OT and IoT Convergence for Gas Compression example

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1 IOT SOLUTIONS WORLD CONGRESS 2018 IOTSWC OT and IoT Convergence for Gas Compression example Trygve Harvei, Digital Technology Lead, Oil Gas & Chemicals ABB

2 Digitalization and Automation «Mist» Edge enabling OT/IoT integration

3 IoT and Ethernet is driving disruption to standard Industry concepts Data and Data quality Infrastructure Cost and Availability Bell Baud Modem Sensors and Analytics APL IEEE P802.3cg 10BASE-T1L

4 Edge technology brings OT to IT using IoT Edge and cloud toghether example NAMUR requirements for change (I4.0) octubre 30, 2018 Slide 4

5 IoT and IT challenging the «ISA 95 model» IoT and SW challenging the traditionally modelled ISA95 type systems; implies introduction of OT/IT barrier. OGC template «design» in line with NAMUR requirements Enterprise + Cloud NAMUR requirements for change (I4.0) Edge OT/IT Barrier OT Support Systems IoT Telecom systems Video PA - Security Auxilary OT Systems Safety & Closed loop control Instrumentation & I/O Utility OT priorities: Functional Safety - Functional Integrity - Cyber Security - Integration capabilities IT priorities: - Cyber Security - 24/7 availability - Integration capabilities octubre 30, 2018 Slide 5

6 Digital and IoT Close the loop continuous optimization of OT utilizing IoT methodologies Optimization (digital) Act Improved operation Service Action Set Points IT and IoT Visualize Decide/apply Operational Technology Maintenance Operation Analyze performance Plant Health Operational data Sense Implementation (physical) Control signals Control Measurements Plant bridging both worlds octubre 30, 2018 Slide 6

7 Data drives business and services for process industries Data Ownership and cyber security Vendor A Vendor B Vendor C Vendor A Vendor B Vendor C Industrial Corp Co Data Lake OT Protection Layer octubre 30,

8 Transforming industrial devices (OT) to IoT at the edge IoT HUB Enabler for condition monitoring Enabler for process performance Enabler for energy management Data access to perform analytics and KPI generation Cost efficient and secure solution for access to new data and high resolution data IT Edge Replication Throttling Proxy GW Router octubre 30, 2018 Slide 8

9 Edge harmonization DDE SQL/ODBC IT Edge Including OT/IT integration Vendor Platforms octubre 30, 2018 Slide 9

10 Traditional Historian vs. IoT and Edge solution for Industry New insights enables optimization and basis for improved maintenance - Insights utilized for stabilizing production gives 2 5% higher throughput and less energy cost - Spare capacity can be focused on specific units operating typically in parallell to save energy and equipment wear. In practice 1 oo 5 units can be used as spare in production as a result of performance analytics several studies have shown - Online but scheduled analytics allows for dynamic adaptations to production environment. Individual KPIs for savings and prioritization of maintenance and optimization can more easily be created and displayed in dashboards for further insights octubre 30, 2018 Slide 10

11 Centrifugal/axial compressors KPI Performance deviation Deviation Monitors when compressor performance have deviated from factory/after-overall performance or if the compressor operates far from its design / best-efficiency region. Deviation from Expected Head A reduction in the delivered pressure (or head) has a negative impact on the energy consumption of the compressor and can lead to mechanical stress and damages to the machine. Recycle line options Hot bypass By-pass option 1 By-pass option 2 P T F P T F T Deviation from Expected Flow A reduction in the delivered flow rate has a negative impact on the energy consumption of the compressor and can lead to unexpected surge events that can severely damage the compressor. Operation in Sub-Optimal Conditions Monitors if compressor is working within design operating point to avoid working in choking or maximum driver power conditions. Compressor or compressor stage octubre 30, 2018 Slide 11

12 Monitoring of Axial Compressors Example detail view Performance Monitoring Compressor Performance Monitoring with use of process and electrical data Development of algorithms filtering out non relevant data, comparing with similar earlier states and qualify results based on electrical data octubre 30, 2018 Slide 12

13 Condition Monitoring of VSDs Example detail view VSD monitoring Asset Health overview showing state of the individual monitored conditions link to related fault modes. Example KPIs include health status of cooling system and abnormal wear caused by temperature cycling by combining process data with electrical data and sensors octubre 30, 2018 Slide 13

14 Closing the loop with IoT/IT/DevOps Benefits of Digital service loops Cloud based monitoring Analytics Easy access to asset health data, anywhere, anytime Facilitates collaboration between customer and domain experts Parameterization and alarm filtering can be handled by vendor Enables user configurable alerting and ad-hoc troubleshooting Supports continuous improvement, through parameter tuning and software updates (DevOps) Improves scalability through reuse of functionality across multiple sites Enables fleet management and predictive analytics based on fleet statistics Enables integrated access to maintenance advice based on FMEAs Digital reports Vendor Performance Energy Maintenance octubre 30, 2018

15 Enterprise analytics Digital journey through Edge and Cloud Local analytics with remote service capabilities Enterprise analytics as a service based on local and centralized analytics Managed edge and enterprises analytics Remote support from service experts Enterprise analytics Data Scientists SME s in Collaborative Operations Centers Validating and injecting expertize Enterprise analytics Data Scientists SME s in Collaborative Operations Centers On-demand support Vendor Data lake UX for managed enterprise analytics ABB Ability Local analytics server On-site SME Customer Data lake Customer Enterprise Users Customer Data lake octubre 30, 2018 Slide 15

16 OT and IoT convergence in a nutshell for gas compression application Networked smart devices is mainstream also in industrial environments Utilization of smartness in devices and practical utilization of available data is low due to design of infrastrucure, siloed application designs and cyber security issues IoT methodology utilized on OT devices creates new ways of capturing data with lower cost and higher quality than traditional historians Proxy solutions One way communication secures critical OT environments Closing the loop utilizing automated analytics Maintanance becomming predictive Performance optimization and energy utilization/management Bigger picture combining the two also integrating with production planning and operational systems Adding real time insights onto technical integrity management Real time - Dynamic time to surge supervision Further utilization of: Process data + equipment data Industrial «IoT» Historians Equipment Data 1.St order principals Analytics octubre 30, 2018 Slide 16

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