INGENIEUR
Figure 10 : The design of optimal conversion pathways in an integrated biorefinery
of sustainability have received increasing attention in industrial practices , education and research fields , numerous pivotal decisionmaking criteria in process synthesis and design including , the efficiency of raw material usage , energy consumption , environmental performance , process safety and occupational health , and integration of process efficiency are now included in PSE .
One commonly studied process synthesis model is the design of an integrated biorefinery , which incorporates several chemical reaction pathways for the conversion of biomass as a sustainable source of energy into value-added biochemical products along with heat and power . Our students enrolled in the System Optimisation course are tasked with utilising systematic screening approaches to identify optimal conversion pathways depending on various design objectives using mathematical optimisation tools . Aspects such as economic performance , raw material allocation , environmental , safety and health impacts are considered during the preliminary design . Figure 10 shows the optimal conversion pathways in an integrated biorefinery synthesised through superstructural mathematical optimisation techniques .
Meanwhile , screening chemical candidates for a particular process application is crucial to obtain optimal process performance . This problem is known as chemical product design , which involves the development of chemicals and formulations possessing the required specifications and characteristics to satisfy customer needs . Product design problems are often solved through computer aided molecular design ( CAMD ) techniques , which have emerged
Figure 11 : Optimal working fluids for an ORC application
as effective tools for designing a vast number of molecules with the desired properties through the use of optimisation tools . CAMD methodology can be adopted in the chemical processing industry for the replacement of hazardous chemicals with less hazardous alternatives that also exhibit compatible property attributes and performance . For instance , students are also assigned to search for promising working fluids for an Organic Rankine Cycle ( ORC ) through CAMD , with the optimal chemical candidates shown in Figure 11 . Through CAMD , the application of chemicals with reduced hazards in processes can minimise the magnitude of consequences or the likelihood of occurrence of an unwanted industrial accident .
Process Control and Machine Learning
Machine learning is a method of data analysis that automates analytical model building . It is a branch of artificial intelligence based on the idea that systems can learn from data , identify patterns , and make decisions with minimal human intervention .
36 VOL 89 JANUARY-MARCH 2022