Abstract: A method for maximizing the selectivity (S) of an epoxidation catalyst in an ethylene oxide reactor system, comprising: receiving a measured reactor selectivity (Smeas), a measured reactor temperature (Tmeas), and one or more operational parameters from an ethylene oxide production system, the measured reactor selectivity (Smeas), the measured reactor temperature (Tmeas), and the one or more operational parameters comprise real-time and historical operating data points over time generated by the ethylene oxide production system, and using a processor to conduct various calculations and determination in order to output an actionable recommendation that includes a target change (Mchange) of a moderator level (M) of a chloride-containing catalyst moderator to its optimal value (Mopt). The method further includes using the processor to (f) display the actionable recommendation on a display.

Abstract: A method for a selecting a loading pressure drop tolerance specification for a plurality of tubes in a multitubular fixed-bed reactor, wherein the plurality of tubes comprise a packed bed of epoxidation catalyst, the method comprising: defining a first loading pressure drop tolerance range for the plurality of tubes based on a desired maximum variation in outlet oxygen concentration, relative to the mean, for the plurality of tubes; defining a second loading pressure drop tolerance range for the plurality of tubes based on a desired maximum number of tube corrections for the plurality of tubes; and selecting the loading pressure drop tolerance specification for the plurality of tubes such that the entirety of the loading pressure drop tolerance specification falls within the first loading pressure drop tolerance range and the second loading pressure drop tolerance range.

Abstract: A near real-time system and method for continuous online monitoring of a plurality of operations in a continuous chemical process facility is described. The method of monitoring the operations is based on a multivariate statistical model developed using off-line, selected process-specific historical process data. Such a model is used by an online monitoring system to monitor the continual operation of a chemical manufacturing facility or refinery in real-time from a remote location. Such real-time monitoring allows for determination of whether one or more of the plurality of operations are operating within their normal operational parameters. This real-time, continuous monitoring system can further be used to predict impending failures or trouble-spots within the continuous production process, or to minimize catastrophic process failures which may occur in a continuous chemical manufacturing process.