人工智能在制造业中的应用：权衡能源消耗与效率提升.pdf

1、Jibran Zuberi,Haitam Laarabi,Sarah Smith,Arman ShehabiAI in Manufacturing:Weighing Energy Footprints Against Efficiency GainsAI in Manufacturing:Weighing Energy Footprints Against Efficiency GainsJibran Zuberi,Haitam Laarabi,Sarah Smith,Arman ShehabiOCP SPECIAL FOCUS:ARTIFICIAL INTELLIGENCE(AI)Manuf

2、acturing sector Accounts for approx.one-third of total U.S.primary energy demand(EIA U.S.Annual Energy Outlook 2025)Traditional smart manufacturing Relies on predefined rules,lean workflows,and simulation-or threshold-based systems.Advanced AI(such as deep learning)in manufacturing Learns from vast

3、amounts of data,adapts in real time,and detects nuances and anomalies beyond hardcoded rules.oRepresents a transformative step beyond conventional digitization and IT integration.Growth in AI concerns have grown over the substantial energy consumption and associated emissions of AI systems.Advanced

4、AI in Manufacturing3Projected AI-Added Revenue by Manufacturing VerticalABI Research(2024)4General AI Use Cases in Manufacturing MANUFACTURING APPLICATIONSOPERATIONSDESIGNPLANNINGREAL-TIMEPredictive MaintenanceQuality ControlSupply Chain and Resource ManagementProcess Optimization and ControlCollabo

5、rative RobotsGENERATIVE DESIGNTESTING/EXPERIMENTATIONCustom Manufacturing5AI Use Cases in Specific Manufacturing SectorsUse caseIndustrial sectorParameters optimized through AI technologiesService providersAI systemReported relative energy savings and other impactsAI-assisted process control,stabili

6、zation,&optimizationCementTemperature control,rates of alternative fuel substitution,kiln speed,feed rate,airflow,raw material proportions,fan speeds,etc.ABB,ThyssenKrupp,CarbonReImubitBasetwoLinear and Non-Linear Model Predictive Control,Fuzzy Logic,and ANN320%energy savings and 38%productivity gai