BASF optimizes plant performance with real-time access to raw material and utility costs

BASF Corporation's Freeport, Texas, site wanted to optimize efficiency at its cyclohexanone production plant. The plant's raw material and a few key utility costs were significant contributors to overall caprolactam and polycaprolactam production costs, so controlling them was the lynchpin to achieving greater profitability for the site.

Scott Hines, operation engineer for the "Anone II" plant, one of two Freeport cyclohexanone plants, decided to focus improvement efforts on the plant's distillation and oxidation areas, to minimize raw material and energy costs per unit product made.

Traditionally, BASF's production management team had relied on monthly reports to make the connection between raw material and energy consumption and product output. Production departments could look at drum levels, raw material receipts and other data daily, but could only reconcile the information monthly to compare how much raw material and energy was used vs. how much product was produced. "With this approach, you can have a production or raw material problem and not realize it until the end of the month," says Hines.

To improve its control over utility and raw material costs, BASF implemented Invensys Corp.'s dynamic performance measurement (DPM) system at the Freeport plant. DPM identifies strategic economic performance indicators and uses these indicators to make profitability visible, in real time, throughout the organization.

BASF's goal was to allow decision-makers at all levels to see how raw material and energy costs were trending relative to plant output. Operators, in particular, required this information as they interacted with the process. It wasn't enough to tell them to "watch steam usage." They needed data in a meaningful form. "We [wanted] to improve our measuring system, and to take it from a monthly to a real-time basis," explains BASF Operations Manager Leonard Schooler.


In the past, Schooler explains, given the complexity of the plant and the many pieces of process equipment used at the facility, in-process inventory was assumed not to change. DPM allowed users to get a more accurate picture of what was really happening.

To implement DPM, Invensys consultants analyzed the plant's strategies, activities and performance measures, and developed a functional hierarchy (Box p. 23) for the plant's oxidation and distillation process areas. They worked closely with BASF to develop this hierarchy. "We tried to pick the most critical variables," says Hines.

Invensys then developed a model to calculate an indicator of performance based on process data. The real-time models were then installed in BASF's distributed control system (DCS), a Foxboro I/A unit, and average DPMs were calculated each hour, shift and day, and sent from the DCS to the plant's PI system, producing daily operations management reports. A range of "acceptable" levels or goals is set. Operators see a bar graph that shifts along with real-time performance levels, and indicates performance in dollars. Managers, meanwhile, see a number: the day's ratio of raw material used per pound of product made. "Users can tell right away whether they're on a loss or a savings trend, and can be alerted to process and equipment problems," says Hines. For example, if one part of the plant were using too much energy, it would be apparent from the reports, and troubleshooting efforts would be initiated immediately to correct the problem.

In one case, steam usage appeared to be much better than it should have been. "Something didn't look right," says Hines. In fact, reflux levels had fallen off and steam usage was down. The roots of the problem were traced to a filtration unit, which was fixed before quality problems became apparent."


Shown here, BASF Senior Production Technician, Tim Tobin (left) and Team Leader Drew McDaniel.

Source: BASF

"DPM helped us to optimize utility usage and reduced the costs of key raw materials," says Schooler. Another tremendous aid has been developing statistical design-of-experiment data. "DPM allows us to perform a much more accurate experiment with the system. By changing key parameters, we could determine the impact of process changes."


DPM screen views show profitability-vs.-output trends.

Souce: Invensys

The technology was easy to implement, says Hines. In addition, little training was needed, since technicians see the data in a relevant form: dollars.

BASF, which began installing DPM incrementally in 2001, believes that the system has paid for itself many times over, allowing the company to make significant cost reductions at Freeport. In fact, BASF now plans to expand its use of DPM at its Freeport facility and to install the technology at other plants in North America.

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