US 12,472,469 B2
Method and system to monitor and control continuous ultrafiltration process units
Venkata Sudheendra Buddhiraju, Pune (IN); Venkataramana Runkana, Pune (IN); Vishnu Swaroopji Masampally, Pune (IN); Karundev Premraj, Pune (IN); Vivek Kumar, Pune (IN); and Swati Sahu, Pune (IN)
Assigned to Tata Consultancy Services Limited, Mumbai (IN)
Filed by Tata Consultancy Services Limited, Mumbai (IN)
Filed on Oct. 25, 2022, as Appl. No. 18/049,338.
Claims priority of application No. 202121050333 (IN), filed on Nov. 2, 2021.
Prior Publication US 2023/0139290 A1, May 4, 2023
Int. Cl. B01D 61/22 (2006.01); B01D 61/14 (2006.01)
CPC B01D 61/22 (2013.01) [B01D 61/145 (2013.01); B01D 2313/701 (2022.08)] 18 Claims
OG exemplary drawing
 
1. A processor-implemented method for monitoring and controlling continuous ultrafiltration (UF) process units, the method further comprising:
receiving, via a one or more hardware processors, a plurality of input data from one or more sensors configured to an UF process units, wherein the plurality of input data comprises a real time data and a non-real time data;
pre-processing via the one or more hardware processors, the real time data by removing outliers and imputing missing values;
converting, via the one or more hardware processors, an inline conductivity sensor data associated with the real time data into a concentration of protein of interest at (i) a feed flow stream, and (ii) a retentate stream of the UF process units based on a plurality of CDC models;
predicting, via the one or more hardware processors, critical quality parameters (CQPs) comprises a volumetric concentration factor (VCF) value and a throughput value of the UF process units by selecting a model from a model repository using the real time data and the non-real time data further comprising (i) a pressure data, (ii) a feed flow rate and (iii) the concentration of protein of interest in the feed flow stream;
optimizing, via the one or more hardware processors, the VCF value and the throughput value based on a plurality of optimal variables recommended for a given feed concentration, wherein the plurality of optimal variables comprises an optimal feed flow rate and an optimal pressure data, wherein a plurality of operating parameters of the UF process units is optimized, using a plurality of models from the model repository, to maximize or minimize or maintain the CQPs or a key performance indicators (KPIs) at a target value, wherein the CQPs or the KPIs of the UF process units comprises the VCF, the throughput, a fouling index and a time of operation of the UF process units,
wherein the fouling index is an indicator of a remaining useful life (RUL) of a membrane,
wherein the fouling index ranges from 0 to 10, where 0 represents no fouling as in case of fresh membrane, and 10 represents severe fouling such that the membrane is unable to concentrate a feed;
controlling, via the one or more hardware processors, the VCF value and the throughput value for a predefined period of a prediction horizon based on a plurality of trajectory profiles recommended for the feed flow rate, the pressure data, and the feed concentration,
retuning, via the one or more hardware processors, an optimization module using a self-optimization module, for a change observed on at least one of (i) constraint values, (ii) tolerance or convergence criteria of an optimization algorithm;
selecting, via the one or more hardware processors, an optimal optimization algorithm by performing (1) changing an objective function, (2) changing the constraints values, (3) changing parameters the tolerance or the convergence criteria of the optimization algorithm, and (4) choosing an another optimization algorithm;
recommending, via the one or more hardware processors, a trajectory of optimum values of a plurality of operating variables for a time period of a control horizon to the UF process units;
performing, via the one or more hardware processors, a real-time dynamic optimization for a subsequent control horizon while a UF controller in the UF process units is implementing actuation profiles, and further controls, turns off pumps in the UF process units, when a pressure at the pump is more than a critical membrane pressure limit; and
determining, via the one or more hardware processors, time stamps at which the pumps in the UF process units are turned on or turned off based on recommended optimal feed flowrate.