Modeling and Optimization
Through modeling and optimization, we improve product design, system operation, and processes, facilitating more effective decision-making and intelligent automation in your organization. We address your business and industry challenges by developing models, simulations, and optimization solutions according to the desired outcomes and the constraints of your problems; evaluating current and possible scenarios, and outlining actionable insights. By productizing and maintaining our operational solutions for decision support, we strive for continuous value generation for your business.
Modeling and Simulation
Reasonance offers mathematical and statistical modeling of systems, processes, events, and outcomes. Given your use case, we build and validate a model that is fitting to your specific requirements and criteria. These models serve as the basis for running offline or online simulations that generate data and insights utilized to improve product design, operational performance, and decision-making. In the cases where the envisioned solution to your problem is rendered not feasible by unknown parameters, our team offers a toolbox of pure statistical and modern machine learning methods for parameter estimation. Some models might still be too complex for efficient evaluation, though. To tackle these challenges, our experts augment and simplify models to a degree that makes them computationally tractable while keeping the model accuracy within a specified range. The resulting simulation is delivered with a predefined data model, so it can be deployed and integrated withing your IT landscape to ensure usability, availability, and compatibility throughout your enterprise.
Extending the established modeling and simulation approach, a digital twin is a near real-time digital replica of a physical product, system, or process, that helps optimize business performance through improved design, manufacturing, and operation. By enhancing the digital twin with additional cognitive capabilities in the form of data analytics and machine learning applications, our team creates cognitive twins that learn and self improve when new data is presented. Furthermore, intelligent digital twins are able to analyze and act upon the captured operational data, supporting the decision-making process. Digital twins leverage data from sources such as sensors, ERP systems, CAD models, and additional metadata, therefore our team defines a canonical data model for your specific application. This allows the digital twin to be scaled horizontally across your organization, being able to cover a multitude of additional use cases. To fulfill the fault tolerance and resilience requirements for Industry 4.0 or Internet-of-Things applications, we build and deploy our digital twins in a modern containerized fashion, allowing for cloud-vendor-independent as well as on-premise deployment.
Mathematical optimization is a powerful, yet complex tool that allows companies to solve different challenges ranging from network planning through delivery scheduling and route planning, to product design and location planning. To fully leverage it, an organization typically needs experts with cross-discipline backgrounds including applied mathematics, operations research, computer science, and engineering. We at Reasonance bring this know-how for a single project or a series of projects, starting with mathematical problem formulation, going through simplification steps, if required, and finally software implementation. Our experts have experience with different techniques for combinatorial optimization, stochastic optimization, gradient-based optimization as well as different heuristic methods, making sure that we can approach a problem with the best tools. We understand that 95% of the optimization problems boil down to a standard problem from the literature, so we use our experience to identify this complex business problem and transform it into a set of smaller optimization problems, solvable with the least amount of effort. To tackle different levels of complexity, we also utilize novel and even bleeding-edge approaches such as optimization through simulation using digital twins or using a combination of digital twin and reinforcement learning. If you believe your organization can benefit from more efficient processes, better planning and resource allocation, and better tuned operations, get in touch with our team. We are here to model the tasks at hand and find the right solution for you.