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An Integrated Analytical Process GC and SHS Based on IS CAN Communication Circor Tech Patrick Lowery ABB Analytical Tracy Dye IFPAC 2008 Baltimore.

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Presentation on theme: "An Integrated Analytical Process GC and SHS Based on IS CAN Communication Circor Tech Patrick Lowery ABB Analytical Tracy Dye IFPAC 2008 Baltimore."— Presentation transcript:

1 An Integrated Analytical Process GC and SHS Based on IS CAN Communication Circor Tech Patrick Lowery ABB Analytical Tracy Dye IFPAC 2008 Baltimore

2 Vision An integrated process analytical system that receives, sends and acts on critical multivariate data to monitor, communicate and control its status and health via any networked client.

3 NeSSI TM Value Proposition Improved System Reliability and Serviceability Reduced Capital Costs Reduced Operational and Maintenance Costs

4 Innovative, Early Adopter Market ? Time Prevalence Gen 2 Gen 1 Achieving the stated vision and value proposition in an innovative, early adopter market dictates the need for a phased, risk reduced approach.

5 Phased Market Approach Phase 1 – Connectivity Hybrid communication system Discrete analog outputs for single signal devices Discrete digital inputs IS CAN networked components for multivariate data devices Basic control Temperature, flow, filtration backup, valve switching Basic indication Sample flow, ΔP, temperature

6 Phased Market Approach Phase 2 – “Self Describing” All SHS components have open standard description file (EDDL, XML, etc.) Real time operational view of SHS on any networked client Fully integrated process analytical system

7 IS CAN for the NeSSI TM Communication Bus “Plug and play” in Div 1/Zone 1 classified areas CAN is everywhere in demanding applications (marine, auto, aerospace) Balanced signaling (differential drive) enables superior noise rejection (relative to unbalanced single end) especially over cables Open and Standard, already built in … Data Integrity Mechanisms Integral Bus Error Recovery and Self Correction Message Prioritization Via Non-Destructive Arbitration Mature and Well Defined Application Layers Such As CANopen Master to slave or peer to peer communication This allows individual devices to contain their own alarms and setpoints Allow for the system to interact with other devices in the system without the “SAM”

8 Smart SHS Topography What is needed to ascertain status of SHS? Power Pressures Flows Temperature (both ambient and actual fluid temp) System valve status Filter “health” (need two signals, either pressure/flow, or pressure & differential pressure) Example of basic smart sample system topography

9 Smart SHS Topography FIBER OPTIC CAN CABLE (ENTIRE GC CONTROL ON FIBER OPTIC CANopen NETWORK ANALOG I/O & IS BARRIERS, IF NEEDED SAM IS POWER SAMPLE SYSTEM CABINET HEATER INTRINSICALLY SAFE CANbus ANALYZER LOWER LEVEL NETWORK PROCESS CONTROL NETWORK DCS SYSTEM AND FIREWALL/ NETWORK SWITCHING STATION

10 Smart SHS Topography BYPASS FAST LOOP FLOW, TEMP, PRESSURES FILTER HEALTH (FLOW AND DIFF PRESSURE) VALVE STATUS FLOW TO ANALYZER GC ATM REFERENCE PRESSURE DIFF PRESSURE AND FLOW ACROSS STREAM SELECT POWER MONITOR AND DEVICE INVENTORY/ HEALTH FROM CAN TO SAM

11 WHAT IS “SAM” There is no industry consortium on the definition of SAM (Sensor Actuator Manager) The definition of SAM in this system topology is: Bridge between C1D1 (Zone 1) and C1D2 (Zone 2) for CAN communications Integrated analog I/O to digitize 4-20mA devices Obtains inventory of all CAN networked devices using IEEE virtual TEDs concept (i.e. device profiles/ data sheets) Monitors total IS can bus power consumption and health Has a basic application interface that can pass alarm triggers and set points down to devices and pass alarms and data up to GC GC is not the sample system master per se, but a data server Future upgrade path for CAN device metadata to provide system configuration data up to HMI at GC interface

12 Comparison to Traditional/ Legacy SHS Purely mechanical SHS Lower initial capital cost, but no data from system If system goes down, analyzer goes down, process is diverted or fines can occur (in emission monitoring applications) EPA requires backfill of worst case data for emission monitoring analyzer downtime, average of $15-25k per event Higher cost in human “capital” and higher average analyzer down time One refining case study found an average of 6 hours of process down time (per event) from time of DCS alarm to time that analyzer/ process chemistry was verified 6 hours of process downtime = BIG $$$

13 Comparison to Traditional/ Legacy SHS Analog instrumented SHS (GEN 1.5) Analog devices (in most but not all cases) are less expensive No multi-variate data from single device All devices must be discreetly wired and must have Discreet IS barrier Analog I/O module to PLC or data logger PLC or data logger Ethernet or other field bus communications module Data can be shown that digital bus implementation can reduce overall system cost ~$300 per sensing point cost savings on pressure/temp sensing ~$2000 per sensing point on flow, including cabling/wiring cost ~20-30% reduction in needed modular or fitting hardware ~40% reduction in wiring/ installation / integration cost

14 Still challenges ahead Although major technical hurdles are being addressed, there are still some market challenges ahead Further reduction of cabling cost needed along with some more choices of chemical compatibility options New types of power levels and digital bus implementation at IS certifying bodies More IS power supply vendors needed Further reduction in component costs can be realized by economy of scale (although highly expensive gen 1.5 systems have been economically justified at several large refineries)

15 Still opportunities ahead GEN 2, digital bus SHS also provide new opportunities Integration of “grab bag” closed-loop sample system with continuous GC SHS for validation Can differentiate between analyzer problem and SHS problem; if analyzer isolated as problem, can automatically route sample to sample cylinder for lab analysis Can localize heating solutions with tighter control or vaporize liquid samples near source to GC, remove the need for problematic liquid inject valves XML metadata into device profiles for graphical representation on HMI displays Integration of continuous analyzers along with associated SHS onto analyzer network


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