NBTC 2004 Presentation Final

Proprietary and Confidential, Page 1Productize, Place, PackageProductize, Place, Package

PSG Inc.Phorix Solutions Group Inc.

““The Next Big Thing”The Next Big Thing”

Joe Anandarajah MBA, B.EngJoe Anandarajah MBA, B.EngPresident - Phorix Solutions Group Inc.President - Phorix Solutions Group Inc.

Technology Manager, IT – Innovations FoundationTechnology Manager, IT – Innovations Foundation


http://www.eaton.com/






For I dipped into the future, as far as human eye could see, saw a vision of the world, and all the wonder that would be.

– Alfred Lord Tennyson (1809 - 1892)





Introduction Trends & Opportunities

Intelligence, Mobility and Interaction Life and Physical Sciences

Portfolio PSG & IF Portfolio Demos and success stories

Packaging the Technologies Impact on your life





Phorix Solutions Group Inc. Value Added Resale and Systems Integration Expertise: Analytics, Business Process Verticals: Financial Services, Call Center and Other

Innovations Foundation Venture Creation and Licensing University of Toronto and External Technologies

Joe Anandarajah, MBA, B.Eng 9 years in IT Sales, Marketing, Systems Integration, Finance, R&D Passion for analytics and aptitude business & mathematics









Processing Power Trends Semiconductor 100x every 10 years Optical Transmission 1000x every 10 years

Market Adoption Increased from 0.5% to 3.5% of SG&A over the 90s Saturated Markets – Financial, HR, SCM, Desktop Applications Virgin Territory – Risk Management, Process Monitoring,

Development and Design

Application Trends Improve Flexibility and Lower Admin Cost – Soft Computing, Self

Healing, Configurable, FederationIT to Grow to 10% of SG&A





$ $$ $$$

System IT Department End User

Hardware, Software

Customization, Maintenance,

ReportingSales, Finance,

Engineering

Configurable, Federation, Self Healing





$ $$

Neural, Spike and Recurrent Networks – How We LearnFuzzy Logic – How We Reason

Bayesian, Markov, SVMs – Representation

More Processing Power -> More Intelligence





$ $

Processing & Delivery:

Graphs, Charts, 3D, Mobile, Learning

Interface: Voice Recognition,

Touch Screen, Virtual Reality





Life Sciences eHealth – Patient Care, Clinical Trials Medical Devices – Test & Measurement, Imaging,

Tools Drug Discovery and Design – MDIT

Physical Sciences Monitoring, Process Control and Diagnostics Computer Aided Design / Manufacturing Computation Materials Science – Bulk Properties,

Heat Transfer









Pattern Recognition Object Recognition and Tracking

Forecasting Condition Based Judgment Based

Diagnostics Expert Systems

DSL Enhancement Increase reach, bandwidth and diagnostic capability

eCash Works just like cash





Object Recognition & Tracking – Demo- Speed

- Lighting Tolerance- Orientation Tolerance





Food Processing Company: Executive Summary__________________________________________ ANALYSIS OF SHEAR PUMP BEARINGS

VIBRATION DATA 21 VIBRATION COVARIATES PROVIDED BY

ACCELEROMETER (CSI and Mastertrend)

3 (of 21) COVARIATES SIGNIFICANT ANNUAL REPLACEMENT COST SAVINGS IF

APPLIED TO PREVIOUS HISTORY = 55% INCREASE IN EQUIPMENT LIFETIME = 10.2 % SIGNIFICANT REDUCTION IN DATA COLLECTION

COSTS





Mass Transit Railway Corporation: Executive Summary

– Had excessive traction motor ball bearing failures

– CBM to monitor bearing grease colour

– Changed inspections from every 3.5 years to annual

RESULTS

- Reduced failures per year from 9 to 1- Reduced total costs by 55%





UK Mail Sorting

- Pilot Project Expert System - knowledge transfer to user - six week implementation with UK Partners - 400 Faults

GLIMP





DecydeWare judgement-based decision technology

Fills current gap between data and decision where the decision-maker must use professional judgement.

Models cognitive processes people use when they reason intuitively

Uses advanced soft-computing methods based on a patented algorithm

Helps the user make faster, more consistent and mathematically rigorous judgement calls when time, evidence, and experience are limited.





Step 1. Choose Risk Tolerance Level

Thresholds

min .80

min .50

max .30 c. Possibility of

b. Proof of

a. Strength of Evidence

Parameters

low risk

conservative

Risk

Degree

0

1

lo flo m fhi hi

fairly high risk





MethodConfidenceOpinionSource

CONCLUSION

Step 2. Select a Factor

Step 4 Enter the Evidence

min .80

min .50

max .30

Risk

Degree

0

1

lo flo m fhi hi

Parameters

Step 3. Choose Logic

IF Factor is THEN Risk is fairly satisfactory fairly low

Actual

Risk

Degree

0

1

lo flo m fhi hifairly satisfactory

fairly satisfactory

unsatisfactory

Source 1

Source 2

Source 3

sure

unsure

fairly sure

phone

in person

intuition Risk is unacceptable. Collect more evidence and recalculate.

Secondary Factor

Secondary Factor

Secondary Factor

Secondary Factor

Secondary Factor

Secondary Factor

Secondary Factor

Secondary Factor

Primary Factor

Primary Factor

Primary Factor

Primary Factor

Overall









Analytics Patterns, Forecast, Expert Systems

Interface Touch Screens, Graphs, 3D

Total Productivity = Machine + Human ProductivityIntuition + Automation + Real-time Human Intervention / Interaction

Problem Business Profitability > Solution DSS





Monitor – Object Recognition Quality

Forecasting – Condition Based Schedule maintenance based on quality trends

Expert System Low cost and most likely cause quickly

Forecasting – Judgment BasedPlanning









Have a VisionThink out of the BoxDomain Expertise

Cross functional

Quantitative Skills Intelligent Algorithms

Qualitative Skills Human Factors

New FrontiersRisk Management, Process Control, Health Care

