Читать книгу Profit Maximization Techniques for Operating Chemical Plants - Sandip K. Lahiri - Страница 44

Due to plastic pollution, pollution from cars and from various carcinogenic chemicals, the usage patterns and demands of various chemicals across the globe is changing very fast. This poses a challenge to chemical industries who makes those products.

One of the ways a research and development department of chemical plants can respond to this challenge is by creating higher‐value‐added, higher‐margin products at a faster pace, in particular in specialty chemicals and crop‐protection chemicals (Klei et al., 2017). Through intelligent algorithms, chemical companies will be able to use high‐throughput optimization to develop and adjust molecules that offer more value. They will also be able to deploy advanced analytics and machine learning to simulate experiments, to use digital predictive power to systematically optimize formulations for performance and costs, and to data‐mine information available from past successful and failed experiments. Not least, they will be able to identify the best possible resource allocation to enhance the performance of R&D teams and the innovation pipeline. Many of these practices are already established in the pharmaceutical industry but were largely unaffordable for chemical companies. With the emergence of inexpensive computing power on a massive scale, this is likely to change.