About PlantBrain

Our platform “PlantBrain” leverages AI/ML to learn deeply and uniquely from the data of each schedule, process, asset, conversations and optics, creating algorithmic twins of your operations.

By leveraging advanced analytics, machine learning algorithms, and other AI tools, PlantBrain enables operators to make data-driven decisions that can drive significant improvements in efficiency, reliability, profitability, and safety.

What we can help you achieve

Upto 10%

Increase in Throughput

Upto 80%

Less Unplanned Downtime

Upto 6%

Improvement in Prime Quality Production

Upto 90%

Reduction in Manual Inspection

How PlantBrain works

Integration

Rapid integration on Industrial Data

The Industrial AI platform PlantBrain, begins by ingesting data from various sources, including Historian, SCADA, PLC, Sensors Connectors, CMMS, LIMS, ERP, Engineering information, Camera DVR, Optics Connectors, and other structured or unstructured data repositories.
This data ingestion process involves connecting to the data sources, retrieving the relevant data, and transferring it to the platform for further processing.

Contextualization

Construction of Contextualized Industrial Data Lakehouse

PlantBrain manages and organizes it in a structured manner. This includes storing the data in a centralized repository, such as a contextualized industrial data lakehouse, ensuring efficient data storage and retrieval.
Data management also involves implementing security measures to protect sensitive data, ensuring data integrity and compliance with data governance policies.

1st Principles

Embedded Business Requirements and Engineering Expertise

AI applications are embedded with the specific business requirements and goals of the organization.
Incorporate engineering first principles and expertise into the design and configuration of the applications.

Preprocessing

Data Cleaning and Preprocessing

Identifying and handling missing data, dealing with outliers or noise, and addressing data inconsistencies or errors.
Data preprocessing techniques like data normalization, feature scaling, or dimensionality reduction, may be applied to optimize the data for analysis and modeling.

EDA

Exploratory Data Analysis (EDA)

PlantBrain performs exploratory analysis to gain insights into the data. This involves statistical analysis, data visualization, and data profiling to understand the characteristics, distributions, correlations, and patterns within the data.
EDA helps identify trends, anomalies, or potential relationships between variables, guiding subsequent analysis and modeling processes.

AI Modelling

AI Modeling

PlantBrain employs AI modeling techniques to extract valuable insights and build predictive or prescriptive models. This step includes various processes, such as feature engineering, algorithm selection, model training, and model evaluation.
Feature engineering involves selecting or creating relevant features from the data to feed into the AI models, enhancing their predictive capabilities.
Algorithm selection involves choosing the appropriate machine learning or deep learning algorithms that align with the specific problem and data characteristics.
Model training utilizes historical data to train the AI models, optimizing their performance and accuracy.
Model evaluation assesses the models' performance using evaluation metrics and validation techniques to ensure their reliability and effectiveness in generating insights.

Insights

Diagnostic, Predictive, and Prescriptive Insights

PlantBrain generates insights from the trained AI models, enabling diagnostic, predictive, and prescriptive capabilities.
Diagnostic insights provide an understanding of the current state of the operations, identifying patterns, anomalies, or deviations from normal behavior.
Predictive insights forecast future outcomes or trends based on historical data, enabling proactive decision-making and early identification of potential issues.
Prescriptive insights offer recommendations or optimization strategies to improve operations, guiding decision-making processes to achieve desired outcomes.

Interface

Interactive, Intelligent & Optimized KPIs, Alerts, and Tracking

PlantBrain provides interactive and intelligent visualizations of Key Performance Indicators (KPIs), allowing stakeholders to monitor and track operational performance in real-time.
The platform also incorporates alert mechanisms to notify stakeholders about critical events, anomalies, or deviations from desired performance.
Additionally, the platform offers tracking capabilities to monitor the progress of insights, actions taken, and the impact on operational performance.