Environment & Safety Gas Processing/LNG Maintenance & Reliability Petrochemicals Process Control Process Optimization Project Management Refining

Information Systems

Boosting temperature inferential control performance in distillation columns

Beijing University of Chemical Technology: Huang, K.  |  Luo, X.

An effective compensation method improves performance

HP Control: Continuous improvement or core-competency?

Tesoro Corp.: Kern, A.G.

In the past decade or two, the concepts of key performance indicators (KPIs), continuous improvement, core-competency and best practices have received a lot of attention. What are the relationships be..

Improving data reconciliation and yield accounting

Indian Oil Corp. Ltd.: Patil, P.  |  Roy, G.

Here's how the Mathura Refinery's data reconciliation and yield accounting project was implemented

Practical process control system metrics

Tesoro Corp.: Kern, A.G.

Here are several useful examples

Agile supply chain planning

M3 Technology: Acuff, C.  |  Jasper, D.
Chevron Corp.: Thomas, C.  |  Tong, D.

Providing a common workspace improves data integration

Service-oriented architecture simplifies data source integration

Infosys Consulting: Samdani, K.

Here's how the approach helps refinery scheduling and also contributes to business-wide SOA adoption

Predicting octane numbers for gasoline blends using artificial neural networks

Iran University of Science and Technology: Pranghooshi, E.  |  Sadeghi, M. T.
Sahand Univerity of Technology: Shafiei, S.

The ANN models were more accurate than regression models

Implementing and maintaining advanced process control on continuous catalytic reforming

Kuwait National Petroleum Corporation (KNPC): Al-Majed, A.  |  Kaushal, S.
Aspen Tech Middle East (ATME): Banerjee, P.

The primary benefit was an increase in reformate octane barrel yield from operating the plant at its economic constraints

Computational fluid dynamics simulation of solid–liquid slurry flow

National Institute of Technology: Ghanta, K. C.  |  Lahiri, S. K.

The resulting model's predictions showed reasonably good agreement with the experimental data

Genetic algorithm tuning improves artificial neural network models

National Institute of Technology: Ghanta, K. C.  |  Lahiri, S. K.

The technique is illustrated by predicting hold-up of slurry flow in pipelines