2013 · 10 citations · 7 references
EngineeringMachine LearningEnergy EfficiencyIndustrial EngineeringEnergy PerformanceAutomated ManufacturingSystems EngineeringIndustrial InformaticsProduction TechnologyMachine AvailabilityComputer EngineeringManufacturing SystemsTotal Energy ConsumptionEnergy ManagementAutomationPredictive MaintenanceSelf-optimizationProduction EngineeringAi-based Process OptimizationTechnologySustainable Production
Due to the growing demand to reduce the environmental impact, the manufacturing companies of today are encouraged to adopt new green methodologies, strategies and technologies for increasing the energy efficiency of their manufacturing production lines. These solutions have a great impact on several productivity metrics including availability and costs. The continuous pursuit of productivity and particularly of machine availability has led to an increase of the total energy consumption in production plants. However, productivity gains can also be achieved by reducing the life-cycle costs of the manufacturing production systems. The research currently done under the scope of Self-Learning Production Systems (SLPS) tries to fill the gap between availability and efficiency by providing an innovative and integrated approach for ensuring the efficient utilization of the resources in machine tools.
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An Environmental Analysis of Machining
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Context extraction for self-learning production systems
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