2020 AIChE Spring Meeting and 16th Global Congress on Process Safety

 2020 AIChE Spring Meeting and 16th Global Congress on Process Safety
Aug 19, 2020
Virtual Meeting

See abstract below for presentation at the 2020 AIChE Spring Meeting. Join us or contact us for more information.

 

Harnessing Big Data Approaches and AI in the Chemical Processing Industry
Brian Rohrback – Infometrix

The term Big Data implies 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 Big Data 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, neuro-computing, and machine learning. In order for industry to achieve the goals that this form of AI promises, we need to approach the issues with more than just words.

This is a summary of a multi-company, multi-industry, hydrocarbon processing consortium, established seven 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. The idea is to enable a shift from current practices to approaches that take advantage of the computational power at our fingertips. It was critical to prioritize solutions that are non-disruptive, utilize legacy systems, and lessen the workload rather than layer on additional requirements. The result is a choice of tools available to consume the data and generate actionable, process-specific information are in hand. The analyzers in place, optical spectrometers in particular, represent the low-hanging fruit.

Last call. Upgrade Pirouette before July 1, 2020

Hello fellow Pirouette users.

If you are still using a legacy version of Pirouette, on July 1st the price to upgrade to the current version of Pirouette, version 4.5, will no longer be available. The cost will be the full retail price of Pirouette v4.5. Older versions (e.g., Pirouette 4.0) were designed and implemented for older Windows environments and have become less compatible with current Windows operating systems. If you are still using an older system that has not been upgraded to Windows 10, products like Pirouette 4.0 may still work. However, we are no longer fixing bugs or implementing enhancements. If you have an older version, we recommend you take advantage of the current upgrade rate before it goes to full price. If you have any questions, need additional information or a quote, email us at sales@infometrix.com.

IFPAC 2020 – Autonomous Calibration and Optimizing Chromatographic Interpretation

IFPAC 2020 cardIFPAC 2020
Feb 23-26, 2020
Bethesda, MD

See abstracts below for papers being presented at the IFPAC 2020 conference. Join us or contact us for more information.

 

 

Autonomous Calibration
Brian Rohrback – Infometrix
Randy Pell – Infometrix
Scott Ramos – Infometrix

The use of chemometrics in processing spectroscopic data is far from new; the processing of NIR data in petroleum refineries dates to the early 1980s and in the food industry well before that. Although the computers have improved in performance leading to speed ups in the calibration process, the procedures being followed have not changed significantly since the 1980s. Intriguingly, we have made decisions on the corporate level that work against each other. We are installing more spectrometers and at the same time we are reducing staffing for spectrometer calibration and maintenance. A change in approach is mandated. In the spirit of automation, there are tools from both the chemometrics and the general statistics realms that can be applied to simplify the work involved in optimizing a calibration. Robust statistical techniques require some set-up of parameters, but once established for an application, they are often useable in every other instance of that application. The result is a one-pass means of selecting optimal samples for a calibration problem and, in turn, simplifies the assignment of model rank. This approach solves two problems:

 

Optimizing Chromatographic Interpretation
Brian Rohrback – Infometrix, Inc.

The heartbeat of the process environment is in the data we collect, but we are not always efficient in translating our data streams into actionable information. The richest source of process information comes from spectrometers and chromatographs and, for many applications, these prove to be the cheapest, most adaptable, and most reliable technologies available. In chromatography, there is a rich history and the chemometrics role is well defined but rarely placed into routine practice. This paper will provide a retrospective of routine processing solutions that have solved problems in pharmaceutical, clinical, food, environmental, chemical, and petroleum applications. It also discusses how to use tech borrowed from other fields to provide more consistent and objective GC results, automate translation of the raw traces into real-time information streams, and create databases that can be used across plant sites or even across industries.

 

APACT ’19 – Autonomous Calibration and the Impact on Process Analysis and Control

Autonomous Calibration and the Impact on Process Analysis and Control – The use of multivariate analysis in processing spectroscopic data is far from new; the processing of NIR data in petroleum refineries dates to the early 1980s and in the food industry well before that. Although the computers have improved in performance leading to speed ups in the calibration process, the procedures being followed have not changed significantly since the 1980s. Intriguingly, we have made decisions on the corporate level that work against each other. We are installing more spectrometers and at the same time we are reducing staffing for spectrometer calibration and maintenance. A change in approach is mandated. In the spirit of automation, there are tools from the general statistics realm that can be applied to simplify the work involved in optimizing a calibration through selection of samples. Robust techniques require some set-up of parameters, but once the parameters are established for an application, they are often usable in every other instance of that application. The result is a one-pass means of selecting optimal samples for a calibration problem and in turn simplifies the assignment of model rank. This approach is completely independent of hardware configuration and can be used with any software – plus it solves two problems: It is a selection process that can be completely automated; and It is objective and does not rely on the relative skill of a specific analyst. The ultimate goal is to integrate spectroscopic measurements in a process setting with the same simplicity-of-effort with which we install temperature sensors. Presented by Brian Rohrback, Infometrix, Inc.

PEFTEC 2019 – Re-engineering Calibration for Process Spectrometers

Re-engineering Calibration for Process Spectrometers – This is a report of a multi-company, multi-industry, hydrocarbon processing consortium, established six years ago, to re-evaluate how the calibration process for analyzers could be managed more efficiently. The first focus was optical spectroscopy, an increasingly important source of process chemistry knowledge due to its advantage of speed, sensitivity, and simple safety requirements. As one of very few analyzer technologies that can measure chemistry, spectroscopy has become a workhorse in the chemical, petrochemical, and petroleum industries. But, even as the number of optical systems is continuing to increase, companies have been decreasing the number of employees who are tasked with their management. As a result, a paradigm shift is required for industry to adapt to a higher workload combined with changes in the fitness level and longevity of the technicians responsible for installation, calibration, and maintenance. What if we could put a spectroscopy system in place and have it handle the application and communicate results as soon as it is turned on? Then, if performance does not match legacy standards, the system dials itself in or calls for help. The systematic approach discussed is not constrained by the brand of hardware or by the software vendor and, as such, the approach can be used to manage any new or any in-place system. Presented by Brian Rohrback, Infometrix, Inc.