2. Value Proposition - Skills Set
(why would you want to hire me?)
• 20+ years of solid experience in leading advanced technology programs
from both Engineering and Business perspectives
Key Strengths
Optimal balance of “big picture” and “attention to detail” -
always seeking balanced timely, cost effective and
technically adequate solutions
Expertise in product
Business oriented perspective
development processes
Diverse technical Strong people
knowledge/experience motivational/mentoring skills
Bias toward continuous Self motivated, ambitious,
process improvement very quick learner
Innovative, Strong problem
Strong communication skills
solving skills
Monesh Patel, 2011
3. Work History Demonstrates Growth
Functional Breadth, Technical Depth and Flexibility
Monesh Patel, 2011
5. Relevant Experience/Training
• 20+ years experience in Engineering Leadership/Program Management
• 20 years on DoD programs
• 15 years in Infrared/EO systems
• MS & BS in Mechanical Engineering
• Masters in Business Administration (MBA)
• Certified Raytheon Six Sigma Black Belt
• Design for Six Sigma, Business Development, Integrated Supply Chain, Lean
• Leadership/PM Training
• Principles of Finance Leadership
• Principles of Program Leadership
• Principles of IPT Leadership
• EVMS for Project Managers
• Strategic Leadership
• Systems Engineering Training
• Systems Enggineering Certification, California Institute of Technology
• Systems Engineer/Architect Certification, Raytheon
• UML/SysML tools/methodologies - ARTISAN
• Master of ConOps certification, Raytheon
Monesh Patel, 2011
7. As Chief Engineer, Led Development of Technologically
Challenging Helmet Mounted & Handheld Multi-Spectral
Networked Imaging Systems
HELMET HANDHELD
Locate Tank-sized Targets Day and Night
5km Range Day / 1.25km Range Night
Detect man-sized target to 150m (goal: 300m)
Operate over wide range conditions
Provide Target Location Components
Laser Range Finder; Laser Markers
Provide Form-Factor for Soldier Mobility
Vis/NI .4 - 1 µMultispectr
al
COMMON FEATURES R SW 1.2 – 1.7µ
input
IR
• Provide Multispectral LWIR, SWIR and VNIR Imaging LWIR 8 - 12 µ
• Adaptive Low-Power Image Fusion
• EZOOM / Super Resolution/ Image Stabilization
• Digital Video Recording - Store and Playback Still Images or Video
• Provide Warfighter Navigation Component - GPS / Compass / IMU Fused
output
• Exploit network connectivity between Warfighters - Share real time video imagery across wireless
network Monesh Patel, 2011
8. As Chief System Architect, Led 25 person Systems
Architecture Development Team on the Kinetic Energy
Interceptor Program
Payload
Kill Vehicle
: IMU KV : Link : Communication
BatteryComm Antenna
Comm : Antenna
data «precondition»
{
data IR has been ejected from the Canister
GNC : Processor Power Tm Antenna
PCU : : Telemetry : Antenna
Conditioning Tm IR has reached safe ignition condition
}
Boost
command data
Valve : Drivers
data «postcondition»
command command -Nav Data
State Not Achieved
{
TBD
data LDACS : Seeker
: KFC/C 1
«uses» }
command Nav (TBD) -Commands
1
Boost Fly-out
Normal Flow
«uses»
«postcondition»
Stage 3 *
«subtype»
S2/S3 Separation
Not Acheived
{
TBD
}
-H&S «subtype»
ACS : GPS : Receiver EED : Driver
Driver : PCU *
command S1/S2 Separation
data : Battery FTS
S3 : Command Destruct
Sequence
S2/S3 Separation
: KFC/C
* Sequence
anti-Jam Antenna -Cmd «postcondition»
GPS Terminate
{
Satellite *
Mission Terminates
}
Antenna «postcondition»
{
The separation of Stage 3 from Stage 2
The IR has achieved the required position/velocity/time
state that allows the payload to execute the intended mission.
}
Context
Diagrams Use Cases
KEI ConOps
+
AUR ConUse
+ Nav (TBD)
Nav (TBD)
KFC/C
KFC/C
Target Data
Navigation Data
Payload
Booster Normal Flow
Interceptor Round
Booster
Generate S1 Ignition Cmd
S1 Ignition Cmd
Sense Vehicle Rate Changes
Maintain Guidance Solution
Generate Steering Cmds
Steering Cmds
Ignite S1
Maintain S1 Vehicle Control
Canister
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ORPTNAC
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)S ,M ,H ,D ,M ,Y( pmatsemiT
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epyT noitamrofnI
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1
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)gnoL ,taL( tnioP hcnuaL
tnioP hcnuaL taerhT
1
1
emiT tcapmI detciderP
tnioP tcapmI detciderP
tnioP tcapmI detciderP
+ Functional Flows, Decomposition
R
Reliability
Pssk
Probability of
Single-Shot Kill
Piperf
Probability of
Interceptor
Performace
Psup
Probability of
Engagement
Support
+
Implement Steering Cmds 1 1 1
Change Vehicle Attitude
1
1
)deilppuS fI( epyT elissiM Pflyout Pdiscrim Pacq
Probability of Probability of Phit Probability of Pkill
)deilppuS fI( yrogetaC elissiM
rebmuN kcarT
Collect Payload H&S data Collect booster H&S
tropeR kcarT taerhT IEK - REI
Interceptor Flyout discrimination Acquisition
Booster H&S Data
Vehicle data downlink Generate Downlink data
Element Use Class
1st stage
performance
2nd stage
performance
3rd stage
performance
Pfor
Probability of Field
of Regard
Containment
Pskr
Probability of
Seeker
Performance
Cases Sequence Diagrams Function/Requirement
Diagrams Allocation Trees
A-Spec,
March 15
ID'd in Func Affected Analysis 06,
Func Reqmt H/W or Perf Specific Verificati needed Referenc
UC Step Use Case Text Func Veiw No. Requirement Text Subsystem S/W Inter ation(s) on or link e
Other Artifacts
+
3.3.3.2-01.02.05.01.01 The Interceptor Round Payload The Interceptor Round PIDS,IM
initiates Command S1 Ignition Payload shall initiate CIDS,
Command S1 Ignition Payload
Payload SW Func CIDS Yes 3.2.1.3 DA
3.3.3.2-01.02.05.01.02 The Interceptor Round Payload The Interceptor Round
sends the S1 Ignition Command Payload shall send the S1 PIDS,IM
Message to the Interceptor Ignition Command Message CIDS,
Round Booster to the Interceptor Round Payload
3.3.3.2-01.02.05.01.03 The Interceptor Round Booster
ignites Stage 1
Booster
The Interceptor Round
Booster shall ignite Stage 1
Payload HW I/F CIDS
PIDS,IM
CIDS,
Payload
Yes 3.2.1.3 DA
Trades List
Booster HW Func CIDS Yes 3.2.1.3 DA
3.3.3.2-01.02.05.01.04 The Interceptor Round Payload The Interceptor Round 3.2.1.2
senses Vehicle rate changes Payload shall sense Vehicle PES;
rate changes
Payload SW
PIDS,IM
CIDS,
Payload
Func CIDS Yes
3.7.1.2.3
Execute
KEI
Engageme
nt
Traceability of Functions to Requirements
Functional, Interface, Performance, Product Requirements
Combined Object Oriented AND “Traditional” Methods Used for Requirements Development
Monesh Patel, 2011
9. As Design for Six Sigma Change Agent, Planned
Product Development Culture Change - SAS DFSS
“Diffusion” Plan
June 2005 Mar 2006 Dec 2006
• Too many product • DFSS enables SAS drive to
failures/over run • Fewer product failures/improving
Mission Assurance
programs/customer Cost, Schedule/Satisfied Customer Mission
organization
dissatisfaction
• Increased Awareness of DFSS in LT, PM, • DFSS Processes
• Limited understanding of Engg. – benefits highlighted through real embedded in our culture
DFSS & associated benefits examples and successes; DFSS Webpage
created People
•100 % of Eng/PM population
• Eng./PM Population untrained • Key members of Eng/PM trained and practicing
population trained
• Programs don’t need
•Although Gate 5 requires DFSS •Program Goal Focused DFSS planning
starts before Gate 5; mandatory elements –
separate DFSS plans – DFSS
plan – Tool Focused DFSS VOC, Cost-Technical Optimization, Risk elements embedded in EMS
deployment Management, Performance Predictability
Process
• DFSS Tools not easily •DFSS tools rolled out and available to all • DFSS metrics used for data
available (through webpage?) driven decisions
• DFSSMetrics rolled out to • Need for special SME network
• Inadequate predictive metrics programs diminished – SMEs liberally
in place distributed
• SME network developed and flowed out
• No SME network
• DFSS Team Established – Center POCs • Organizational ownership
• Part Time DFSS Champion engaged of DFSS
Structure
• SAS LT flows down DFSS Expectations
KRA
Monesh Patel, 2011
10. As Design for Six Sigma Change Agent, Influenced Product
Development Culture Change by Showing the Gains
1. Cost Reduction Opportunities from CAIV/DTC: $4.5M
2. OLI DFSS Blitz: $3.85M
Achieve Affordability
• Cost & Schedule Targets
• Predictable Performance
• Problem Prevention
• Sustaining Gains
• Customer Satisfaction
DFS
Robust
S Producibilit
Performanc y
e
1) Predictable Performance 1) Cost Reduction Opportunities from DFMA:
2) Cost Avoidance from SDM for SNR: $215K $250K
3) Risk Reduction 2) Risk Reduction
Net Financial Benefit of DFSS projects: $9M
Total for ALL Expert projects: $16M
Continue to Drive DFSS into SBRS Engineering Culture: 3 more DFSS
Expert Projects Planned – spawning many more Specialist projects
