Real-time process optimization taken to the next level

In the broad process industry, units operating automatically, e.g., through the application of advanced process control (APC) or real-time optimization (RTO) digital technology, can become up to 10% more efficient. By automatically calculating product quality and adjusting key process parameters, APC can reduce variability, minimize feedstock and energy usage, and reduce emissions. The trend of APC and RTO sees optimization become broader, encompassing more units, and targeting higher-level objectives. The demand for such optimization solutions will be geared towards sustainability, whereas now, they are primarily defined in terms of economic objectives and by now these technologies are fully mature.

APC and RTO are a must-have for companies to remain competitive

A plant typically consists of many different interconnected pieces of equipment. For example, in a refinery, there may be several processing steps to produce the final product. The third trend takes optimization to the next level because once a plant has optimized individual sub-units, there is an additional gain to optimizing them together. The goal would be to optimize multiple units or equipment together, with a unified objective, which might be to produce a given product while minimizing the CO2 emissions of the overall plant – something that’s not possible today. 

In another example, a chemical plant may generate a lot of residual heat, which could be used in a different department or even by a different company that runs a process requiring lower temperature. In this way, the optimization could be coupled across a group of companies.

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A dynamic mix of energy sources

As sustainability initiatives gather momentum (remember the first trend of moving toward sustainable production), the choice of energy sources used by the process industry will become more dynamic. The energy (heat, electric power) needed for a specific process at any moment in time may come from a mix of sources including fired boilers, onsite power generation, green electricity from a wind farm, gas-fired turbines, waste heat boilers using rest heat from the process, etc. To squeeze the next 5% of energy efficiency out of a process will require looking at the problem from end to end – it won’t be good enough to optimize individual pieces. The overall emissions and energy efficiency of an industry cluster will depend on this, and the economic and environmental pressures will ensure that it will be done.

The biggest hindrance to taking optimization to the next level remains in defining the problem, gathering the data, integrating datasets throughout the different units, and developing the models. The actual process optimization can be implemented using advanced data analytics technologies, which are now available open source.

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