GOLDEN ALUMINUM Increases Production Effectiveness “I must tell you that most people in our plant are very impressed with ULTRAMAX®.  I have been able to reduce a particular quality defect (edge cracks off the Hot Mill) by 78%.  No one including myself has been able to do that in 20 years of operating this plant.” Larry Hopkins, Perpetual Improvement Manager Golden Aluminum, Fort Lupton, CO.   March 26, 2007.  Procter & Gamble Optimizes Manufacturing Operations Using ULTRAMAX^® Technology CINCINNATI, OH, Oct 10, 2001 – The Procter & Gamble Co. (P&G) has reached an agreement with Ultramax Corporation to purchase ULTRAMAX optimization technology for integration with P&G production computer control systems. ULTRAMAX technology continually adjusts manufacturing processes for maximum business and financial performance as materials and conditions vary and economic factors or business objectives change.  “The decision to integrate ULTRAMAX sequential optimization method and technology into Procter & Gamble manufacturing processes underscores our commitment to accelerating cost reduction,” says Cy Wegman, Optimization Specialist, P&G Corporate Engineering Technical Laboratory. “Our past experience using the ULTRAMAX method and technology has shown substantial improvements in operating performance and bottom line profits.”  ULTRAMAX dynamic optimization technology adjusts process settings to improve performance according to defined objectives and operational constraints. The process operates reliably within safety, capacity and regulatory constraints, achieving continuous improvements in product quality and throughput while reducing energy and raw material consumption, emissions and waste. The Procter & Gamble Co., headquartered in Cincinnati, OH, manufactures and markets 300 brands to 5 billion consumers in 140 countries. Founded in 1982, the Ultramax Corporation, also headquartered in Cincinnati, OH, is a leading international supplier of process optimization technology and services. For public release, P&G Alpharma Increases Fermentation Yield by 20% with ULTRAMAX “I consider ULTRAMAX to be the best system one could employ to make rational process control adjustments, with those changes quickly resulting in measurable (predefined) improvements. Of equal importance, these changes will result in a more robust, profitable and predictable process. “I am responsible for improvements in our large-scale fermentation process. Over the years, I have tried various non-linear modeling methods to make the necessary improvements in the process, as well as attempt to establish a higher level of predictability. Before ULTRAMAX, process improvements were frustratingly slow in coming and the results offered low predictability for two reasons: 1) a change in one or more uncontrolled inputs occurred during the course of obtaining the data that required additional tests to be run, and, 2) the control (decision) input changes had to be small so as to not cause a process failure, thus the outputs had very low signal to noise ratios. “The moment I was introduced to the ULTRAMAX concepts I knew deep down that this was the answer for which I had been searching. In the few years I have used it, my fermenter yield (on a near 50-year-old process) has increased by over 20%, with variability decreasing by over 50%. The decrease in variability has allowed me to "see" other variables that were impacting our process, and when changed, increased the robustness of the process.” Dr. Michael Barder, Alpharma IBM Accelerates Process Design and Improves Production Performance with ULTRAMAX “ULTRAMAX … has been effectively used by IBM to rapidly model and optimize existing processes, as well as efficiently develop (from zero knowledge) high performance processes to standards not previously experienced. Successful applications have been encountered in photolithography, dry etching, film deposition, thermal processing and ion implantation, with no failure of the software or its sequential optimization methodology observed. Final process yield improvement and process variability reduction are to be expected via this technology.” Bob McCafferty, IBM.