Blog
Beyond the Numbers
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Leveraging the Simulation-Based Digital Twin
“CEOs and senior executives have long dreamed of trialing their strategic decision-making prior to its execution. Till now the methods haven’t been very reliable. This has changed with the application of gen AI and advances in digital twin technology.”
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Quality as Culture: Cultivating Excellence in Every Step
Quality assurance in discrete event simulation (DES) is not a one-time event; it’s a continual process, a culture deeply ingrained in our best practice series. After all, a misaligned tool can be more detrimental than no tool at all. In this post, we’ll explore the multifaceted approach MISIM takes to ensure our models are robust, reliable, and ready for the rigors they’re designed to simulate.
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How Simulation Modeling Supports Capacity Planning Decisions
Capacity planning determines whether an operation can meet future demand without wasting capital on unnecessary infrastructure. Get it wrong, and the consequences show up quickly: overbuilt facilities that sit underutilized, bottlenecks that choke throughput during peak periods, or fleets and equipment sized for a demand curve that never materialized.
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Process Optimization Using Simulation: A Practical Guide
Operations leaders are under constant pressure to improve throughput, reduce costs, and get more value out of existing assets. Process optimization is how they do it, but the methods used to get there vary widely in accuracy and risk.
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How Simulation Modeling Improves Supply Chain Optimization
Supply chain optimization has become one of the most pressing priorities for operations leaders across mining, logistics, manufacturing, and distribution.
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Strategic Planning Under Uncertainty: How Simulation Improves Business Decisions
Strategic planning has always required leaders to make big commitments with incomplete information. What has changed is the degree of uncertainty involved.
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Digital Twin vs Simulation: What’s the Difference?
Executives evaluating a major capital project often hear both terms in the same conversation, sometimes from the same vendor in the same breath. Digital twin vs simulation is a question that determines how much a project will cost, how long it will take, and whether the resulting model will still be useful two years from…
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Transforming the Mine Value Chain: Exploring the Modelling Frontier
In the mining industry, the pursuit of value optimization is a persistent and significant challenge. The strategic application of integrated simulation modelling across the entire value chain stands as a promising, yet largely underexploited, approach. Until now, its ability to drive substantial economic benefits has remained mostly unrealized.
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Why Simulate? Unlocking the Potential of Discrete Event Simulation
In any competitive business landscape, staying ahead of the curve is more than an advantage—it’s a critical necessity. When effectively implemented, DES can yield returns that exceed 100x, standing as a powerful tool in unlocking value and driving transformative business outcomes.
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Unseen Forces: The Critical Role of Shadow Models in Simulation
At MISIM, we consider shadow models an integral component of any well-designed simulation. Their primary advantage? They inject a level of thoroughness into the validation process that is indispensable. Shadow models provide an essential quality assurance check that cannot be understated, ensuring that the underlying simulation model is both accurate and well understood.
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Enhancing Simulation Efficiency: The Power of Decoupling Data From Code
In the world of discrete event simulation (DES), the management of input and output data stands as a critical governance function. Our best practice series highlights the segregation of input and output data from model code as a critical workflow enhancement.
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Warm-Up for Peak Performance: Optimally Achieving Steady-State in Discrete Event Simulation
The concept of a warm-up period is just as critical in the realm of discrete event simulation as it is in in your exercise routine. Let’s dive into why it is integral to the accuracy of simulation models and how it can be used to reduce compute requirements.
