Adriano Engineering CBM
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Adriano Engineering provides an innovative real-time condition monitoring and predictive maintenance system using artificial intelligence. The system collects data from equipment in real-time, uses machine learning to detect failures and classify faults, and generates online reports. It is developed using a sprint methodology over multiple releases to first monitor equipment, then identify persistent faults, and finally detect new faults from logged data. The system architecture includes sensors connected to an on-site data processing system that uploads information to a SQL database and web server for analysis and reporting. This predictive maintenance approach allows for early failure detection and analysis to minimize downtime and maintenance costs.
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► Custom AI Software Development: Choose from our range of AI services, including AI Workshops with inspiring case studies and insights, Edge AI for real-time analytics on images, videos, sounds, and time-series data, Cognitive Automation for the automation of complex tasks with software robots, and HPC for algorithm optimization across various CPU, GPU, and FPGA architectures.
► Incubation: Explore our innovative product brainello, an AI-powered document processing software that works without templates, and Ewa Guard, AI for Drones enabling large area visual analytics.
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SM Infocom proposes a Production Analysis Application (PAA) to address challenges with complex production projects including time delays in addressing issues, a lack of insights from large amounts of data, and overreliance on manual processes. The PAA would consolidate production data from machines in real-time, perform analyses, and generate customizable reports to facilitate preventative action, improve resource utilization, reduce downtime, and increase output quality. Benefits of the PAA include real-time solutions, increased productivity and efficiency, better planning and forecasting, and reduced production costs.
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Applications whose foundation is laid on Reactive Manifesto accounts for being Reactive Applications. But can any monitoring pipeline ensure that its worthy enough to monitor your reactive fleet?
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CalArts毕业证学历书【微信95270640】CalArts毕业证’圣力嘉学院毕业证《Q微信95270640》办理CalArts毕业证√文凭学历制作{CalArts文凭}购买学历学位证书本科硕士,CalArts毕业证学历学位证【实体公司】办毕业证、成绩单、学历认证、学位证、文凭认证、办留信网认证、（网上可查，实体公司，专业可靠）
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Adriano Engineering CBM
- 1. Innovative Intelligence for Industry 4.0
- 2. Adriano Engineering System architecture SQL Server (Data Base) Web Server Application Server Process Data REAL TIME KPIs & Metrics AY% FPY% OEE% CPK PPM Non Conformities OTD Efficiency Maintenance Rework Safety Training
- 3. Real Time Condition Based Maintenance The predictive maintenance system is designed to determinate the condition of in-service equipment in order to estimate when maintenance should be performed. This brings several cost savings: • Minimizing the time the equipment is being maintained • Minimizing the production hours lost to maintenance • Minimizing the cost of spare parts and supplies.
- 4. Induce Failure Trending (one month) Vibration analysis by Adriano Vibration analysis by ISO 400 hours fault anticipation
- 6. Real Time Condition Based Maintenance •Real time failure detection •Failure analysis (diagnosis and prognosis) •Online report´s
- 7. Data processing On site data processing, fault detection and online report generation SQL Server (Data Base) Web Server Application Server Process Data
- 8. Sprint 1 Deliverable’s: • Monitoring system of motor or pump • Artificial intelligent failure classifier (Supervised learning) • DB logging and instant failure report
- 9. Sprint 2 Deliverable’s: •Identification of most persistent fault •Report update
- 10. Sprint 3 Deliverable’s : •New Fault identification base on logged data •Report update No. 1 No.2
- 11. Delivering time line Sprint 1 200 hrs Sprint 2 200 hrs Sprint 3 200 hrs Sprint 4 200 hrs Monitoring system Identification of most persistent fault New fault identification New fault identification Failure classifier Report update Report update Report update DB logging
- 12. Roadmap Process monitoring and fault detection Data Analysis with Machine Learning and AI Adaptive Predictive Expert Control System on Real-Time Sprint 1 Sprint 2 Sprint 3
- 13. Certification Vibration analysis level ll (ISO 18436.2)
- 14. Contact information CEO Marcos Adriano marcos@adriano-e.com Sales Manuel Monroy manuel.monroy@adriano-e.com AMS Yosef Zendejas yosef.zendejas@adriano-e.com R&D Luis Espinosa luis.espinosa@adriano-e.com contacto@adriano-e.com +52 (81) 2559-9871