Automating Process Optimization with AI: The FlexSim Optimizer and Live Digital Workplaces

Process bottlenecks and related issues often require complex and dynamic solutions. Discover how FlexSim recommends process improvements from live data, and see how the FlexSim OptQuest optimization engine solves multidimensional problems. OptQuest uses machine learning to evaluate multiparameter input groups in order to strategically determine optimal outcomes across various performance objectives. This method provides faster and more intelligent solutions to intricate problems than manual techniques do. In scenarios with constantly evolving operational inputs, FlexSim can be configured as a live Digital Workplace, continuously operating at set intervals, and using live data streams based on system feedback and artificial intelligence (AI) predictions. This approach necessitates specific model programming, which we will explore. By implementing these advanced techniques, businesses can significantly improve their process optimization capabilities, addressing complex challenges more effectively than traditional methods allow.