"As a COTS (Commercial-Off-The-Shelf) product, Simio fits perfectly to model the use of the armed forces logistics from Germany to Afghanistan. Simio allows detailed analysis and individual 'links' as well as an aggregated end-to-end analysis and optimization of complex supply chains of the Bundeswehr. Simio [adheres] particularly well to the supply chain approach." Mr. Hans-Georg Konert
Former Colonel and Managing Director
Konekta Consulting GmbH in Brühl, Cologne
Simulation is the answer to accounting for variability in supply chains and no software does it better than Simio.
Simio allows users to:
Simio gives you a view into your supply chain in a way made possible only with simulation.
With Simio is object-based simulation software with a unique mix of simplicity and flexibility that lets users quickly improve performance of dynamic systems and identify and avoid risk fast.
By combining the simplicity of customizable, shareable objects with the flexibility of processes, Simio can rapidly model almost any system without requiring programming.
By its very nature, optimization cannot account for variability and since it’s the analytical tool of choice for supply chain analysis, organizations that rely on it will have a limited view of their business.
In general, optimization and simulation can both lower costs. But only simulation can evaluate on-time delivery or the dynamic cost of quality. In some cases where enough data exists, simulation can predict the quality.
Systems where it is too expensive or risky to do live tests. Simulation provides an inexpensive, risk-free way to test changes ranging from a "simple" revision to an existing production line to emulation of a new control system or redesign of an entire supply chain.
Large or complex systems for which change is being considered. A "best guess" is usually a poor substitute for an objective analysis. Simulation can accurately predict their behavior under changed conditions and reduce the risk of making a poor decision.
Systems where predicting process variability is important. A spreadsheet analysis cannot capture the dynamic aspects of a system, aspects which can have a major impact on system performance. Simulation can help you understand how various components interact with each other and how they affect overall system performance.
Systems where you have incomplete data. Simulation cannot invent data where it does not exist, but simulation does well at determining sensitivity to unknowns. A high-level model can help you explore alternatives. A more detailed model can help you identify the most important missing data.
Systems where you need to communicate ideas. Development of a simulation helps participants better understand the system. Modern 3D animation and other tools promote communication and understanding across a wide audience.
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