Join Brian Rohrback, President of Infometrix on Feb. 25th at 1:00pm ET.
Free Webinar: Process Control & Instrumentation Series
Practical AI: In Search of Dynamic, Autonomous Process Analytics
The application of the concepts behind artificial intelligence and machine learning mandates a systematic approach to extracting information from multiple, byte-dense data sources. Effective extraction of this information leads to improvements in decision making at all levels of the chemical, petrochemical, and petroleum industries. To accomplish anything in the AI space, we need to combine traditional approaches in statistics, database organization, pattern recognition, and chemometrics with some newer concepts tied to better understanding of data mining, neurocomputing, and machine learning. This is an introduction to a practical approach to deploying AI and how a multi-company, multi-industry, hydrocarbon processing consortium, established eight years ago to re-evaluate how the calibration process for sensors and analyzers could be managed more efficiently. The focus spans optical spectrometers, chromatographs, and process sensors, independently and in combination, with a shift from current practices to approaches that take advantage of the computational power at our fingertips.
Dr. Rohrback’s expertise covers the integration of multivariate data processing for process analyzers and laboratory instruments catering to routine quality analysis. Prior to his current position, he worked for Cities Services Oil Company, now Occidental Petroleum, with industry positions including research scientist managing the chromatography group, an exploration geologist, and manager of planning/budget for EAME. He holds a B.S. in chemistry, a Ph.D. in organic geochemistry, and an MBA. His 50-year span of published works include topics in petroleum exploration, chemical plant optimization, clinical and pharmaceutical diagnostics, informatics, pattern recognition and multivariate analysis.
Venue:
April 23-25, 2024
Hyatt Regency Hotel, New Brunswick, NJ
Presented by:
Brian Rohrback, Ph.D., MBA, President, Infometrix, Inc.
Abstract:
The use of multivariate statistics, whether termed chemometrics or machine learning or (fill in the blank), is critical for industry to move from human-centered processing to more automated, objectively reliable processes. In the laboratory world, we seek to discover new routes for solving problems that will give us better solutions than previous methods. And this largely university-based effort is critical for enabling improvements in product manufacturing and the quality control process that accompanies it. But, given academia’s limited access to commercial application samples, most chemometrics publications deal only with the method development side of a given problem. If we are going to benefit a manufacturing organization, an industry, or especially society, the emphasis needs to be on the shift from this laboratory origin to a solid process implementation. Anything useful we devise must ultimately get used; if we fail to integrate proven technology into the day-to-day, the development process is simply an expense. The experience through the now five decades of implementing multivariate solutions has identified some steps, some barriers, and some low-hanging fruit. How do we succeed in pushing new technology the last mile?
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