Smart Operations seamlessly connects the enterprise with the factory floor, automating end-to-end processes from inventory to manufacturing, maintenance, and quality.
Discover how AI in Oracle Fusion Supply Chain Execution can help optimize operations and facilitate the disruption-free factory.
Oracle Fusion Cloud Advanced Inventory extends the capabilities of Oracle Inventory Management to support mid-tier, low-complexity warehousing operations
Streamline your global, mixed-mode manufacturing to make anything, anywhere, with an intelligent, optimized, and integrated solution powered by IoT and AI.
Transform your maintenance processes with an integrated and intelligent enterprise asset management system that’s written for the cloud and designed for the Internet of Things environment. Use Industry 4.0 capabilities and predictive analytics to predict asset failure, estimate reliable lifespan, and trigger prescriptive workflows to take preemptive action.
Gain full visibility into and control of the flow of goods across your company and global supply networks to improve customer satisfaction, decrease costs, and optimize service levels and working capital investment.
Drive closed-loop quality processes through design, procurement, inventory, manufacturing, and field service to ensure rapid detection and resolution of quality events. Make faster, more informed decisions and reduce risk with a predictive and connected 360-degree view of product quality across product lifecycle and supply chain processes.
Oracle이 Gartner Magic Quadrant, Warehouse Management Systems 부문에서 9년 연속 리더로 선정된 이유를 확인해 보세요.*
Oracle은 실행 능력 및 비전의 완성도 부문에서 가장 높은 점수를 획득하며 통산 17번째로** 리더로 선정되었습니다. 그 이유를 확인해 보세요.
Use powerful solutions for collecting operational data in real time, gleaning insights from the data, communicating rapidly, and making holistic and collaborative decisions.
Monitor factory efficiency to detect any unusual production behavior using predictive analytics on multiple sources of data. Provide a machine-monitoring platform to detect and predict unusual equipment behaviors and recommend the next best action to fix anticipated failures.
Leverage machine learning to identify hidden root causes for quality, yield, and other operational issues. Use deeper insights with your experts to make faster decisions and eliminate bottlenecks in production.
Use quality monitoring all along the production cycle to detect quality deviations and generate predictive alerts. Run an immediate root cause analysis to identify the sources of a quality issue. Set up best practices training using real data from past quality issues.
Learn about the revolution that's changing manufacturing.
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* Gartner, Inc., “Magic Quadrant for Warehouse Management Systems”, Simon Tunstall, Dwight Klappich, Rishabh Narang, Federica Stufano, 2024년 5월 2일.
** Gartner, “Magic Quadrant for Transportation Management Systems”, Brock Johns, et al. 2024년 3월 27일.
본 그래픽은 Gartner, Inc.가 발행한 연구 문서의 일부로서, 해당 문서의 전체적 맥락에 따라 평가해야 합니다. Oracle은 요청이 있을 시 해당 Gartner 문서를 제공합니다. Gartner는 연구 간행물에 언급된 공급업체, 제품 또는 서비스를 보증하지 않으며 기술 사용자에게 최고 등급 또는 기타 지정을 받은 공급업체만 선택하도록 권장하지 않습니다. Gartner 연구 간행물은 Gartner 연구 조직의 의견으로 구성되며 사실에 대한 진술로 해석되어서는 안 됩니다. Gartner는 상품성 또는 특정 목적에 대한 적합성 보증을 포함하여 이 연구와 관련된 모든 명시적 또는 묵시적 보증을 부인합니다. GARTNER는 등록된 서비스 상표이며, MAGIC QUADRANT는 Gartner, Inc. 및/또는 미국 및 전 세계 내 계열사의 등록된 상표입니다. 본 페이지에서는 허가를 받아 사용하였습니다. 무단 복제 및 사용을 금합니다.
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