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Agenda Overview – Manufacturing – June 19-22, 2017
Pre-Conference Workshops: Monday, June 19, 2017
Full-day Workshop
Supercharging Prediction with Ensemble Models
Dean Abbott, Abbott Analytics, Inc.
Full-day Workshop
Hadoop for Predictive Analytics: Hands-On Lab
James Casaletto, MapR Technologies

Day 1: Tuesday, June 20, 2017
(PAW Business runs in parallel on this day - dual registration required)
8:00-8:45am Registration & Networking Breakfast
8:45-8:50am Conference Welcome
Bala Deshpande, IBM Watson Cognitive Center of Competence
Jon Riley, NCMS
8:50-9:10am Diamond Sponsor Presentation
9:10-10:00am
KEYNOTE
Weird Science: How to Know Your Predictive Discovery Is Not BS
Dr. Eric Siegel, Predictive Analytics World
10:00-10:30am Exhibits & Morning Coffee Break
10:30-11:15am Failure Detection, Fault Prediction, Predictive Maintenance
Case Study: Rolls Royce Company
Predictive Analytics Solution Template for Early Prediction of Assembly Line Failures

George Iordanescu, Microsoft
11:20am-12:05pm
Case Study: Beet Analytics
Manufacturing Asset tracking and optimization using predictive analytics

Girish Rao, Beet Analytics
Anish Mathew, Soliton Technologies, Inc.
12:05-1:30pm Lunch in the Exhibit Hall
1:30-2:15pm Panel Discussion
Venture Capital perspectives on Predictive Analytics in Manufacturing

Lead: Adrian Fortino, Mercury Fund
2:15-2:35pm Lightning Round
2:40-3:25pm Predictive Analytics in Digital Manufacturing
Solving The Curse of Dimensionality in Process Manufacturing
James Foster, Archer Daniels Midland Company
3:25-3:55pm Exhibits & Afternoon Break
3:55-4:40pm
Case Study: Siemens PLM
Closing the loop with Predictive Product Performance

Richard Semmes, Siemens PLM
4:45-5:30pm
Case Study: Usynaptics
TBA

Ken Anderson, Usynaptic
5:30-7:00pm Networking Reception

Day 2: Wednesday, June 21, 2017
(PAW Business runs in parallel on this day - dual registration required)
8:00-8:45am Registration & Networking Breakfast
8:45-8:50am Conference Co-Chairs Welcome
Bala Deshpande, IBM Watson Cognitive Center of Competence
Jon Riley, NCMS
8:50-9:10am Diamond Sponsor Presentation
9:10-10:00am
KEYNOTE
Artificial Intelligence: Will it make Smart Manufacturing Smarter?
Bala Deshpande, IBM Watson Cognitive Center of Competence
  IoT and Industrial Internet
10:00-10:45am
Case Study: Honeywell International
Profit from Insight: Monetizing Data & Analytics in Today's Connected World
Sakti Kunz, Honeywell International
10:45-11:15am Exhibits & Morning Coffee Break
11:15am-12:00pm Failure Detection, Fault Prediction, Predictive Maintenance
Case Study: 3DSignals
The Sound of (Machine) Music: How Deep Learning on Noise is Disrupting Industrial IoT
Gal Corfas, 3DSignals
12:00-1:15pm Lunch in the Exhibit Hall
1:15-2:00pm
KEYNOTE
Case Study: IBM
Cat DeSesa, IBM
2:00-2:15pm Sponsor Presentations
2:15-3:00pm IoT and Industrial Internet
Case Study: Schneider Electric
Reduce unplanned downtime using predictive maintenance

Michael T. Reed, Schneider Electric
3:00-3:30pm Exhibits & Afternoon Break
3:30-4:15pm Data Science for Manufacturing
Case Study: Magnitogorsk Iron and Steel
Decreasing Steelmaking Costs with Machine Leaning: A Practical Case Study

Sergey Sulimov, Magnitogorsk Iron and Steel Works OJSC
4:20-5:05pm Data Science in Manufacturing
To Be Announced

Post-Conference Workshop: Wednesday, June 21, 2017
Three hours: 5:30-8:30pm
R Bootcamp: For Newcomers to R
Max Kuhn, RStudio

Post-Conference Workshops: Thursday, June 22, 2017
Full-day Workshop
R for Predictive Modeling: A Hands-On Introduction
Max Kuhn, RStudio
Full-day Workshop
The Best and the Worst of Predictive Analytics:
Predictive Modeling Methods and Common Data Mining Mistakes

John Elder, Elder Research, Inc.
Full-day Workshop
Advanced Methods Hands-on: Predictive Modeling Techniques
Dean Abbott, Abbott Analytics, Inc.

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