vehicle sector overview january 2018
TRANSCRIPT
VEHICLE SECTOR OVERVIEW JANUARY 2018
Proprietary & Confidential
OVERVIEW
AppliedEA reduces the high failure rates and overwhelming maintenance costs of manned and autonomous ground vehicles by providing a real-time solution that continuously monitors, analyzes and services these machines
and allows them to meet, and exceed, critical operational performance benchmarks.
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THE OPPORTUNITY
Maintenance is the largest and most important budget item associated with vehicle ownership
and operation
~50% of overall operational budget 200% of original vehicle acquisition cost
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10-60% failure rates
THE MAINTENANCE CHALLENGE
OPERATIONALREADINESS
LOGISTICS STRATEGICPLANNING
WHAT CAN STAKEHOLDERS DO TO IMPROVE OVERALL FLEET
AVAILABILITY AND COST CONTAINMENT NEXT YEAR?
ENTERPRISE, OEM, SERVICE PROVIDER
MAINTENANCE &SAFETY
SERVICE PROVIDER, INSURANCE UNDERWRITER,
DRIVER/OPERATOR
IS MY VEHICLE READY NOW? IS IT SAFE TO OPERATE? ARE
PROCESSES IMPACTFUL AND RAPID?
HOW MANY VEHICLES ARE PREPARED FOR OPERATIONS
TODAY? THIS WEEK?
OPERATIONS MANAGER
HOW MANY PARTS DO WE NEED NEXT WEEK? NEXT MONTH?
MAINTENANCE MANAGER, INVENTORY MANAGER
RE
LEV
AN
T
QU
EST
ION
S
KE
Y
STA
KE
HO
LDE
RS
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Affordability: an acquisition issue
Availability: an operations and logistics issue
Liability Exposure: a financial issue
Customer Retention: a business issue
MAINTENANCE DIRECTLY IMPACTS VEHICLE OEMS AND OPERATORS
Maintenance concerns fundamentally undermine
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THE KEY DATA REQUIREMENT
▸ Vehicle OEMs and operators require access to fundamental vehicle operational data in order to operate efficiently and profitably
▸ Vehicle OEMs and operators need access to very accurate and up-to-date information about the
• Vehicles
• Usage patterns
• Failure rates
• Causes of breakdowns
• Performance histories
• Maintenance records
▸ This data is acutely unavailable in the manned and autonomous vehicle sector – as a consequence, it is very difficult for an OEM or operator to dominate this growing market
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▸ AppliedEA makes it possible to automatically capture rating parameters as well as the historical data from the vehicle, in real time
▸ This huge amount of data can be analyzed for design, operations, availability, and supply chain decisions
▸ This moves vehicle OEMs and operators to the realm of continuous calculations – thereby reducing incurred losses with proactive strategies vs. historical tactics to achieve desired availability outcomes
• Higher Operational Rate
▪ % of operational vehicles
• Minimized cost to achieve the appropriate Operational Rate
▪ Fix what is needed faster, fix it correctly the first time, do not fix things that are not broken
• Optimized supply chain
▪ Lower cost and better Operational Rate since less vehicle downtime due to waiting for parts
WHAT WE PROVIDE
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CURRENT MAINTENANCE METHODOLOGIES
▸ Scheduled and Preventive
• Programmed on a time or usage trigger
▸ Predictive
• Model-based, looks at MTBF per component, defines a causality-driven model, and deduces what are the subsystem and system MTBF impacts
▸ Vibration Analysis
• Model-based, looks at single factor/component and identifies when it breaches operational parameters
▸ Unscheduled
• Activated by driver reports or other diagnostics
These approaches are expensive but still ineffective in meeting Operational Readiness targets and minimizing re-work percentages.
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OUR INNOVATIVE AVAILABILITY APPROACH
▸ Look at the empiric data
• If you perform a specific driving maneuver, the internals will behave in the exact same way
• We identify when the internals do not behave in the exact same way while executing the exact same driving maneuver and there is a potentially problematic escalation in degradation
▸ Take into consideration both the kinematics as well as internal sensors
• Identify driving maneuver micro-state where the internals are relatively stable
▸ Per operation, review each driving maneuver micro-state and validate that the internal sensor outputs are similar to the last X times this vehicle/model performed the exact same maneuver
• If you see an escalating degradation – then alert the relevant stakeholder and take action
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OUR SOLUTION
Log data on vehicle performance indicators –
such as energy usage, vibrations and temperature levels – is downloaded and can be used to monitor the health of a single vehicle or
an entire fleet
DATA
CAPTURE
Diagnostic algorithms automatically analyze
acquired data providing a comprehensive indication of
vehicle health contextualized by driving
maneuver data
BACKEND
ANALYTICS
Software and web-based tools communicate needed
repairs and suggest maintenance actions
RESPONSE
ENABLEMENT
The AppliedEA Condition Based Maintenance (CBM) platform dictates that corrective actions should only be performed when certain indicators show signs of decreasing performance, continuous operation outside the normal operational parameters, or upcoming failure.
AppliedEA increases vehicle availability rates by providing a real-time solution that continuously monitors, analyzes and services these machines.
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OUR DIFFERENTIATORS
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Rapid and Easy Deployment
Can work on any type of vehicleSuitable for both manned and autonomous vehicles
No hardware, no need to modify the vehicle, no certifications requiredCloud or on-premise implementation
No need to reskill or hire laborSupplements existing processes
Secure environment
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Definitive Outcomes
Ongoing and immediate feedback as to the reliability status of the vehicleIntegrated descriptive, predictive and prescriptive analysis
Based on advanced Artificial Intelligence and Machine Learning algorithmsFind actionable information cost-effectively regardless of the quantity of data
Utilize existing empiric dataFully-automated – no need for manual analysis or human intervention
User-friendly dashboard interface and drilldown tools
OUTCOMES OF THE APPLIEDEA APPROACH
▸ The entire value chain – from R&D to commercial implementation to aftermarket service – is positively impacted
• Lower severity and frequency of vehicle failure
• More accurate vehicle design
• Better understanding of the autonomous vehicle ecosystem
• Empiric evidence that regulatory and certification requirements are exceeded
• First-order cyber hardening
• Routing intelligence
• Higher customer satisfaction
• Lower insurance and warranty rates
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CUSTOMER IMPACT
Decreased Maintenance Costs
Improved Reliability
Enhanced Safety
Increased Availability
Incidents, Available Vehicles, Downtime
Reduced Liability Costs
Higher User Satisfaction
.
Lower Overall Program Costs
Replacement Cost of Inoperative Vehicles
Higher ROI
Lower Cost Per Operational HourLower Operational RiskIncreased Available Operational Hours
Per Same Budget
OPERATIONAL
FINANCIAL
Competitive Differentiator
Better Use of Available Data
New Opportunities in Manned and Autonomous Vehicle Markets
Highlights Improved Past Performance
Cyber HardeningBetter Risk Management Streamlined Material Flows
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More Detailed Troubleshooting Techniques
Reduced Training Burdens
APPLIEDEA AS A SOURCE OF COMPETITIVE ADVANTAGE
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Superior Products Barriers to Entry Directly Monetized
The proprietary data generated by the AppliedEA platform generates very valuable outcomes for vehicle OEMs and operators
ABOUT US
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Gen. Mike Hayden Dr. Bill Schneider Matthew Freedman Dr. Benjamin Mann
Director of the CIA. First Principal Deputy Director of National Intelligence. Director of the NSA. Four star general at USAF. Commander of the Air Intelligence Agency. Director of the Joint Command and Control Warfare Center. Director of Motorola Solutions. Distinguished Visiting Professor at Oxford University.
U.S. Under Secretary of State. Chairman of the Defense Science Board and the Defense Business Board. Director of General Atomics, BAE Systems USA, EADS North America, ABB Susa, MBDA USA, and Selex ES USA. Advisor to the U.S. Departments of Defense, Energy, and State. Advisor to Kurion-Veolia and DSI.
Advisor to U.S. Pacific Fleet, Defense Intelligence Agency, U.S. Special Operations Command, Department of State, Department of Defense, Department of the Navy, National Security Council, and Office of Management and Budget. White House Transition Director reporting to Secretary of State Colin Powell.
Inventor of Topological Data Analysis. VP at Ayasdi. Program Manager, Senior Scientist and Acting Deputy Office Director at DARPA. Program Officer at National Science Foundation. Faculty member at Harvard University, Clarkson University, and the University of New Mexico.
Dr. Paul Kaminski Dr. Tony Tether Dr. Rick Lawrence
U.S. Under Secretary of Defense. Chairman of RAND Corporation, the Defense Science Board, and Seagate Government Solutions. Director of General Dynamics, The Mitre Corporation, Bay Microsystems, CoVant Technologies, and Johns Hopkins Applied Physics Lab. Advisor to the MIT Lincoln Laboratory.
Director of DARPA. Director of the National Intelligence Office. Vice President of Science Applications International Corporation’s (SAIC) Advanced Technology Group. Director of Aurora Flight Sciences (acquired by Boeing) and Strobe (acquired by GM). Member of the Army, Navy and Defense Science Boards.
Head of Machine Learning and Decision Analytics at IBM Watson. Distinguished Research Staff Member at IBM. Head of the Neutronics Methods Group at the Argonne National Laboratory. Recipient of the 2014 INFORMS Innovative Applications in Analytics Award.
Josh SegalCEO & Founder
First employee and VP at Varonis Systems (Nasdaq: VRNS). Venture capital experience at Exigen Capital, Applied Materials Ventures, WR Hambrecht, and Global Catalyst Partners. Investor in P-Cube (acquired), M-Stream (acquired), Grandis (acquired), and Infinera (IPO). Combat service at Israel Defense Forces.
Gafar LawalCOO
Managing Director, CTO & Chief Architect, Morgan Stanley. Partner Architect, Microsoft. Chief Technology Architect, Merrill Lynch. Awarded two patents.
Senior Management Board of Advisors
Patrick LongDirector of Innovation
SVP Aviation Programs at 4M Research. Lean Six Sigma Project Officer at US Army. Maintenance Information Technology Officer at US Army. Special Operations maintenance test pilot at US Army. Grey Eagle Unmanned Aerial System Officer at US Army.
