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BRAINBOX ARTIFICIAL INTELLIGENCE PLATFORM 

Connecting the best of two worlds of Physics and Machine Learning.

 
THE TECHNOLOGY

Solves the critical issue of operating, maintaining and repairing, even when you aren't near them physically, thus improving productivity and reducing downtime

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THE TWIN CHARACTERISTICS

The Brainbox Digital Twin creates a comprehensive physical and functional structure of any industrial component, product or system.

  • The Twin is a smart geometric tool which links digital artefacts including engineering data, operational data and behavioral models via numerically and empirically simulated models.

  • The Twin design evolves along with the real system throughout the lifecycle and generates a seed which is shared between knowledge and historical system

  • The Twin is used to describe behavior, trend, patterns, changes due to applied physics phenomena and also to derive solutions relevant for the real system

  • Its a next generation Digital Twin which can bring an impeccable change in future designs of these systems

BENEFITS OF BRAINBOX TWIN

Predicting what is happening on your production line, and predicting what will happen in future, is essential for your overall manufacturing productivity, and business profitability. 

  • Achieve increased reliability of equipment's and production lines

  • Improved OEE through reduced downtime

  • Improved productivity and performance

  • Reduced risk in product availability, marketplace reputations

  • Lower maintenance cost by predicting maintenance issues

  • Increases new business opportunities such as mass customization, operational optimizations and more

  • Improved product quality, and deep insight into the performance of your products

  • All the above combined Brainbox Twin brings in result in the ultimate benefit of improved profits

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BRAINBOX TWIN FOR INDUSTRY

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Analytical Models

state models includes structure, member elements. stiffeners, hydrometeorological and environmental

Information Models

specific systems and components including vibration, stress, thermal and acoustics

Physics Models

numerically simulated governing physics models combined with empirical models of influencing parameters

Domain Models

time domain models of components and systems combined with geometric models for stress and loads

Digitization

sensors, probes integrated with process and various loading data from the asset, Sensor virtualization and data fusion

Brainbox AI

software driven control algorithms with knowledge system and historian library

THE INNOVATION
 

Inventing Novel Technologies is in our DNA

APPLYING ARTIFICIAL INTELLIGENCE

How Brainbox uses artificial intelligence to deliver real-time insight into industrial asset health

We start with the machines and structures every time we invent. We have been working with applied AI for over four years, but we are only in the beginning stages of understanding the true potential of AI. We are researching further on how to improve the health of industrial assets and help our customers solve big problems such as productivity losses due to unplanned downtime, unfortunate situations, etc.

 

We work on real industrial problems that have a tangible impact on our customer's businesses and the world, and the benefit is growing by the day.

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QUANTUM BOUNDARY METHOD

Limiting behaviors and positivity

The most important part of Artificial Intelligence is to create a mere-self of the subject. At Tardid we have been working extensively on Quasi-Local Mass to understand the asset behaviors and subsequent changes limiting to their behaviors and failures. The primary goal of Brainbox is to provide the "Time-To-Failure" matrix, and to do the same digitized data and models are not enough as there are certain invisible factors which has its own relevance stronger than what we perceive. 

Brainbox closely observes

  • Asymptotically Flat Manifolds

  • Quasi Local Mass in AH Manifolds, which includes curvature estimates

  • Positivity factors of the Masses

IN-BUILT GOVERNING PHYSICS MODELS

We have developed a strong chain of distributed Physics-Aware Neural network for effective state estimation

 

Due to the rapid introduction of volatile and renewable energy sources and controllable loads, asset conditions are challenged by unusual fluctuations in operational conditions. Therefore, accurate real-time monitoring of assets becomes increasingly pivotal in order to ensure reliable operations and understanding the continuous stresses causing failures. 

Brainbox has inbuilt classifying models which continuously observes physical phenomena and predicts outcomes of health and new phenomenon. Brainbox processes four types of models to simplify (1) Objects (2) Interactions between objects (3) Systems of objects together with their interactions, and/or (4) processes

COMBINED WITH INFLUENCING PHYSICS META MODELS

Its all about monitoring environmental data in real-time under various cyclic loadings  like, ingress or loss, temperature changes, wind, waves, current, seismic, flows etc.

 

Brainbox considers these influencers to develop neural models and then applies the knowledge to determine the cyclic responses. Furthermore, these models are further categorized into discrete and continuum. These metrics are generated to assess the influencing environmental impact on the assets or its activities. The primary impacts are measured (renewable or non-renewable) to assess situations for reasoning purpose. The ultimate sustainability goal of this technology is to optimize operations and minimize downtimes. Since the complete elimination of these factors is hardly possible, but with advanced tracking and simulation Brainbox can bring an impeccable improvement in future design of these assets.