Streaming Data and Event Infrastructure - OSIsoft

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Streaming Data and Event Infrastructure by Alcoa’s Smelter Control System to either increase or decrease load. An increase load signal means that the smelter is consuming excess MW’s from Midwest ISO’s system which also results in an increase in aluminum production. A load decrease signal results in a drop in aluminum production thereby diverting some of the Warrick Power Plant’s electricity into the Midwest ISO system to make up load demand of the grid. Either way, Alcoa wins. With common data, Alcoa talent across the globe will engage in collective innovation and the pursuit and sharing of best practices. In order to focus Alcoa Talent on management of the plant, measurement data must meet the following criteria: Accurate, Real-time, Correlated and Historized. Sharing a common language with other plants will allow Alcoa to truly realize the Alcoa Advantage. A discovery in one plant can result in procedure, training, and policy changes in the other plants. SMART measures will become common measures. They will allow Alcoa to share best practices from one plant to another. IBM IBM Burlington is a large semiconductor manufacturing site which consumes 3.2 million gallons of water PER DAY and 446 million kilowatt hours of electricity annually. The sites potable water is supplied from the Champlain Water District. This potable water must be purified to meet the strict Ultra Pure Water (UPW) quality requirements needed for semiconductor manufacturing. UPW is 10 million times cleaner than the raw potable water. By using the PI System, IBM has achieved over $10M in annual savings, reduced water usage by 27%, reduced operating costs, and minimizing environmental impact while increasing manufacturing capability by 30%. The IBM Corporation is using Advanced Water Management techniques to drive cost improvements required to compete in a global market. These techniques are applied to Ultra Pure Water systems, heating and cooling waters, potable, non-potable and waste water treatment in semiconductor manufacturing. Water systems are closely monitored and data is collected and analyzed to support the decisions necessary to achieve IBM’s desired water management goals. These goals include strict control of water quality, reduction in water consumption, reduction in energy consumption and overall lower cost of operation. The IBM plant has achieved a 27% reduction in water usage, $3M in annual savings while manufacturing output increased by more than 30%. IBM’s data driven water management techniques have wider application that can be applied to address water issues for water stewards, distributors, industry and consumers. Water management challenges are largely a data management challenges. From the water resource all the way through to the water consumer, to the wastewater treatment operations and back to the resource there exists vast amounts of water data: usage, sustainability, quality, pricing etc. Organizing the data, analyzing the data and presenting the results in easily accessible formats transforms the data into manageable pieces of usable information. This information is the basis for sound decision making around water issues. Last Saved May 4, 2012 10 of 20
Streaming Data and Event Infrastructure The challenges are extracting the information in an efficient and meaningful way, presenting usable information to the proper levels of the organization and making data supported decisions to move towards established goals. Although the water industry is data intensive, to a very large extent data management systems have been lagging behind some more advanced industries such as petrochemical and semiconductor manufacturing. As water management issues become more critical the application of these techniques become appropriate. IBM uses the OSIsoft PI System for data collection, organization, analysis and presentation of data. IBM’s advanced water management data analysis tools were developed borrowing techniques from IBM’s manufacturing operation. These techniques allow for the transformation of vast amounts of raw water data into manageable amounts of useful information. These advanced water management techniques can be successfully applied to water management issues for ecosystems, utilities, industries and municipalities. KPIs provide the primary information tool to drive an organization towards its water management goals. KPIs were developed to be user appropriate at various levels of the organization. The IBM Burlington site has reduced over 2000 water monitoring data point to 80 KPIs. These 80 KPIs are analyzed automatically, abnormal circumstances are brought to the attention of operations and drill down capabilities within the software allows for quick troubleshooting of excursions. IBM’s water treatment goals can be simply described as continuous operations, maintaining water quality and operating at low cost. There are over 400 million data packets per day being analyzed. This amount of data would be overwhelming without advanced techniques to transform it into usable information. IBM has applied OSIsoft data collection and visualization along with KPIs, SPC and Cost Modeling to support IBM’s water management goals. These techniques are used in combination with more conventional real time data trending and correlation. The goal of these techniques is to transform the 400 million packets of data into a manageable amount of useful information. Through the use of computer driven data analysis only important information is extracted and brought to the attention water system engineers, technicians and operators. There has been a 27% reduction in water purchases and associated purchased water cost. Since much of the water saved was Ultra Pure Water there are additional savings associated with the treatment steps. There is a strong relationship between water and energy. This was important for IBM as it provided additional justification to implement projects. There is capital cost avoidance related to supporting the increased semiconductor manufacturing output. The efficiencies gained allowed support of increased manufacturing with existing infrastructure. Sappi Fine Paper The pulp and paper industry is incredibly competitive—retention and expansion of market share are key factors to success. Not only is this industry capital-intensive, it also requires the balanced management of multiple resources. Add to that the recent interest customers have in knowing more about where their paper comes from, and the business need for rich data is Last Saved May 4, 2012 11 of 20
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Streaming Data and Event Infrastructure - OSIsoft

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