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NOV-DEC 2018

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PROCESS AUTOMATION INTECH NOVEMBER/DECEMBER 2018 19 in their quest to add value, minimize risk, increase profits, and lower costs. The TV series Star Trek: The Next Generation shows how employees can use data analytics to add value. When crew members need to make a decision, they ask their computer (AI) questions to leverage the vast amount of stored information and determine the best course of ac tion or to phrase further questions. This open information exchange helps the crew make the right decisions at the right times, and the AI learns more about those situations. Value of data analytics There are many applications of data analytics in chemical plant engineering, product development, customer ser - vice, and service or product development. One concrete example is using AR/VR or mobile devices to guide and assist technicians. Here are some ways that data analytics can add value: Predictive maintenance: Similar to predictive plant control, real-time data is used to predict when equipment will fail. In stead of performing maintenance on an arbitrary schedule, you do it only when it is necessary, guided by past experience. You are more likely to identify equipment failure before it hap- pens and better manage the risks involved. The key to success here is the experience of your maintenance staff. Real-time process optimization and predictive control: De ploying AI/ML can deepen the understanding of how a plant operates. Building upon your employees' past experi- ence, predictive operational control and real-time process optimization enhanced by AI/ML will further improve qual - ity, reduce safety issues, and optimize energy and raw mate- rial consumption. Energy management: The process industry relies on utili- ties (e.g., electricity, steam, gas, and water), and energy man- agement is necessary to limit costs. Today, energy manage- ment focuses on the collection of energy data to achieve certifications like ISO-50001, which are typically used for tax benefits. If you combine this information with systems like MES, enterprise resource planning (ERP), and supply chain man - agement, it becomes easy to predict the energy consump- tion based on the scheduled activities. You can use these predictions to negotiate shorter-term energy contracts— freedom to choose the best offers can bring significant savings. Plus, you can analyze process data together with energy data to optimize your production process to reduce your energy consumption. Support at all levels Developing your own custom Industry 4.0 architecture is one part of the picture. Industry 4.0 needs your support as it evolves to adapt to new challenges and use cases. Chief of ficers, such as CIOs, CTOs or CDOs, play critical roles in the transformation to Industry 4.0. I agree with Nick Ismail in his recent article, "Artificial intelligence: Data will be the differentiator in the market- place," where he said that the CIO is essentially responsible for the "support and sustain" side of things, while the CTO is responsible for translating the new business requirements to technical requirements. All parties involved should learn about existing standards and participate in the development of new or updated standards. Support from evolving standards ISA-95 is a cornerstone in an Industry 4.0 architecture, as un- derlined by Charlie Gifford and David Daff in "ISA-95 evolves to support smart manufacturing and IIoT." I am personally developing an ISA-95-based architecture as illustrated in the figure. This lets my organization reap the rewards of using an established standard, helps with the IT-OT convergence, and manages the flow of the data and information between the operational functions. Quick wins give your Industry 4.0 project momentum: l Analyze and document processes and infrastructure. Complete understanding is required before new tech - nology or processes are introduced. Bringing employees onboard will be easier, and you may discover many easy optimizations. l Build inexpensive interfaces between your existing infra- structure and processes to collect and share data. l Create digital dashboards to streamline communication using the cost-effective edge computing and IoT technolo-

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