Innovative Intelligence for Industry 4.0
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
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.
Induce Failure Trending
(one month)
Vibration
analysis
by
Adriano
Vibration
analysis
by ISO
400 hours fault anticipation
Frequency Analysis
ISO state
Excellence
Short-term
operation allowable
Real Time
Condition Based Maintenance
•Real time failure detection
•Failure analysis
(diagnosis and prognosis)
•Online report´s
Data processing
On site data
processing, fault
detection and
online report
generation
SQL Server
(Data Base)
Web Server
Application
Server
Process Data
Sprint 1
Deliverable’s:
• Monitoring system of
motor or pump
• Artificial intelligent failure
classifier (Supervised
learning)
• DB logging and instant
failure report
Sprint 2
Deliverable’s:
•Identification of most
persistent fault
•Report update
Sprint 3
Deliverable’s :
•New Fault
identification base
on logged data
•Report update
No. 1
No.2
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
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
Certification
Vibration analysis level ll
(ISO 18436.2)
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

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Adriano Engineering CBM