149 Big Data Analytics and Statistics I

Wednesday, April 13, 2016: 8:00 AM - 9:30 AM
335A (Hilton Americas - Houston)

The session welcomes contributors that highlight the application of statistics in Big Data Analytics in the process industries. The topics could potentially cover (but are not limited to) the planning of data collection, data pre-processing or management, data summarization to extract useful information, making inferences or predictions, etc. and should demonstrate how the methodology deals with the challenges in the big data setting (the 4Vs) with the goal of improve or optimize the process design or operations. The goal here is to highlight the importance of Statistics in Big Data Analytics applications.

Topical A: 2nd Big Data Analytics
Computing Systems and Technology Division (10)
Swee-Teng Chin Email: SChin@dow.com

8:00 AM
(149a) Root Cause Investigation on Defect Batches with Advanced Statistical Techniques
Wenyu Su, Jeff D. Sweeney, Wenzhao Yang, Marvin Tegen and Dayna Colvin

8:22 AM
(149b) Batch Process Monitoring By Dynamic Time Warping and k-Means Clustering
Adel Basli, Ajit Gopalakrishnan, Sudhir Kulkarni and Tim Poludniak

8:44 AM
(149c) Optimizing an Industrial Batch Process Using the Design of Dynamic Experiments Methodology
Christos Georgakis, Swee-Teng Chin, Philippe Hayot, John Wassick and Leo H. Chiang

See more of this Group/Topical: Topical A: 2nd Big Data Analytics