-making (discover how DES insights identified supply chain risks and highlighted opportunities for cost savings and performance improvements)
What data outputs do you get from discrete event simulation?
With a powerful DES software tool (like Twinn Witness predictive simulation software), you can extract and visualise data in many ways – from spreadsheets to visualisations and animations. This enables you to maximise impact for key stakeholders and deliver an in-depth understanding of various what-if scenarios.For example, you can plan and design your model in 2D before switching to 3D for an immersive visual experience. You could also view your model as an abstract process flow. Data can also be exported seamlessly back into Excel – typically in a text file – and placed wherever you need it, whether that’s a database, Power BI or Tableau.
Ultimately, there’s flexibility based on the functionality you need.
Why choose Twinn Witness for your DES software?
With Witness, you can experiment with multiple what-if scenarios, unlock in-depth business insights, and create immersive 3D simulations. Not only do we excel when it comes to importing and exporting data swiftly and seamlessly. With customisable designer elements, it’s easy to plan and design your model layout. And we can incorporate continuous elements – fluids, for example – as well as discrete processes.
We also offer a variety of options when it comes to working with us:
- We supply software with a licence so you can develop your own models – As part of this, we can also provide customisable simulation modelling training which incorporates mentoring to look at the model and help you make decisions about what to do with it.
- We deliver a DES solution to solve your challenges – With this approach, you don’t need to be a modeller or understand DES. Instead, we do the simulation modelling on your behalf, wrapping it in an interface that makes it easy to use.
- We provide a comprehensive consulting service – Looking at your process, we’ll build a model, experiment and report back to you. With this approach, there’s no transfer of a solution asset or software licence.
Do you have more questions about discrete event simulation?
Get in touch with our experts.
Twinn Witness Simulation Software
