Size 18

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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