Dynamic Risk AnalyzerTM (DRA)

Early Risk Detection for the Process and Energy Industries

Ulku Oktem, PhD Co-founder, CEO and President oktem@nearmissmgmt.com

www.nearmissmgmt.com | Philadelphia, PA

Ankur Pariyani, PhD Co-founder, Chief Innovation Officer pariyani@nearmissmgmt.com

Deb Grubbe Chief Marketing Officer grubbe@nearmissmgmt.com

Accidents

Hidden Near-Misses

(Not Casually Observable)

Incidents (Observable Near-Misses)

Core Concept

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Initiation Phase

Hidden Risks (in Process Data)

Incident Major Event

Time

Imp

act

Alarm / IOW

Resolve Process Risks at Initiation Stage with DRA

Early identification of process issues when process is still within normal limits

3

Dynamic Risk AnalyzerTM (DRA)

Early Risk Detection Software

Detects process problems at initiation stage autonomously

Alerts operating team

timely

Analyzes hundreds of tags using patented

technology

4

Problem Initiation

DRA Detection

Operations Team

Safe & Reliable Operation

Process Data

Precursors

Corrective Actions

• Spends 10-15 mins to review all tags (full peripheral vision) DRA points out problem areas – autonomously

Typical Operating Unit: • Has thousands of tags (temperatures, pressures, etc.)

Typical Engineer: • Spends 1-2 hrs and reviews 20-30 tags/day (~3% tags)

using Spreadsheets / Historian / Trending tools

Engineer WITH DRA:

DRA Difference

Industrial Control System

Firewall

DCS

SCADA

PLC/ Instrument

systems

Process Control Network

Business Network

SECURED CUSTOMER NETWORK

Managers

Engineers

Operators

Firewall

OPC

DRA Architecture

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ONSITE DRA SERVER

Historian

EQUIPMENT ISSUES Compressor Vibration Problem Product Bucket Problem Control Valve Plug Erosion Pressure Control Valve Plugging Level Control Valve Plugging Pump Cavitation Pump Clogging

Customer Case Studies Early Detection of Operations Issues

PROCESS ISSUES Steam Leak in Sulfur Bath Hydrocarbon Carryover Furnace Plugging Line Plugging Lube Oil Filter Clogging Temp. Controller Problem Overhead Seal Oil Issue

INSTRUMENTATION ISSUES Sensor Flatlining Faulty Transmitter I/O Card Module Failure

OPERATOR ISSUES Operator Error Unstable Operating Procedure

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Customer Case Study: Compressor Vibration Problem

• DRA identified anomalies in vibration variables for a rotary equipment

• Unit was running at higher load than normal

• No alarms were activated (high alarm at 1 mm)

• Rectified by center realignment of compressor

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120-day Trend of LPC Axial Vibration (in mm)

Early indications by DRA

Maintenance shutdowns

Customer Case Study: Control Valve Plug Erosion

• DRA identified anomalies in valve

opening, indicating slow but steady decrease

• Possible root causes were identified early on and spare parts were ordered

• Investigation showed that the valve plug erosion caused the decrease in opening (see below)

Level Control Valve Opening (60-day trend)

Early indications by DRA

9

Findings Anomalies detected by Production Supervisor on mid-level indicator for an amine sweetener column and communicated promptly to Operation Engineer.

Actions Operation Engineer confirmed the abnormality and raised notification.

Benefits Early detection of the anomalies prevented a possible hydrocarbon carryover which will have resulted in potential further downstream unit interruption.

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Customer Case Study: Hydrocarbon Carryover Avoidance

Findings Anomalies detected by Operation Engineer through

DRA – indicating sudden drops in LC503.PV

Actions Maintenance Order was raised to apply engineering

solutions for the equipment.

Benefits Early detection of drops prevented further

possible pump cavitation (P-21254 ), which will

have resulted in costly equipment damage and

process interruption.

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Customer Case Study: Pump Cavitation

Early indications by DRA

Benefits of DRA – Beyond Just Risk Detection

Uptime, Efficiency, HSE, Quality

Prevent emergency maintenance

Move from reactive to PROACTIVE culture

Increase peripheral vision and team’s productivity

Benchmark plants and operations

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DRA INSTALLATION

DRA Hardware Requirements (Per License)

Processor: 4 CPU cores (physical cores) at 2.8 Ghz RAM: 16 GB Storage: 1 TB of HDD Operating System: Windows Server 2012 or Linux OS (RedHat/SUSE/Ubuntu) Server type: Virtual machine (VM) or physical server NOTE: • Specs are for each DRA unit and are sufficient to support ~5 years’ worth of data. • A higher end server can be used to install multiple DRA instances on a single server.

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DRA Implementation Steps

For each DRA Unit to be installed

Configure a Server for DRA (IT)

Identify tags to be monitored (Operations)

Organize tags into groups (Operations)

Identify shutdown rule(s) (Operations)

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FACILITY CHECKLIST

Install DRA software in collaboration with Facility IT

Populate tags to be monitored

Program shutdown criteria

Schedule historical calculations

Conduct user training

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DRA Implementation Steps NMM CHECKLIST

~ 1-2 days

~ 2 weeks

~ 2 hrs x 3 sessions

DRA in PETRONAS Annual Sustainability Report 2015

Award Finalist – Nov 2017

Award Finalist – June 2017

Process Interventions & SAP Maintenance –Summary

HYDROCRACKER

AFTER DRA

Autonomous analysis of 700+ tags

Results available for morning meetings

Problem Resolution

Selection of 15-25 tags by Engineers

Identification of potential problems

Quick identification of potential problems

Fast communication with Maintenance/Operations

BEFORE DRA

~ 2 hrs

700+ TAGS

1M+ DATA POINTS

RECORDED DAILY

How does one identify the risk

information buried in this data timely

and efficiently?

BIG DATA (Per Process Unit)

~ 15 mins

Communication with Maintenance/Operations via Emails, Phone Calls, etc.

Problem Resolution

~ 1-2 hrs

Analysis via trending tools (Historian, Excel, etc.)

~ 2 hrs

MORNING MEETING WITH OPS GROUP

Actions based on review of 25 tags

Analysis of 700+ tags

Quick identification of top 5-10 risks

Actions based on review of 700+ tags

Follow-up on effectiveness of

actions

Review impact of change

Review of ~15-25 tags

DAILY REVIEW BY ENGINEER

Review based on operating limits and alarms: • Urgent process response • Maintenance requests

FOLLOW-UPS DURING DAY

WITHOUT DRA

WITH DRA

MORNING MEETING WITH OPS GROUP

Review based on DRA indicators: • Early process interventions • Timely Maintenance requests

FOLLOW-UPS DURING DAY

24x7 PROCESS MONITORING BY OPERATORS

DAILY REVIEW BY ENGINEER

Self-Directed Engine

Drill-Down to Problem Areas

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Peripheral Vision (Enterprise-Wide Risk Information)

Rapid ROI

DRA Differentiators

Intuitive Interface

Institutional Memory

Early Detection of Problems