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MAY-JUN 2018

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18 INTECH MAY/JUNE 2018 WWW.ISA.ORG PROCESS AUTOMATION control variables. Our midsized refinery will have about 93 high-level SPIs for daily viewing and use by management, 357 SPIs for hourly viewing and use by engineering personnel, and 377 SPIs for real-time viewing and use by shift opera - tors (figure 1). Some of the management and en- gineering SPIs use manufacturing ex- ecution system data as well as DCS data (e.g., production plan data, crude assay data, laboratory data), along with data from external sources, such as utility and feedstock pricing. Managers and engineers often prefer to check SPIs using a laptop, mobile phone, or tablet from anywhere in the world. Therefore, management and engi- neering SPIs are often provided via a digital twin in the cloud (figure 2). The digital twin in the cloud gathers data from the plant's distributed control sys- tems, historians, and labs—as well as from other sources, such as feedstock and energy pricing. It uses this data to calculate relevant management and en- gineering SPIs, and securely distributes this information to users worldwide. On the other hand, operations SPIs, the main topic of this article, can be de- termined using DCS data. Each of the 377 operation SPIs has up to five sub- categories in the areas of control per- formance, process performance, energy efficiency, asset performance, and criti- cal alarms. For SPIs not measured due to a lack of sensors or analyzers, process simulation can be implemented within the DCS to calculate soft sensors for es timating unmeasured process vari- ables from measured variables using rigorous process models. Improve operations Once the SPIs are created, they provide measurable goals for control room op erators, typically tied to optimiza- tion strategies and production plans. Most of these goals are achieved not through the efforts of a single operator, but by the effort of all operators working in the facility, so tracking operator per - formance is difficult, but can be done by using karaoke-type dashboards. In Japan, there is a mechanism for scoring karaoke singers based on cat- egories, such as pitch, technique, passion, stability, and rhythm. These dashboards help singers analyze their singing and motivate them to improve. In process plants, karaoke-type dash- boards use a similar scoring mecha- nism, but focus on operational priori- ties, such as production, profit, energy, reliability, and safety (figure 3). These dashboards help control room opera- tors analyze operational priorities and find areas for improvement, motivating them to achieve improved operation. The karaoke-type dashboard tracks the performance of each control room operator during his or her shift by checking the uptime of an SPI (time during which the SPI is in the ideal range or without alarm). Operators can check their performance with respect to profit, production, safety, reliability, and energy use. Improvements can be visualized by improved performance of the operator during a shift. Karaoke-type dashboards can be linked to relevant SPI dashboards that display each SPI with its ideal range(s). If a certain SPI is outside the ideal range, an alert is automatically activat- ed, and expert advice is displayed so the control room operator can take agile action to optimize the SPI. By optimiz- ing SPIs, operator actions mimic those of a multivariable controller, which is one of the categories of advanced pro- cess control, resulting in optimal con- trol of related process variables. Improve process plant engineering SPIs, alert information, and operators' scores are stored in the DCS, and plant engineering and third-party person- nel can use them for benchmarking, root-cause analysis, or expert consult- ing for continuous improvement. SPIs and related dashboards can thus help engineers and operators transform their work from event driven to profit driven. Even with profit-driven operation, it is easy to fall into the trap of func- tional silos of information, with each person optimizing his or her area of responsibility to meet objectives—but with overall effectiveness of the orga- nization, operation, or value stream suboptimal. This happens when the engineering team and management personnel use a set of SPIs that are different from and nonaligned with the control room operators' SPIs. This problem can be addressed by having aligned targets for engineering, opera- tions, and management. Figure 2. Digitally replicating live plant operating data and economic data in the cloud allows KBC, a division of Yokogawa, to distribute SPIs to management and engineering personnel worldwide.

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