Читать книгу Profit Maximization Techniques for Operating Chemical Plants - Sandip K. Lahiri - Страница 45

As of now, it is quite clear that digital will have a significant impact on many areas of the chemical industry, with the gains in manufacturing performance potentially among the largest companies (Holger Hürtgen, 2018). Chemical companies have already created the infrastructure to collect and store enormous amounts of process data from hundreds of thousands of sensors, but very few have succeeded so far to take advantage of this data gold mine of potential intelligence. With the availability of cheaper computational power, IoT‐based cheap sensors, and intelligent advanced analytics tools, all chemical companies can now use those data to make more profit, extract knowledge from those data, and using machine‐learning and visualization platforms to uncover ways to optimize plant operations (Wang, 1999).

AI‐based machine learning tools can be used to develop insights into what happens in a chemical plant's complex manufacturing operations; this can help chemical companies solve previously impenetrable problems and reveal those that they never knew existed, such as hidden bottlenecks or unprofitable production lines.

There are three major areas where applications of advanced analytics tools can give an enormous profit increase, namely predictive maintenance; yield, energy, and throughput analytics; and value‐maximization modeling, as shown in Figure 2.3 (Wang, 1999).

Figure 2.3 Three major impact areas where advance analytic tools will help to increase profit