Big Data Analytics and Process Safety I


Description:
Contributions that combine the area of Big Data Analytics and Process Safety are welcome in this session. Approaches that are capable of analyzing multiple data sources (such as distributed control systems (DCS), historians (ip.21, LIMS), emergency shutdown databases (ESD), operator log books) in order to identify process near-misses and determine the probability of serious accidents are welcome in this section. Areas of interest include proactive alarm management systems capable of providing real time insight to detect equipment failures, development of novel process safety leading indicators, hazard risk assessment methodologies and Industrial applications that focus on demonstrating improvements on process safety performance utilizing big data analytics are of special interest in this session.

Sponsor:
Process Safety Spotlights
Co-Sponsor(s):
Topical A: 3rd Big Data Analytics (TA)


Chair:
Osvaldo Bascur
OSIsoft, LLC

Email: OsvaldoB@osisoft.com

Co-Chair:
Andrew Staszak
Senior Engineer
MMI Engineering
Houston, TX
77094
Phone Number: 979-575-1897
Email: astaszak@mmiengineering.com


Papers:
A Data-Driven Early Warning System for Mining Accidents
Yu Luo, Columbia University; Ashutosh Nanda, columbia University; Shivaram Rajgopal, Columbia University; Vinay Ramesh, Columbia University; Venkat Venkatasubramanian, Columbia University; Zhizun Zhang, Columbia University
New Ways to Visualize and Consolidate Alarm Management KPIs
Leandro Pinto Sr., Braskem; Vanessa Conz, Braskem
A Simple Way to Calculate Control Loop Service Factor Taking in Account Plant Conditionals
Leandro Pinto Sr., Braskem; Erica R. P. Claro, Braskem S.A
See more of this Group/Topical: Global Congress on Process Safety