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Powering Industryat the OT/IT Edge
©2019 451 Research, LLC | WWW.451RESEARCH.COM
Industry 4.0 and Industrial IoT concepts are driving the collisionof operational technology systems and industry standardinformation technology systems
Industrial manufacturers use sensors and other devices to gather IoT data at the edge...
and use that data to power misson-critical use cases
Industrial intelligence integration is increasinglyhappening at the edge, near the machineswhere data is generated
Many industrial applications simply generate TOO MUCH DATA to be affordably transported to, stored at and primarily executed away from the edge
68%
66%
61%
61%
Sensors added toexisting equipment
Sensors alreadyembedded in equipment
Network devices
Control infrastructure(PLC, MES, SCADA, DCS, etc.)
% of respondents (n=79)
% of respondents (n=75/63)
451 Research case study analysis
38%
22%
17%
29%
29%
22%
25%
20%
24%
36%
43%
57%
63%
72%
Connected worker
Fleet tracking
Smart robotics
Intelligent logistics
Inventory monitoring and management
Predictive maintenance/condition-based maintenance
Production/manufacturing monitoring
TodayTwo Years
57%
50%
43%
41%
34%
27%
Security
Cost
Networkingconnections
Availability ofstaff/expertise
Infrastructureresiliency
Latencyconsiderations
$64,608.72
$191,826.17
$319,043.62
$21,406.14 $27,218.44 $33,030.73
$- $50,000
$100,000 $150,000 $200,000 $250,000 $300,000 $350,000
YEAR 1 YEAR 3 YEAR 5
EDGE VS. CLOUD COSTS OVER A 5 YEAR PERIODREAL-WORLD IOT USE CASE: MANUFACTURING QUALITY AND YIELD MONITORING
CLOUD
EDGE
NEAR-EDGE
EDGE
76% of industrial firms initiallyprocess their operational data at the edge or near-edge
Meanwhile, the type of analytics conducted atthe edge is becoming advanced (AI and ML),requiring more significant edge compute capabilities
Solution providers building industrial OT products and solutions must build and deliver them on ITindustry-standard compute, storage and connectivityinfrastructure capable of enabling a full-powered,fully-intelligent OT/IT industrial edge or riskthemselves, and their customers, being left behind.
FACTORS DRIVING WORKLOADS TO THE EDGE
Smartmachines
Multi-access edge
Microdatacenters
Sensors onlegacy equipent
65%
50%
49%
37%
47%
32%
Metrics and
Legacy OT Analytics
measurements
Rules-based actions
TYPE OF EDGE ANALYTICS EXECUTED
2017
2018
2019
Sources: 451 Research, Voice of the Enterprise: Internet of Things, Workloads Q1 2019 and Operational Technologies Perspective 2H 2018
35%40%43%
Advanced analysis(including AI/ML)
AI/ML OT Analytics
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