Читать книгу Profit Maximization Techniques for Operating Chemical Plants - Sandip K. Lahiri - Страница 33

With the advent of faster computers in CPI, a large amount of process data is collected and stored every minute by data historian software like IP21, the Pie system, Exaquantum, etc. Every second or minute data of all process parameters of whole plants are now available. This large historical data depository is a distinct feature of today's CPI as compared to older generation plants. These real‐time process data are like an untapped gold mine. Many insights and much process knowledge can be generated from these large sets of operating data. However, very little has been done so far. Due to the unavailability of effective process data analytics, the knowledge hidden in such data could not be tapped properly. The main concerns of CPIs are how to extract meaningful information from these data. Thus, today's chemical industry remains data rich but information poor. There is a need to generate an effective framework where knowledge can be extracted from this wealth of data. Advanced AI based big data analytics systems need to be applied to extract knowledge. The capability to meet this challenge is key for business excellence.