Decarbonisation Technology - November 2021

Additionally, as continuous flow applications become increasingly common, refineries can benefit from a PAT knowledge manager that is equipped with flowsheet modelling functions for dynamic material tracking and tracing, which also supports closed-loop feedback process control. These capabilities provide important insights into the movement of materials and products through continuous processes, as well as in- depth characterisations, from raw materials to final product batches. Therefore, such a model can be particularly beneficial when feedstocks with highly variable levels of impurities are used. A PAT framework can help oil processing facilities to adopt more sustainable materials and practices by addressing key production challenges while providing advantages that can enhance a business’s competitiveness in the marketplace. In particular, such a system enables facilities to have the in-depth understanding needed to maintain optimum process Total quality management for green products conditions at all times as well as enhanced control over their operations. As a result, PAT can reduce waste, processing time and ultimately energy consumption, helping to make decarbonisation practices more commercially and environmentally sound. To maximise the benefits that can be achieved with PAT setups, refineries need to implement a knowledge management platform that can support real-time process control. An example of a highly effective solution that delivers these capabilities is the total quality management software synTQ, which is already widely used in demanding industries where advanced monitoring strategies are required, such as pharmaceutical manufacturing. The software has been proven to help businesses cut the environmental impact of their manufacturing and processing activities while supporting the delivery of high-quality products at competitive prices.

specific lignocellulosic biomass being processed, optimising throughput. 1 Also, processing plants can leverage accurate quality predictions for dynamic control. In effect, facilities can benefit from real-time process visualisation as well as the ability to manually or automatically change the CPPs to optimise the operating conditions and CQAs. For instance, ethyl ester content prediction models based on NIR measurements have been effectively applied to support biodiesel production practices. Specifically, this method has been used to monitor on-line alkali-catalysed transesterification reactions of soybean oil and ethanol, 2 helping biorefineries maintain optimum processing conditions. This strategy is also highly beneficial in determining when the reaction is complete, avoiding under- and over-processing. Data management for effective PAT frameworks In order to create a truly holistic and immediate understanding of their new processes, refineries should incorporate a knowledge management platform to support their PAT strategies. This software can gather and share data with sensors and analysers on the processing line as well as MVA tools and industrial automation devices. Such devices include programmable logic controllers (PLCs), distributed control systems (DCSs) as well as supervisory control and data acquisition (SCADA) platforms that regulate refinery operations. The platform also interfaces with higher-level management systems, such as manufacturing execution systems (MESs), thus combining the insight provided by different levels of the automation pyramid and presenting it in an easily understandable manner to subject matter experts. Besides providing a central hub, an advanced PAT knowledge management solution has the ability to directly control multiple CPPs at the same time to obtain the desired CQAs. This can be performed automatically by means of an intelligent control algorithm. By adopting this technology, refineries can do more than simply keep CPPs as close as possible to their set-points. In fact, they can enhance the flexibility and adaptability of their processes while enhancing efficiency and end product quality.

Martin Gadsby mgadsby@optimal-tech.co.uk VIEW REFERENCES