Control strategy and methods for continuous direct compression processes

We presented a control strategy for tablet manufacturing processes based on continuous direct compression.The work was conducted by the experts of pharmaceutical companies,machine suppliers,academia,and regulatory authority in Japan.Among different items in the process,the component ratio and blended powder content were selected as the items requiring the control method specific to continuous manufacturing different from the conventional batch manufacturing.The control and management of the Loss in Weight(LIW)feeder were deemed the most important,and the Residence Time Distribution(RTD)model were regarded effective for setting the control range and for controlling of the LIW feeder.Based on these ideas,the concept of process control using RTD was summarized.

Data-driven soft sensors in blast furnace ironmaking:a survey

The blast furnace is a highly energy-intensive,highly polluting,and extremely complex reactor in the ironmaking process.Soft sensors are a key technology for predicting molten iron quality indices reflecting blast furnace energy consumption and operation stability,and play an important role in saving energy,reducing emissions,improving product quality,and producing economic benefits.With the advancement of the Internet of Things,big data,and artificial intelligence,data-driven soft sensors in blast furnace ironmaking processes have attracted increasing attention from researchers,but there has been no systematic review of the data-driven soft sensors in the blast furnace ironmaking process.This review covers the state-of-the-art studies of data-driven soft sensors technologies in the blast furnace ironmaking process.Specifically,wefirst conduct a comprehensive overview of various data-driven soft sensor modeling methods(multiscale methods,adaptive methods,deep learning,etc.)used in blast furnace ironmaking.Second,the important applications of data-driven soft sensors in blast furnace ironmaking(silicon content,molten iron temperature,gas utilization rate,etc.)are classified.Finally,the potential challenges and future development trends of data-driven soft sensors in blast furnace ironmaking applications are discussed,including digital twin,multi-source data fusion,and carbon peaking and carbon neutrality.