Abstract: State of the art techniques used for Flue Gas Desulpharization (FGD) process monitoring fail to comprehend the relationship between various process parameters, which is crucial in determining the performance of a FGD process being monitored. The disclosure herein generally relates to industrial process monitoring, and, more particularly, to a method and system for performance optimization of Flue Gas Desulphurization (FGD) Unit. The system identifies Key Performance Indicators (KPIs) associated with the process being monitored, and identifies parameters associated with each KPI. This information is used to generate several predictive models, from which a predictive model having the highest value of composite model score amongst the predictive models is selected as the predictive model for processing the input data, which is then used to perform optimization of the FGD process.

Abstract: Combined cycle gas turbine (CCGT) power plants have become common for generation of electric power due to their high efficiencies. There are various problem related with improving the efficiency of CCGT plants by optimizing the manipulated variables. The method and system for optimizing the operation of a combined cycle gas turbine has been provided. The system is configured to calculate an optimal value of manipulated variables (MV) with efficiency as one of the key performance parameters (KPI). The MVs from the existing CCGT automation system, i.e. a first set of manipulated variables and the manipulated variables from the optimization approach, i.e. a second set of manipulated variables are combined to determine an optimal set of manipulated variables. The method further checks for the anomalous behavior of the system and define the root cause of the identified anomaly and the operational state of the CCGT plant.

Abstract: Pulverizers are very critical equipment in overall functioning of a plant. They need to be controlled and monitored properly for the optimized operation of the pulverizers. A system and method for performance and health monitoring to optimize operation of a pulverizer is provided. The system comprises a digital twin that can mimic the performance of the pulverizer in real-time and assist the operators in decision making related to operation, maintenance and scheduling. The digital twin is configured to receives real-time sensor data from a plurality of data sources and provides real-time soft sensing of key health and performance parameters of the pulverizer. One more key aspect of the solution is the advisory system that alerts and recommends corrective actions in terms of parameters controlled through other equipment or changes in operation or design or changes in cleaning schedule.

Abstract: This disclosure relates generally to solvothermal synthesis-based method for nanoparticles production. In conventional nanoparticle production methods, precursor loading is limited to below the solubility limit of the precursor and focused completely on tight control of particle size and size distribution that results in low throughput and low yield. The disclosed method includes enabling process conditions to increase metal precursor loading up to the solubility limit of the metal precursor solution. The method includes pouring the pH modifier dropwise into the metal precursor solution with vigorous stirring, resulting in the formation of the metal hydroxide solution. The concentration of metal precursor solution is maintained in range of about 0.025M to 2 M, pH in range of 9 to 12, and stirring speed of 800-1200 rpm. The metal hydroxide solution is heated and a temperature of the reaction in the range of 25° C.-400° C.

Abstract: This disclosure relates to a method and system o real time prediction of tire remaining useful life using a tire digital twin. Herein, the digital twin of the tire monitors a plurality of tires while accounting for runtime as well as parking operation of tires. During runtime, tire goes through multiple operational changes, therefore, the system is configured to estimate the operational changes. The estimation is done in the form of index, which is compared with the manufacturers' recommended value. Similarly, while vehicle is parked, tire still goes through changes which play an important role in its overall health, like, long pending wheel rotation can lead to flat spot. Tire inflation can change owing to cool down effect as well as uncontrolled natural leakages. Further, these parameter indexes are clubbed together to calculate the health index of the tire, which is used to estimate the tire's current remaining useful life.

Abstract: It is important to know the flow rates of oil and gas from individual wells in connected oil and gas wells. The existing methods for multiphase flow measurement are prohibitively expensive and used infrequently. The system is configured to ingest real-time and non-real-time data from a plurality of well data sources. Utilizing this data, a plurality of physics-guided data-driven well surveillance models run in real-time for forecasting a plurality of parameters including the flow rates of oil, gas and brine from individual wells, computing the health of well assets and performing fault detection and localization in well assets. The system is also configured to automatically compose a well performance optimization problem based on the current performance of the wells and health of well assets and solve the problem to identify optimal process settings for improving the operation of connected oil and gas wells.

Abstract: The ability to comprehend the context of a given programming artifact and extracting the underlying functionality is a complex task extending beyond just syntactic and semantic analysis of code. All existing automation capabilities, hence heavily depend on manual involvement of domain experts. Even recent approaches leveraging Machine Learning Capabilities are supervised techniques, whereby the dependency on domain experts still remains—in preparing suitable training sets. A method and system for automated classification of variables using unsupervised distribution agnostic clustering has been provided. The present disclosure focuses to tap the flexibility of the code and presents a domain agnostic approach using unsupervised machine learning which automatically extracts the context from source code, by classifying the underlying elements of the code. The method and system do not require any manual intervention and opens a wide range of opportunities in reverse engineering and variable level analysis space.

Abstract: Industrial processes and equipment are prone to operational changes and faulty operation of such processes and equipment can adversely affect output of the overall setup. Existing systems for monitoring and fault detection consider individual instances of data for fault detection, which may not be suitable for industrial processes. Disclosed herein is a system and a method for anomaly detection in an industrial enterprise. The system collects data from a plurality of sensors as input. The system processes the collected data along temporal dimension, during which the data is split to multiple segments of fixed window size. Data in each segment is processed to identify anomalous data, and data in segments identified as containing the anomalous data is further processed to identify one or more sensors that are faulty and are contributing to the anomalous data.

Abstract: This disclosure relates to a method and system for adaptive learning of physics-based models, data-driven models and hybrid models used in an industrial manufacturing plant. A model-based optimization and advisory device (MOAD) is configured for monitoring performance of data-driven and physics-based models of industrial process units in real-time, computing model quality index for models, triggering adaptive learning of these models and in case of drift in predictions, diagnosing the reasons for drift in predictions. Suggesting re-tuning, re-building, and recreating of the models to achieve highest prediction quality, and automatic deployment of latest models.

Abstract: Monitoring and analysis of plurality of operations in mining and mineral processing is critical to achieve optimized performance. Existing tools are specific to one or other individual operations and this individuality introduces limitations for end to end monitoring of entire mining to mineral processing operations. Method and system for online monitoring and optimization of mining and mineral processing operations providing an integrated approach utilizing short-term mining plan data, information generated using established drill and blast design software, simulation models of fragmentation, crushing, screening, grinding and flotation to arrive at an optimized charge plan and set points for controllers is disclosed. The proposed method and system improves key performance indicators such as cost of mining operations, specific energy consumption in comminution circuit, maximizes yield of desired particle size, and maximizes grade and recovery of mineral of interest while considering operational constraints.

Abstract: This disclosure relates to a method and system for regime-based process optimization of various assets of industrial manufacturing and process plants or units. Operating regimes of assets are identified and a regime similarity score of each asset is computed from regime sequences of integrated industrial data and compared with a given threshold to identify regimes of operation. Operating regimes are matched with regimes of regime database and industrial assets and similar operating regimes are group together. Process optimization is carried out for each group of industrial assets to identify optimum settings in order to maximize output or minimize loss/cost considering process and equipment constraints. Anomalies are analyzed in the unmatched operating regimes and a diagnosis is carried out to identify the root cause for any detected anomalies. Remaining useful life of components in the assets with unmatched operating regimes is estimated to ensure component reliability and to prevent failure.

Abstract: This disclosure relates generally to production of stable and uniformly dispersed nanoparticles. Convention methods of nanoparticle production includes a two-step approach that utilizes additives or surface modifiers. The disclosed method avoids using any additives/surface modifiers owing to the environmental and economic implications. The method includes employing process conditions in a reaction to manipulate electrostatic double layer repulsive forces among nanoparticles to impart the dispersion stability of nanoparticles. The reaction includes pouring pH modifier dropwise into metal precursor solution with vigorous stirring forming metal hydroxide solution, while maintain ranges for concentration of metal precursor solution about 0.15M to 0.75 M, pH about 9 to 12, ionic conductivity about 50 to 200 mS/cm, stirring speed about 800 to 1200 rpm, aging time 6 to 24 hours. The metal hydroxide solution is heated with temperature maintained in range of 100 to 400° C.

Abstract: Fouling is formation of deposits on the heat exchanger surfaces that adversely affects operation of heat exchanger. Fouling can be approximated through a set of estimated heat exchanger parameters, which may not be accurate, leading to uncertainty in operation/maintenance decisions and hence the losses. A system and a method for identification and forecasting fouling of a plurality of heat exchangers in a refinery has been provided. The system comprises a digital replica of the heat exchanger network. The digital replica is configured to receive real-time sensor data from a plurality of data sources and provides real-time soft sensing of key parameters. The system is also configured to diagnose the reasons behind a specific condition of fouling. Further, an advisory is provided, that alerts and recommends corrective actions. The system provides estimate for the remaining useful life (RUL) of the heat exchangers and suggests the cleaning schedule.

Abstract: Data is prone to various attacks such as cyber-security attacks, in any industry. State of the art systems in the domain of data security fail to identify adversarial attacks in real-time, and this leads to security issues, as well as results in the process/system providing unintended results. The disclosure herein generally relates to data security analysis, and, more particularly, to a method and system for assessing impact of adversarial attacks on time series data and providing defenses against such attacks. The system performs adversarial attacks on a selected data-driven model to determine impact of the adversarial attacks on the selected data model, and if the impact is such that performance of the selected data model is less than a threshold, then the selected data model is retrained.

Abstract: Performance and lifespan of batteries deteriorate with time due to various factors. Existing systems for battery management use different approaches for the battery management, and also rely on static value of parameters for State of Health (SOH) and Remaining Useful Life (RUL) estimation, thereby failing to consider current condition of the battery. The disclosure herein generally relates to battery management, and, more particularly, to a method and system for online battery management involving real-time estimation of State of Health (SOH) and Remaining Useful Life (RUL) of a battery, based on real-time data collected from the battery. The system determines state of the battery as one of charging, discharging, and rest. Further, corresponding to the determined state, the system determines values of one or more parameters, and processes the determined values with a battery performance model for online determination of the SOH and RUL.

Abstract: The disclosure generally relates to methods and systems for determining multi-column chromatography process configuration for capturing antibodies. Conventional approaches for design of MCC configuration are limited to rule based, either driven by UV spectroscopic measurements or by performing number of experiments, which involves a lot of material costs and time utilization. The present disclosure solves the technical problem of identifying the operational conditions that optimized the MCC process and the MCC configuration. A multi-objective optimization function defined with one or more decision variables associated with the operating conditions is considered to determine the optimal MCC configuration, while satisfying purification goals. The one or more key performance measures of the MCC process comprises a productivity, a capacity utilization, a product yield, and a product purity.

Abstract: This disclosure relates to optimizing an operation of an equipment by a neural network based optimizer is provided. The method include receiving, information associated with at least one equipment instance (j) as an input at a predefined sequence of timestamps; training, a plurality of simulation models for each equipment instance to obtain a function (fj); processing, the external input parameters (et) to obtain a fixed-dimensional vector and passed as an input to obtain an vector (it); generating, a modified (it) from the output vector (it) based on a domain constraint value; computing, a reward (rt) based on (i) the function (fj), (ii) the modified (it), (iii) the external input parameters (et), and (iv) a reward function (Rj); and iteratively performing the steps of processing, generating, and computing reward (rt) for a series of subsequent equipment instances after expiry of the predefined sequence of timestamps associated with a first equipment instance.

Abstract: An apparatus and a method for continuous solvothermal synthesis of nanoparticles, are provided. The apparatus includes an inlet section, a reactor section, a flexible quenching unit, and an outlet section. The inlet section separately receives reactants including the solvent and a precursor solution that are allowed to flow into the reactor section. The reactor section includes multiple spiral turns such that each of the spiral turns includes a helical channel followed by a counter-helical channel for enabling mixing of the reactants to cause solvothermal reactions between them. The counter-helical channel changes the direction of flow of reactants upon flow of said reactants from the helical channel to the counter-helical channel. The flexible quenching section enclosing a portion of the reactor section quenches a slurry formed as a result of the solvothermal reactions, wherein the slurry includes the nanoparticles of targeted characteristics. The outlet section facilitates withdrawal of the slurry.

Abstract: Hydrogen being a clean, highly abundant and renewable fuel, is a promising alternative for conventional energy sources. Mostly, this hydrogen is stored in the form of hydrides. The existing methods for identification of material for hydrogen storage as expensive and time consuming. A method and system of identification of materials for hydrogen storage has been provided. The method provides a machine learning technique to predict the hydrogen storage capacity of materials, using only the compositional information of the compound. A random forest model used in the work was able to predict the gravimetric hydrogen storage capacities of intermetallic compounds. The method and system is also configured to predict the thermodynamic stability of the intermetallic compound.

Abstract: Performance and lifespan of batteries deteriorate with time due to various factors. Existing systems for battery management use different approaches for the battery management, and also rely on static value of parameters for State of Health (SOH) and Remaining Useful Life (RUL) estimation, thereby failing to consider current condition of the battery. The disclosure herein generally relates to battery management, and, more particularly, to a method and system for online battery management involving real-time estimation of State of Health (SOH) and Remaining Useful Life (RUL) of a battery, based on real-time data collected from the battery. The system determines state of the battery as one of charging, discharging, and rest. Further, corresponding to the determined state, the system determines values of one or more parameters, and processes the determined values with a battery performance model for online determination of the SOH and RUL.