Product Yield Improvement Increases Earnings By $20 Million

Improvements to Product Yield based on Optimizing Feed Network

• A network of feed Sources being fed to two Tall Oil Refineries.
• Current optimization was based on minimizing logistics costs.
• Feeds were being blended at each refinery into one large mixing tank.
• Distillation parameters were fixed with little feed-forward automation into Tower Control.
• Feed pricing was based on a negotiated price versus taking into consideration Feed Quality and Tower Yield Effects.

Feed Composition and Tower Yield Analysis and Modeling Findings

• Significant differences in quality and composition from source to source – differences in paper mill processing and regional differences due to the trees and types used.
• Some qualities had plugging and adverse effects on processing that were not clear to customers as well as a lower number of high-value materials.
• Purchasing contracts did not consider the quality and adverse effects on the process. Different feeds also had different effects on the two processing plants.

Impact to EBITDA of $20M/yr. due to improvement in Yield, Contract Repricing, and a reduction in downgrading low-value products.

Developed Refinery LP Model that simulated operations, assisted in monthly planning and ranked feeds based on quality, and impact on the plants that:

• Established profitability to the two plants by feed.
• Optimized feed distribution to two plants (ex: some feeds close to one plant had better yields at the other offsetting extra transportation costs)
• Ranked Feeds and established 3-grade levels for feed.
• Established better criteria for negotiating price.
• Optimization of feed network also reduced production and downgrading of low-value products.
• Ranked new feeds and determined optimum pricing relative to the feed yield database as new feeds were acquired.