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Software de análise preditiva /
Software de simulação /
ProModel Optimization Suite Reveja
ProModel Optimization Suite
Avaliações: 5 | Classificação geral: BoaExcelente | |
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Accelerate Process Improvement While Eliminating Risk:
ProModel is a discrete-event simulation technology that is used to plan, design and improve new or existing manufacturing, logistics and other operational systems. It empowers you to accurately represent real-world processes, including their inherent variability and interdependencies, in order to conduct predictive analysis on potential changes. Optimize your system around your key performance indicators.
The graphics for this software are outdated compared to other products out there. The output viewer is not always reliable. It crashes when you have large amounts of data from multiple scenarios/replications. You do need to have some programming knowledge to fully utilize all the benefits the software has to offer.
I do not have any real concerns with ProModel.
Online tutorials (these are examples I use in class), animation, the addition of undo (!), new interface, training I attended last year in Utah, extensive graphics library, and the user support.
Can't think of much to say here - the lack of 'undo' and a familiar interface (yes, sorry, that means mimicking Windows...) were a challenge in years past. Not so now!
ProModel is a very flexible application with a wide range of functionality. One can develop a basic simulation of a simple process using easy o follow graphical interface. Also, one can develop a sophisticated simulation of a complex process or system using ProModel's built-in functionality enhanced by user-developed logic. In any case, ProModel is an incredibly valuable tool to analyze and understand process variability and complex interactions.
With ProModel's flexibility comes many ways of modeling a specific situation. The biggest challenge is being able to evaluate the options, and to choose the most effective and efficient one.
Fits very well with out operation of pickers picking in a warehouse. Lots of flexibility in outputs available.
Inability to track certain metrics within the model.