Lloyd F. Colegrove, Mary Beth Seasholtz, Chaitanya Khare
This article discusses some experiences and challenges in establishing an enterprise manufacturing intelligence (EMI) platform at a major chemical manufacturing company, and recommends steps you can take to convince your management to harness big data.
Multiscale systems engineering has emerged as a way to understand and address the ever-growing list of global challenges related to energy and the environment. These challenges, many of which revolve around energy security, energy affordability, and...
Use this structured approach, which combines preliminary experimental data with predictive methods and heuristics, to quickly generate and screen process alternatives at the early stages of a new venture.
Climate models use mathematical equations to represent interactions between and within the ocean, land, ice, and atmosphere — providing a means to understand the climate system and predict future climate changes. They are becoming increasingly...
Today's CFD Programs are more powerful and easier to use than ever, thanks to improved mesh-generation strategies, computational methodologies, user interfaces and enhanced graphics capabilities. Cover photo courtesy of Acusim and Intelligent Light.
This article focuses on the regulatory drivers for alarm management, summarizes key practices, and challenges automation vendors to devise new ways to help customers implement more-effective alarm systems.
By employing the latest virtualization solutions for process control systems, chemical plants can reduce PC hardware requirements, simplify system management, and lower the total cost of ownership, as well as improve site availability, reliability,...
In silicocatalyst optimization is the ultimate application of computers in catalysis. This article provides an overview of the basic concepts of predictive modeling and describes how this technique can be used in catalyst and reaction design.
Computer-based environmental compliance training offers a number of advantages. This article discusses the benefits of computer-based training, outlines its most important components, and provides tips for structuring and writing a course.
Dynamic process modeling based on non-uniformly sampled data and multiple sampling runs, even for nonlinear systems, can be performed using spreadsheet implementations of the weighted-least-squares (WLSQ) and Runge-Kutta WLSQ methods.