Exploring Discrete Event Simulation with Purak Patel

In this Q&A, Purak discusses DES and its applications, covering key concepts such as:

• The benefits of DES
• How it’s used in various real-world applications
• Steps in implementing DES
• Best practices for building reliable DES models
• Common pitfalls in implementing DES
• Advanced techniques and emerging trends

Can you provide an overview of discrete event simulation and its applications?

A: Discrete Event Simulation (DES) is a methodology wherein a simulation model of a given work process is developed by factoring in both internal and external elements of a physical system, along with its constraints, to replicate its behaviour and performance over time.  Inputs can include everything from resource availability (e.g., the number of machines on the factory floor) to data about weather patterns, employee leaves, and macroeconomic headwinds that could disrupt workflow—just to name a few.

The strength of DES lies in its focus on system events that occur at discrete time intervals based on changes in system states. Advances in computational power have enhanced this method, enabling the virtual simulation of increasingly large and complex systems over years or decades in a fraction of the time.

Q: How does Actalent utilize discrete event simulation methodology to address the challenges faced by those in the manufacturing, processing, inventory, warehouse, logistics, and supply chain industries?

A: These industries are under mounting pressure to enhance efficiency, productivity, and profitability due to heightened competition, the advent of new technologies, changing demand and supply timelines, and the shift to low-cost and/or efficient material movement, among other factors.

At Actalent, we specialize in discrete event simulation and other methodologies, including robotics, ergonomics, agent-based, and system dynamics simulation, for manufacturing and industrial systems. Our passionate team dives deep into system assessments, addressing industry challenges while architecting and implementing innovative, technology-driven solutions.

Q: Can you provide examples of real-world applications where discrete event simulation has been successfully employed?

A: DES analysis can be applied to any process involving resource utilization. It is used in both greenfield and brownfield projects across various industries, including manufacturing, processing, inventory, warehousing, logistics, supply chain, healthcare services, and defense.

For example, if you're planning to build an electric vehicle battery factory, you need to assess required capacity and plan resources accordingly. Another application is evaluating the impact of introducing new products or variants within existing production and storage facilities—for instance, DES can help simulate the effect of, say, adding a new machine into the mix, or removing three workers from the floor.

DES can drive real results. One automotive OEM we worked with was struggling to combat traffic congestion in their manufacturing process, which was impacting the plant's throughput and increasing accident rates. In three months, our team developed a material flow DES model to identify peak traffic areas and develop an alternate layout. These efforts increased safety on the factory floor, eliminated delays caused by congestion, and reduced material handling manpower by 30%.

Q: Can you elaborate on the steps involved in implementing a discrete event simulation solution for a client? How do you ensure a smooth transition and integration into their existing operations?

A: First, a virtual replica of the system (i.e., a simulation model) is developed to visualize behaviour and performance of the system over time. Next, that simulation model is validated and verified for accuracy (e.g., does the replica show the same output during a certain time period as the system it’s replicating?). Then, “what-if” scenario analyses, experimentation, and further optimization of the model are performed.

Actalent deploys steadfast project management and subject matter experts to coordinate and implement this process. We also iterate the model over time, developing deployment procedures and adopting select technologies based on initial findings. This can range from simple process changes to semi-automation solutions to the integration of new special-purpose mechanisms.

Importantly, these solutions are always oriented around their impact on the company’s overall business strategy.

Q: Can you share any tips or best practices for building reliable and accurate discrete event simulation models?

A: There is no one-size-fits-all recipe for building reliable and accurate DES models, since they vary greatly depending on each individual business and industry sector.

With that said, it’s critical to understand the objective of the simulation at the outset of any DES project (e.g., inventory reduction, resource optimization, space reduction, etc.), as well as the level of abstraction and its effect on the overall system. Ask clear, scientific questions regarding what needs to be done with DES and why.

Understanding these objectives can help set parameters for DES that drive efficiencies. Otherwise, models may be developed in great detail without yielding tangible results.

Q: What are common pitfalls in discrete event simulation models and how can practitioners avoid them?

A: Important pitfalls include:

1. Distractions (i.e., missing and/or incorrect data inputs)
2. Implementation challenges (e.g., labor or cost issues hindering the implementation of a certain improvement)
3. Interpretation issues (e.g., miscommunications between those offering a solution via DES and those implementing it)
4. Acceptance problems (e.g., employees struggling to accept that a change needs to be made)

To avoid these roadblocks, it’s crucial to, again, clearly articulate the problem at hand; seek opportunities to simplify the model; critically analyze simulation behaviours; and dispel the notion of simulation as a black box. Fortunately, various tools are available to help practitioners apply these principles and sidestep common pitfalls.

Q: What are some advanced techniques or methodologies used in discrete event simulation? Are there any recent advancements or trends in the field?

A: DES tools have added many features for auto analysis and report generation, helping engineers make decisions and conduct multiple experiments quickly and seamlessly.

Another emerging trend is “digital twin” technology, which allows engineers to make real-time changes to a physical system via its integrated digital replica, thereby improving the entire design and installation process.