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Oil, Gas & Petrochemicals CementChemicalsMetals & Minerals Life Sciences UtilityAutomotive Intelligent, Self Describing Process Analytical Systems ABB.

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Presentation on theme: "Oil, Gas & Petrochemicals CementChemicalsMetals & Minerals Life Sciences UtilityAutomotive Intelligent, Self Describing Process Analytical Systems ABB."— Presentation transcript:

1 Oil, Gas & Petrochemicals CementChemicalsMetals & Minerals Life Sciences UtilityAutomotive Intelligent, Self Describing Process Analytical Systems ABB Analytical

2 Vision A self reliant, intelligent, “self describing” process analytical system that receives, sends and acts on multivariate data to monitor, communicate and control its status and health via any networked client.

3 NeSSI Generation 2 Opportunities For Improvement Component Centric Location of system level intelligence Method for accessing, controlling, and graphically representing NeSSI system undefined All components are networked

4 NETWORKED SHS DEVICES SYSTEM LEVEL ADVANTAGES Access and automatically observe and gather component ID, supplier data, etc. Multivariate data are provided at a single node Reduction in and management of communication cables A/D conversion local to the SHS component

5 NETWORKED SHS DEVICES SYSTEM LEVEL DISADVANTAGES Higher costs IS requirements for the physical layer limit the choices for a communication bus; network link budgets tend to degrade

6 NeSSI Generation 2 Opportunities Pervasive System Philosophy System centric architecture System level control, awareness, access resides in a local SHS controller/server System is object oriented and “Self Describing”

7 Concept Building Blocks SHS (Networked and Non-networked Components) Process Analyzer (Including Non-network Enabled 3RD Party) SHS Server/Controller

8 Integrated Smart Analytical System Architecture

9 The Value Proposition Improved System Reliability and Serviceability Reduced Capital Costs Reduced Operational and Maintenance Costs

10 The Methodology SHS Component Visibility Framework Networked and Non-Networked Components Self Describing SHS System Level Control

11 SHS Component Visibility SHS Node Classifications Accessible Directly acquirable by the SHS C/S Detectable Indirectly acquirable by the SHS C/S Invisible Neither accessible nor detectable

12 SHS Component Visibility Accessible SHS Node Classifications Networked: Multivariate data and control access are provided over a common wire IS interface. Non-Networked (Signal Level): Single signal/control access provided per interface connection.

13 SHS Component Visibility Accessible  Networked Accessible  Non-Networked

14 SHS Component Visibility Detectable SHS Node Classifications Isolatable: Attribute or detected condition ascribable to specific SHS component Non-Isolatable: Attribute or detected condition not ascribable to any specific SHS component

15 SHS Component Visibility Detectable  Isolatable Invisible  Non-Isolatable Detectable Flow

16 Interim Conclusions Making all SHS components network accessible is not entirely practical nor necessary A unified procedure for acquiring data from all SHS components (Networked and non- networked) and “self describing” the SHS are still needed.

17 The Methodology Sample System Component Visibility Networked and Non-Networked Components Self Describing SHS System Level Control

18 SHS SYSTEM LEVEL CONTROL Object Orientation Each SHS component described by an object model using standard XML schema Icon, port names and locations, predefined values and control fields to display component status or provide a graphical control handle, supplier specific data The component class models coupled with structures and procedures (interconnection and collective operation) make up a composite SHS class

19 C1 Data Structures Component Object Models FP1 C3 FP1FP2 C2 FP1FP2 C4 FP1FP2 SHS Controller/Server Component and System Object Modules Flow and Electrical Connection Netlists

20 SHS SYSTEM LEVEL CONTROL SHS system centric approach Control and access services are made available to external clients (PC, process analyzer, etc.) via a standardized XML schema served from the SHS Controller/Server The SHS becomes “self describing” via this server-client relationship The object oriented approach for system self description embraces a holistic view of the SHS as a coherent system of both physical and logical components that must be combined to work collectively to realize SHS functionality.

21 SHS SYSTEM LEVEL CONTROL The “As-Built” Configuration The system level representation of the SHS is now captured and described in an “As-Built” configuration file The “As-Built” configuration file is flashed to the SHS server/controller and presented on various networked clients

22 Reduced maintenance staffs; need for increased reliability and serviceability strongly dictate the need for a system centric, self describing Smart Process Analytical System NeSSI Generation 2 does not address all of the requirements for such a system A fully functional and cost effective smart SHS is achievable with a hybrid of networked and non- networked Data from all SHS components (especially non- networked!) can be acquired and completely represented using a self describing SHS XML approach and the Server-Client Concept SUMMARY

23 QUESTIONS?


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