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MAY-JUN 2019

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INTECH MAY/JUNE 2019 17 PROCESS AUTOMATION case example about offshore platforms, McKinsey has shown that although huge amounts of data are already being collected, only a small portion is actually being used as a basis of operational deci- sions (figure 1). This is currently changing, as the technical infrastructure that allows data-driven decision making becomes available. Other important trends include flexible modu- lar plants for producing small quantities of fre- quently changing products. Such processes are more difficult to operate because of the frequent product changeovers, and it is more difficult to gather experience. New big data and artificial intelligence methods can predict upcoming problems long before they affect production. They also enable prescriptive maintenance strategies. Remote operation is be- coming more widely used. Often it makes sense to bring in highly specialized remote expertise. Sometimes even the whole plant is operated re- motely, as is the case for many offshore platforms. Modern control rooms have turned into net- worked information and communication centers where collaboration workflows come together. The remaining operators need a supportive work environment that helps them stay vigilant and carry out their jobs as effectively as possible. Breaking down information silos Modern process plants are complex and highly coupled systems. As a result, a problem in one part of the process will tend to propagate across dif- ferent subsystem and plant components. The ad- vanced automation systems in use also add com- plex dynamic interactions between the different plant components, making it difficult to obtain a clear assessment of a potential problem. Collab- orative efforts from a multidisciplinary team are needed to effectively troubleshoot, diagnose, or optimize process dynamics. In addition, the FAST FORWARD ● Digitalization, IoT, big data, artificial intelligence, and virtual reality will improve industrial process operation. ● Work environments must support collaboration at all levels and support high-performance work around the clock. ● Knowledge workers in process operation still spend too much time searching for data in information silos or proprietary tools.

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