Machine Learning on IoT Data
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The complexity, criticality, and real-time demands of the energy sector make it a prime candidate to benefit from applying machine learning. This session presents two case studies of machine learning automating decisions for energy companies. For the largest windfarm operator in North America, machine learning applies predictive and prescriptive analytics to the complex task of scheduling crews for maintenance and repairs. Automating the scheduling process across multiple windfarm sites saves the operator millions in labor costs per year and frees managers and crews to do actual work. Machine learning also evaluates ever-changing conditions and automatically reschedules workers and tasks as necessary. For a large European energy company, online machine learning provides a systematic and automated approach to commodities trading, including creating and executing trading strategy and predicting prices.
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Machine Learning on IoT Data
- 1. Advanced Analytics Of IoT Using Machine Learning Paul Hofmann PhD CTO April, 2017
- 2. What We Do World-Class Platform We develop advanced analytics applications for asset- intensive industries that focus on operations in context, in motion, and in real time: collecting and correlating data, predicting asset condition and operation, optimizing and automating networks of people and assets, and visualizing everything in real time. Our applications are developed on our own advanced, end-to-end platform, and our machine learning engine produces intelligence agency-class analytics. This gives us a huge advantage in quality and time-to-value for our customers. Analytics for the IoT Revolution
- 3. Why SpaceTime? Rapid time-to-value and quickly add new capabilities Continuous optimization and action at the edge Past and Future Proof Connect legacy, multi-vendor, future Predict and optimize under uncertain conditions in real time
- 4. We’re Leading the Revolution SpaceTime has a global, Fortune 500 customer base spanning key industrial markets, including 8 of the 20 largest utilities. Key Customers Global Presence Singapore Japan EuropeUK Canada Corporate HQ Silicon Valley
- 5. Three Examples For Reasoning On Probabilistic Graphs Of Time Series
- 6. - Pricing Optimal Battery Warranty - Commodities Trading - Case Study Predictive & Prescriptive Windpark Maintenance
- 7. Use Time Series To Predict Nonlinear Battery Failure Innovative machine learning to find hidden patterns in time series Predict capacity degradation without having seen it in the wild Combine Hidden Markov Model with Hierarchical Mixture Models Why Reduce accruals by reducing financial risk of warranties How Predict degradation over time Find optimal policy for warranties
- 8. Failure Time Prediction To See Over The Hill The failure time prediction gives the probability of failure into the future – at any given point in time
- 9. CBM with Prediction Assumes failure at A: lower asset life, increased repair/replacement costs Time in Operation Advanced Machine Learning For Optimized Asset Lifecycle Failure SpaceTime Machine Learning ● Predict forward in time without loss of confidence ● “See over the hill” to extend asset life ● Produce better optimization for lower costs and increased productivity A Optimization Zone Probability of Failure Predict Failure Optimize Operations Detect Anomalies Extended Asset Life B
- 10. Comparing Predictive Models Risk tolerance threshold for unit failure, e.g. 12.5% • Risk tolerance is a constraint on operations • The model that produces fewest false negatives the longest is the most efficient • Accuracy is not the most important metric! • The trade off between failure rate and operating hours is more meaningful
- 12. The Holy Grail Of Time Series Beating The EMH Innovative machine learning to find hidden patterns in time series Combine deep learning with hierarchical dynamic Bayesian Models to predict price Use stochastic optimization for money management Learn optimal trading policy EMH Efficient Market Hypothesis Market reflects all relevant info Systematics Trading Make money beating the EMH
- 13. Futures Contracts Energy BRENT CRUDE WTI CRUDE US NATURAL GAS UK NATURAL GAS ETHANOL Brent CrudeMetals GOLD SILVER COPPER PALLADIUM Crops CORN WHEAT SOYBEANS OIL SOYBEANS MEAL
- 14. Helping Largest Wind Farm Operator Make Decisions Under Uncertainty • Reduced crew hours: $2.3 million savings/location • Optimized crew schedule • Improved crew safety and regulatory compliance • Solution – Crew Optimization – 250 users Success Story: Predictive Maintenance & Optimization ● Largest wind farm operator in the world; 19 states and 4 Canadian provinces ● 100+ sites; 10,000+ turbines; 1,000 teammates “Using advanced analytics to optimize resources and efficiency allowing us to reclaim thousands of lost hours of productivity” General Manager Largest Windfarm Operator Energy Resources
- 15. Optimization Weather Forecasts Crew Availability Work Order List Sensor Data Crew Schedule Crew Route Work Order List Traffic Value of Activities Performed Risk and Cost Managed Crew Skills Asset Failure Model Other Models DATA INPUTS OUTPUTS/ACTION Remaining Useful Life SpaceTime can perform optimization even when inputs involve uncertainty, like weather or traffic, and constantly changing inputs like the probability of asset failure. Global Optimization of Operations
- 16. Reasoning Under Uncertainty Over Graphs Speech Recognition Computer Vision Assets As ApplicationsGames Time in Operation Failur e A Optimiza tion Zone Probability of Failure Predict Failure Optimize Operation s Detect Anomalies Extended Asset Life B
- 17. The Team Jason Lenderman Alan McCord, PhD Rob Jones, PhD Zaid Tashman Marcela Munoz Recognition
- 18. Web: spacetimeinsight.com @spacetimeinsght linkedin.com/company/space-time-insight facebook.com/spacetimeinsight SpaceTime, SpaceTime Insight, and the Galaxy symbol are trademarks of Space Time Insight, Inc. Thank You @paul_hofmann https://www.linkedin.com/in/hofmannpaul Web: spacetimeinsight.com @spacetimeinsight linkedin.com/company/space-time-insight facebook.com/spacetimeinsight SpaceTime, SpaceTime Insight, and the Galaxy symbol are trademarks of Space Time Insight, Inc.
- 19. Backup