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2058 - US Navy VesselsAI-Infused Food Supply vs. Demand Model.pdf

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1、US Navy Advanced Analytics Presented byAndrea Ludwig Account DirectorSteve Waterbury Solution ArchitectI B M Te c h X c h a n g e 2 0 2 4 L a s V e g a sOur Global ReachIBM Platinum Business Partner with Over 20 Years of Experience in Data&AI solutions.Over 300 Employees Across Europe,Asia,Africa,Au

2、stralia,and North America.Comprehensive Suite of Services:Consulting,Software Engineering,and Education.Cubewises purpose is to share our know-how and deliver pioneering,innovative,enduring planning,analysis,and reporting solutions,equipping our customers with the skills to transform how they naviga

3、te and harness the complexity of their business to their competitive advantage.CL1P Class 1 Common Operating PictureWe operate in a very dynamic environment,and our logistics must pace,and in many cases,precede and propel,our operations.”US Fleet Forces Director of Fleet Ordnance and Supply,Rear Adm

4、iral Matt OttProvide visibility of food on-hand in theater to support the Navy menu based on the current headcount in any given area of responsibility.AI infused analytics with the ability for What if scenarios based on changing environment.This provides the ability for leadership to quickly make de

5、cisions based on operational need.InventoryDemandEnduranceVessel Operational RequirementsClass based restrictionsGalley SpaceSupplier-VesselStorage typesNavy menuSailor PreferencesHolidaysTemperatureBehaviorWaste/SpoilageSubstitutionsOperational EffectivenessSupply chain ResiliencyMoraleSupplier Con

6、tract AdherenceNote:The variance from the menu card is referred to as“Acceptability”US Navy Setting the TableDecision OptimizationMachine LearningGenerative AIxP&AOptimizing InventoryMinimizing Contested MilesLearn the CrewPredict demand“Pe

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本文介绍了IBM Tech Exchange 2024上,Andrea Ludwig和Steve Waterbury关于美国海军先进分析的演讲。Cubewise作为IBM的金牌商业伙伴,拥有超过20年的数据和AI解决方案经验,全球有300多名员工。他们致力于分享专业知识,提供创新、持久的规划、分析和报告解决方案,帮助客户应对业务复杂性,获得竞争优势。其中CL1P是一套用于动态环境中快速做出决策的工具。海军需要优化库存管理,预测需求,减少浪费,并考虑船员偏好和节假日等因素。通过决策优化、机器学习和生成式AI,他们帮助海军提高了预测准确性至86%,并减少了34%的争议里程。最后,他们鼓励与会者继续探讨数据和AI等领域,以进一步创新。
有何亮点?" "Cubewise如何帮助海军优化库存管理?" "AI在海军决策优化中扮演什么角色?"
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