Invensys planning, scheduling system improves ethylene plant profitability

Foxboro, MA— Invensys Production Management ions for refining and petrochemical plant optimization and decision support. Invensys Production Management is a division of Invensys plc (London, U.K.) that includes APV, Avantis, Baan, Eurotherm, Foxboro, SimSci/Esscor, Triconex and Wonderware.

“In the past, non-linear approaches were considered to be too slow and cumbersome to solve this type of complex planning problem,” says Lanny Carr, Invensys Production Management’s vp. “However, olefins production is inherently non-linear, so using a linear programming (LP) approach often resulted in solutions that were not as accurate as they should be, compromising plant profitability.

“In contrast, Invensys’ planning system combines the accuracy of a non-linear model with the execution speed usually associated with LP approaches. By enabling planners to quickly and accurately determine the most economically advantageous mix of available feedstocks for olefins production, our new planning tool can help today’s plants save anywhere from $5 to $10 per ton of finished product. In a 400,000-ton-per-year plant, the typical payback for this investment can be six months or less.” The company adds that its non-linear approach can result in typical savings ranging from $2 million to $4 million per year.

This new planning and scheduling system combines elements of Invensys’ process simulation and non-linear optimization technologies from its Simulation Sciences division, as well as the full capability of Spyro yield prediction technology from Technip-Coflexip. The new system can be used for a broad range of ethylene plant applications, including strategic studies, feedstock evaluation, monthly planning, and daily production scheduling. Advanced, equation-based optimization technology simplifies model building and maintenance, while the familiar Microsoft Excel spreadsheet user interface insulates planners and schedulers from the complexities of the non-linear optimization model.

Control Engineering Daily News DeskJim Montague, news editorjmontague@reedbusiness.com

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