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. In the intricate world of business operations, the transformative power of a well-executed simulation model is undeniable. At MISIM, we not only recognize this power but also the profound responsibility that comes with it. Our ethos revolves around aligning each model precisely with your business needs, understanding that 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.

Multifaceted Approach

Unit Testing. Unit testing is the first line of defence in the quality assurance journey. By running tests on isolated units of code, we confirm each segment functions as intended, independently. This ‘sandboxed’ testing ensures that each part of the code is thoroughly vetted before integration with larger systems, much like testing the integrity of bricks before laying a foundation.

Integration Testing for a Cohesive System. Once units pass muster, we move to integration testing, where different code segments are assembled to ensure they work together seamlessly . This stage identifies issues that may not be evident in unit testing, such as data flow problems or interface glitches, ensuring that the sum is as solid as its parts.

Model Validation to Ensure Performance Reality. Validating a model’s performance is crucial. Our approach involves creating static ‘shadow’ models—simplified versions of the system without variability—and comparing their outcomes to the dynamic model. By isolating and removing randomness, we can verify the model performs as expected under controlled conditions, thus affirming its predictive power.

Calibration and Tuning for Accuracy. Calibration is about adjusting model parameters to mirror real-world performance outcomes and benchmarks. It’s a delicate tuning process that ensures the model doesn’t just work in theory but reflects the practical, often messy realities it’s designed to replicate.

Explainability and the Backbone of Trust. We stress-test models and conduct deep dives into outcomes to ensure there’s a logical explanation for every result. This level of explainability is not just about ensuring accuracy; it’s about building trust with stakeholders who rely on the model’s predictions to make critical decisions.

Continuous Monitoring Beyond Deployment. Our commitment to quality extends beyond deployment. We continuously monitor model performance during sensitivity analyses, optimization, and deep dive explorations to ensure consistency and explainability. This ongoing vigilance allows us to catch and correct drifts in model performance, ensuring our simulations remain accurate over time.

Cultivating a Mindset of Quality

At MISIM, we encourage revisiting code and constructs frequently, not because we doubt our work, but because we believe in its continuous improvement. Quality assurance for us is not a department or a checklist; it’s a mindset adopted by every team member, fostering a culture where excellence is the norm.

Conclusion: Assurance at Every Step

Through rigorous unit testing, careful integration, methodical validation, precise calibration, the pursuit of explainability, and continuous monitoring, we assure the quality of our simulations at every step. It’s a comprehensive approach that underscores our commitment to delivering simulations that stakeholders can depend on, simulations that not only predict but also illuminate the path forward. This commitment to quality isn’t just about maintaining standards; it’s about elevating them, ensuring that our work today stands the test of time and the scrutiny of tomorrow.

Visit our Best Practices blog series to learn more.


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