You can only gain access to certain items and special pricing if you have logged in. Login Now.
CC-97-135 NEURAL NETWORKS HELP OPTIMIZE SOLVENT EXTRACTION PROCESS IN A LUBE OIL PLANT
Anita L. Riddle, Mobil Corporation, Beaumont, Texas; Naveen V. Bhat, Paviiion,Technologies, Inc., Austin, Texas; Jack R. Hooper, Lamar University, Beaumont, Texas
Format:
Electronic (digital download/no shipping)
Associate Member, International Member, Petrochemical Member, Refining Member -
$0.00
Government, NonMember -
$35.00
Description:
Significant process improvements can be made even on older process units using artificial neural network models. At Mobil Beaumont Refinery, Texas, yields were improved by 8.4% on the light neutral stock and 6.2% on the medium neutral stock with no capital investment as a result of optimizing a furfural solvent extraction unit in a conventional lubricant refinery. Variability in by-product quality also decreased. Energy consumption was reduced by 7.7% on light neutral stock and by 2.3% on medium neutral stock. Air emissions were reduced by 6.4%. The benefits of these improvement in the processes are estimated at about $7,000,000 per year.
Product Details:
| Product ID: | CC-97-135 |
|---|---|
| Publication Year: | 1997 |