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英特尔&CIO:2024制造业边缘AI状况白皮书:迈向新范式(英文版)(12页).pdf

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1、S P O N S O R E D C O N T E N T|W H I T E P A P E RThe state of edge AI in manufacturing:moving to a new paradigm White paperSPONSORED BYFrom improving employee productivity and safety to reducing operational costs and spotting product defects,manufacturers see no shortage of use cases for edge AI.2

2、CIO|Intel|The state of edge AI in manufacturing:moving to a new paradigmTODAYS MANUFACTURERS face pressure from a convergence of forces,many are largely beyond their control.Skilled worker shortages and rising labor costs are driving them to improve productivity with fewer resources.Higher prices fo

3、r energy and materials constrain margins,and tariffs and geopolitical disruptions cause many to make major changes in their supply chains or restrict sales.A recent Foundry MarketPulse survey of 500 senior enterprise decision-makers including 170 in manufacturing found overwhelming agreement that ed

4、ge artificial intelligence(AI)technology has the potential to help overcome many of these challenges,and many manufacturers have successfully implemented solutions for specific use cases.But questions about the technologys complexity and cost are holding some back from broader deployments.To reap th

5、e full benefits of edge AI,the survey suggests,manufacturers need to gain a better understanding of the technology and develop an implementation strategy that fits their needs and budget.What manufacturers want from edge AI:saving money and growing revenueAmong the many challenges driving manufactur

6、ers to adopt AI solutions,an acute labor shortage tops the list.Millions of baby boomgeneration workers who have spent their lives in the industry are retiring,with fewer younger workers entering the field to take their place.Even with modern advances in robotics,many plants remain shorthanded.Secur

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本文主要讨论了制造业中边缘人工智能(AI)的应用现状和未来趋势。主要观点包括: 1. 制造业面临劳动力短缺、能源和材料价格上涨、贸易政策和地缘政治动荡等挑战,边缘AI技术有望帮助制造商克服这些难题。 2. 制造商对边缘AI的主要需求是降低成本和增加收入,包括提高员工生产力和安全性、减少运营成本、创造新产品和服务、提高客户体验等。 3. 边缘AI在制造业中的主要应用包括提高员工安全、改善安全监控、智能库存管理、预测性质量控制、实时设备监控、实时异常/产品缺陷检测和警报等。 4. 制造商对边缘AI的期望很高,认为它将显著提高自动化和效率,帮助他们创造革命性的新产品和服务,并提高收入。 5. 制造商在实施边缘AI时面临技术复杂性和成本问题,需要通过加入行业联盟、确保技能和资源、整体规划AI集成、与合作伙伴建立协调的AI生态系统等措施来克服这些挑战。
制造业如何利用边缘AI提高员工生产力和安全性? 边缘AI如何帮助制造商降低运营成本和发现产品缺陷? 制造商如何克服边缘AI实施的挑战,实现更广泛的应用?
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